Life-Cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-Mining Algorithm
Abstract
:1. Introduction
- Examine the travel patterns in a representative intra-city (Abu Dhabi) dataset for existing residential areas or upcoming residential developments.
- Present a systematic way of assessing critical factors eliciting mode choice in commuter market segments towards optimising the social, i.e., stakeholder demands, aspect of the overall LCA of transportation systems and in the process, reduce the user-transport life-cycle energy and environmental load of residential buildings.
- Determine bus service desiderata for policymakers to develop an ameliorated bus service in future, which may divert more building residents to the improved bus service. This can potentially reduce the life-cycle costs and environmental (greenhouse gas emissions, smog, resource and energy use) burdens besides tacking the social parameters (stakeholders’ perspectives) towards optimising overall life-cycle burdens of residential buildings as well improving future building designs, i.e., lesser parking area requirements, more shared walkable spaces, better accessibility etc.
2. Theoretical Background
2.1. Multiscale Effect of Road Network Transport System on Residential Buildings
2.2. Interrelated Urban Form, Transport System and Buildings LCA: Public Transport Accessibility and Residents’ Mode Choices
2.3. Factors Affecting Travel Perception and Mode Choice
2.4. Data Mining for Analysing Travel Datasets
3. Materials and Method
3.1. Survey Design and Analysis
- Modal variability: distribution of generated trips for each mode (i.e., bus and car travel). Five segments as pro-sustainability (PS) passengers (i.e., regular bus travellers and non-users of cars), occasional multimodal (OMD) travellers, frequent car/taxi travellers (FrCT) and environmentally insensitive (EI) commuters (i.e., non-users of public bus service) item.
- Perception of bus service as value for money (VfM): trade-off between quality of ride and level of fare. Three segments of good value for money, borderline value for money and bad value for money.
- Commuter satisfaction from level of service (LoS): ranked based on perception of the current level of network coverage and frequency of buses. Three segments of good level of service, borderline level of service and bad level of service.
3.2. Conceptual Framework—Overall Proposed Modelling Approach
4. Results
4.1. Performance of the Proposed Algorithm
4.2. Phase I Results—Public Responses From Statistically-Significant Rules
4.2.1. Affordability and Constrained Users
4.2.2. Crowded Buses
4.2.3. Dynamics of Bus Fare, Quality and Frequency
4.3. Phase II Results—Policy Insights from Validated Association Rules
4.3.1. Targeting Work Commutes and Full-Time Workers
4.3.2. Impact of Residential Building Typology, Locality and Nodal (Bus-Stop) Characteristics
4.3.3. Budgetary Constraints, Bus Service Frequency and Network Coverage
4.3.4. Journey Time and Ride Quality
4.4. Public-Accorded Desiderata for Value-Added Bus Service for Local Building Residents
4.4.1. Residential Apartment Building Designs May Need to Be Upgraded
4.4.2. Existing Nodal (Bus-Stop) Distribution is Adequate
4.4.3. Optimise Journey Time to Impact Commuter Satisfaction
4.4.4. Bus Service Frequency, Crowded Buses and Level of Fare
5. Discussion
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A
No. | Questions | Responses (please circle as appropriate) | ||||||
---|---|---|---|---|---|---|---|---|
MU | Modal variability (mode use) variables | |||||||
MU1 | How often do you travel by bus? | 1. First time | 2. Less often | 3. 1–3 times/month | 4. Once a week | 5. 2–4 times/week | 6. Over 5 times/week | 7. Never |
MU2 | How often do you travel by private car or taxi? | 1. First time | 2. Less often | 3. 1–3 times/month | 4. Once a week | 5. 2–4 times/week | 6. Over 5 times/week | 7. Never |
LoS | Level of service variables | |||||||
LoS1 | How satisfied are you with current frequency of buses on this route? | 1. Very dissatisfied | 2. Dissatisfied | 3. Neutral | 4. Satisfied | 5. Very satisfied | ||
LoS2 | How satisfied are you with current level of network coverage on this route? | 1. Very dissatisfied | 2. Dissatisfied | 3. Neutral | 4. Satisfied | 5. Very satisfied | ||
VfM | Value for money variables | |||||||
VfM1 | How satisfied are you with current quality of ride on buses on this route? | 1. Very dissatisfied | 2. Dissatisfied | 3. Neutral | 4. Satisfied | 5. Very satisfied | ||
VfM2 | How satisfied are you with current level of fare of buses on this route? | 1. Very dissatisfied | 2. Dissatisfied | 3. Neutral | 4. Satisfied | 5. Very satisfied | ||
ST | Travel Bias (Structural-type Constraints Questions) | |||||||
ST1 | Your accommodation type? | 1. Villa | 2. Apartment | 3. Hotel | 4. Labour camp | 5. Other | ||
ST2 | What is your employment status? | 1. Retired/Other | 2. Visitor | 3. Student | 4. Unemployed | 5. Work part-time | 6. Work full-time | |
ST3 | What is your annual rent? (AED) | 1. Under 10,000 | 2. 10,000–20,000 | 3. 20,001–40,000 | 4. 40,001–60,000 | 5. 60,001–100,000 | 6. Over 100,000 | |
SP | Travel Bias (Spatial-type Constraints Questions) | |||||||
SP1 | Where do you live? | 1. Al-Bateen | 2. Downtown | 3. CBD | 4. Al-Mina | 5. Al-Wahdah | 6. Shakhbout St to city edge | 7. Out of city |
SP2 | Where did you start this journey? | 1. Al-Bateen | 2. Downtown | 3. CBD | 4. Al-Mina | 5. Al-Wahdah | 6. Shakhbout St to city edge | 7. Out of city |
SP3 | Where are you travelling to? | 1. Al-Bateen | 2. Downtown | 3. CBD | 4. Al-Mina | 5. Al-Wahdah | 6. Shakhbout St to city edge | 7. Out of city |
SP4 | Purpose of your journey today? | 1. Work | 2. Study | 3. Business | 4. Personal reason | 5. Shopping | 6. Leisure | |
SP5 | Type of ticket you purchased today? | |||||||
SD | Travel Bias (Socio-demographic Constraints Questions) | |||||||
SD1 | Age (years) | 1. Under 16 | 2. 16 – 24 | 3. 25 – 34 | 4. 35 – 44 | 5. 45 – 64 | 6. Over 65 | |
SD2 | Number of cars in household | 1. No cars | 2. 1 to 2 cars | 3. 3 to 5 cars | 4. Over 5 cars | |||
SD3 | Do you hold a UAE driving license? | 1. Yes | 2. No | |||||
SD4 | Ethnicity/Nationality | 1. UAE | 2. Caucasian | 3. Middle Eastern | 4. African | 5. South Asian | 6. Southeast Asia | 7. Other |
SD5 | Gender | 1. Male | 2. Female | |||||
SD6 | Your gross monthly income in AED | 1. Under 10,000 | 2. 1,000–3,000 | 3. 3,001–5,000 | 4. 5,001–10,000 | 5. 10,001–20,000 | ||
SQ | Perceived Service Quality Questions | |||||||
SQ1 | I am satisfied with journey time | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ2 | The buses are too crowded | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ3 | Bus travel is the easiest way for me | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ4 | I am satisfied with the bus-stops | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ5 | Travel by car or taxi is expensive | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ6 | Traffic congestion delays my journey | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ7 | I chose to live further from work (i.e. near family and friends) and longer commute time is insignificant to me | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ8 | I chose to live closer to work as shorter commute time is significant to me | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ9 | Willing to pay more for bus travel if I always had a seat | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree | ||
SQ10 | I am satisfied with the existing distribution of bus-stops on the current travel route (Today it took me longer/many minutes to get to bus-stop) | 1. Strongly disagree | 2. Disagree | 3. Neutral | 4. Agree | 5. Strongly agree |
Variables | N (Valid) | Mean | Standard Deviation | Variance |
---|---|---|---|---|
Frequency of bus travel | 1517 | 5.20 | 1.149 | 1.321 |
Frequency of car travel | 1305 | 2.94 | 1.414 | 2.000 |
Satisfaction with frequency of buses | 1512 | 3.70 | 0.899 | 0.809 |
Satisfaction with network coverage | 1494 | 3.74 | 0.890 | 0.793 |
Satisfaction with quality of ride | 1501 | 3.98 | 0.976 | 0.953 |
Satisfaction with level of fare | 1505 | 3.37 | 1.351 | 1.824 |
Your accommodation type? | 1509 | 2.52 | 1.390 | 1.933 |
What is your employment status? | 1505 | 5.55 | 1.103 | 1.216 |
What is your annual rent? (AED) | 1384 | 2.09 | 1.252 | 1.566 |
Where do you live? | 1519 | 3.76 | 1.814 | 3.291 |
Where did you start this journey? | 1518 | 3.35 | 1.845 | 3.405 |
Where are you travelling to? | 1515 | 3.38 | 1.823 | 3.323 |
Purpose of your journey today? | 1514 | 3.25 | 2.130 | 4.539 |
Type of ticket you purchased today? | 1516 | 1.32 | 0.732 | 0.536 |
Age (years) | 1507 | 3.21 | 0.923 | 0.851 |
Number of cars in household | 1440 | 0.17 | 0.392 | 0.153 |
Do you hold a UAE driving license? | 1503 | 1.79 | 0.411 | 0.169 |
Ethnicity/Nationality | 1507 | 5.02 | 1.070 | 1.145 |
Gender | 1509 | 1.13 | 0.333 | 0.111 |
Your gross monthly income in AED | 1385 | 2.47 | 1.048 | 1.099 |
I am satisfied with journey time | 1508 | 3.95 | 0.826 | 0.682 |
The buses are too crowded | 1519 | 0.60 | 0.489 | 0.240 |
Bus travel is the easiest way for me | 1519 | 0.66 | 0.475 | 0.226 |
I am satisfied with the bus-stops | 1496 | 3.38 | 1.125 | 1.265 |
Travel by car or taxi is expensive | 1519 | 0.45 | 0.497 | 0.247 |
Traffic congestion delays my journey | 1519 | 0.35 | 0.478 | 0.228 |
I chose to live further from work | 1519 | 0.66 | 0.472 | 0.223 |
I chose to live closer to work | 1319 | 4.70 | 2.70 | 7.301 |
Willing to pay more for bus seat | 1519 | 0.36 | 0.479 | 0.229 |
Satisfied with existing bus-stop distribution | 1519 | 2.10 | 0.676 | 0.457 |
References
- Borrego, C.; Tchepel, O.; Barros, N.; Miranda, A.I. Impact of road traffic emissions on air quality of the Lisbon region. Atmos. Environ. 2000, 34, 4683–4690. [Google Scholar] [CrossRef]
- Gray, D.; Laing, R.; Docherty, I. Delivering lower carbon urban transport choices: European ambition meets the reality of institutional (mis)alignment. Environ. Plan. A Econ. Space 2016, 49, 226–242. [Google Scholar] [CrossRef] [Green Version]
- Crispino, M.; D’Apuzzo, M. Measurement and prediction of traffic-induced vibrations in a heritage building. J. Sound Vib. 2001, 246, 319–335. [Google Scholar] [CrossRef]
- Rychtáriková, M.; Jedovnický, M.; Vargová, A.; Glorieux, C. Synthesis of a Virtual Urban Soundscape. Buildings 2014, 4, 139–154. [Google Scholar] [CrossRef] [Green Version]
- Hasan, U.; Chegenizadeh, A.; Budihardjo, M.; Nikraz, H. A review of the stabilisation techniques on expansive soils. Aust. J. Basic Appl. Sci. 2015, 9, 541–548. [Google Scholar]
- Hasan, U. Experimental Study on bentonite Stabilisation Using Construction Waste and Slag. Ph.D. Thesis, Curtin University, Perth, Australia, 2015. [Google Scholar]
- Le, A.B.D.; Whyte, A.; Biswas, W.K. Carbon footprint and embodied energy assessment of roof-covering materials. Clean Technol. Environ. Policy 2018. [Google Scholar] [CrossRef]
- Mawed, M.; Al-Hajj, A.; Alshemery, A.A. The impacts of sustainable practices on UAE mosques’ life cycle cost. In Proceedings of the Smart, Sustainable and Healthy Cities: 1st International Conference of the CIB Middle East and North Africa Research Network, Abu Dhabi, UAE, 14–16 December 2014; pp. 307–324. [Google Scholar]
- Alqahtani, A.; Whyte, A. Evaluation of non-cost factors affecting the life cycle cost: An exploratory study. J. Eng. Des. Technol. 2016, 14, 818–834. [Google Scholar] [CrossRef]
- Dodd, N.; Donatello, S.; Garbarino, E.; Gama-Caldas, M. Identifying Macro-Objectives for the Life Cycle Environmental Performance and resource Efficiency of EU Buildings; JRC EU Commission: Luxembourg, 2015; p. 117. [Google Scholar]
- Badland, H.; Schofield, G. Transport, urban design, and physical activity: An evidence-based update. Transp. Res. Part D Transp. Environ. 2005, 10, 177–196. [Google Scholar] [CrossRef]
- Yigitcanlar, T.; Kamruzzaman, M.; Teriman, S. Neighborhood Sustainability Assessment: Evaluating Residential Development Sustainability in a Developing Country Context. Sustainability 2015, 7, 2570–2602. [Google Scholar] [CrossRef] [Green Version]
- Jabareen, Y.R. Sustainable Urban Forms: Their Typologies, Models, and Concepts. J. Plan. Educ. Res. 2006, 26, 38–52. [Google Scholar] [CrossRef]
- Zimring, C.; Joseph, A.; Nicoll, G.L.; Tsepas, S. Influences of building design and site design on physical activity: Research and intervention opportunities. Am. J. Prev. Med. 2005, 28, 186–193. [Google Scholar] [CrossRef] [PubMed]
- Cervero, R. Public transport and sustainable urbanism: Global lessons. In Transit Oriented Development; Routledge: London, UK, 2009; pp. 23–35. [Google Scholar]
- De Luca, S. Public engagement in strategic transportation planning: An analytic hierarchy process based approach. Transp. Policy 2014, 33, 110–124. [Google Scholar] [CrossRef]
- Leyden, K.M.; Slevin, A.; Grey, T.; Hynes, M.; Frisbaek, F.; Silke, R. Public and Stakeholder Engagement and the Built Environment: A Review. Curr. Environ. Health Rep. 2017, 4, 267–277. [Google Scholar] [CrossRef] [PubMed]
- Stephan, A.; Stephan, L. Life cycle energy and cost analysis of embodied, operational and user-transport energy reduction measures for residential buildings. Appl. Energy 2016, 161, 445–464. [Google Scholar] [CrossRef]
- Hasan, U.; Whyte, A.; Al Jassmi, H. Critical review and methodological issues in integrated life-cycle analysis on road networks. J. Clean. Prod. 2019, 206, 541–558. [Google Scholar] [CrossRef]
- Stephan, A.; Crawford, R.H.; de Myttenaere, K. A comprehensive assessment of the life cycle energy demand of passive houses. Appl. Energy 2013, 112, 23–34. [Google Scholar] [CrossRef] [Green Version]
- Diana, M. Measuring the satisfaction of multimodal travelers for local transit services in different urban contexts. Transp. Res. Part A Policy Pract. 2012, 46, 1–11. [Google Scholar] [CrossRef] [Green Version]
- De Vos, J.; Mokhtarian, P.L.; Schwanen, T.; Van Acker, V.; Witlox, F. Travel mode choice and travel satisfaction: Bridging the gap between decision utility and experienced utility. Transportation 2016, 43, 771–796. [Google Scholar] [CrossRef]
- Anderson, J.E.; Wulfhorst, G.; Lang, W. Expanding the use of life-cycle assessment to capture induced impacts in the built environment. Build. Environ. 2015, 94, 403–416. [Google Scholar] [CrossRef] [Green Version]
- Batarce, M.; Muñoz, J.C.; de Dios Ortúzar, J.; Raveau, S.; Mojica, C.; Ríos, R.A. Use of Mixed Stated and Revealed Preference Data for Crowding Valuation on Public Transport in Santiago, Chile. Transp. Res. Rec. J. Transp. Res. Board 2015, 2535, 73–78. [Google Scholar] [CrossRef]
- Stathopoulos, A.; Cirillo, C.; Cherchi, E.; Ben-Elia, E.; Li, Y.-T.; Schmöcker, J.-D. Innovation adoption modeling in transportation: New models and data. J. Choice Model. 2017, 25, 61–68. [Google Scholar] [CrossRef]
- Golob, T.F.; Hensher, D.A. The trip chaining activity of Sydney residents: A cross-section assessment by age group with a focus on seniors. J. Transp. Geogr. 2007, 15, 298–312. [Google Scholar] [CrossRef]
- Diana, M.; Pronello, C. Traveler segmentation strategy with nominal variables through correspondence analysis. Transp. Policy 2010, 17, 183–190. [Google Scholar] [CrossRef]
- Tan, P.-N.; Steinbach, M.; Kumar, V. Introduction to Data Mining, 1st ed.; Addison-Wesley Longman Publishing Co., Inc.: Boston, MA, USA, 2005. [Google Scholar]
- Elder, J. Handbook of Statistical Analysis and Data Mining Applications, 1st ed.; Nisbet, R., Miner, G., Eds.; Academic Press: Boston, MA, USA, 2009; p. 864. [Google Scholar]
- Al-Hussaeni, K.; Fung, B.C.M.; Iqbal, F.; Dagher, G.G.; Park, E.G. SafePath: Differentially-private publishing of passenger trajectories in transportation systems. Comput. Netw. 2018, 143, 126–139. [Google Scholar] [CrossRef]
- Laing, R.; Tait, E.; Gray, D. Public engagement and participation in sustainable transport issues. In Proceedings of the Construction, Building and Real Estate Research Conference of the Royal Institution of Chartered Surveyors, Las Vegas, NV, USA, 11–13 September 2012. [Google Scholar]
- Hasan, U.; Whyte, A.; Al Jassmi, H. Framework for Delivering an AV-based Mass Mobility Solution: Integrating Government-Consumer Actors and Life-cycle Analysis of Transportation Systems. In Proceedings of the 46th European Transport Conference, Dublin, Ireland, 10–12 October 2018; p. 18. [Google Scholar]
- Hasan, U.; Whyte, A.; Al Jassmi, H. Public-Transport System Management: Improving Service Satisfaction and Sustainable Uptake. 2018. submitted. [Google Scholar]
- Chu, K.; Chapleau, R. Augmenting transit trip characterization and travel behavior comprehension. Transp. Res. Rec. J. Transp. Res. Board 2010, 2183, 29–40. [Google Scholar] [CrossRef]
- Diana, M. Studying patterns of use of transport modes through data mining: Application to us national household travel survey data set. Transp. Res. Rec. J. Transp. Res. Board 2012, 2308, 1–9. [Google Scholar] [CrossRef]
- Gürbüz, F.; Turna, F. Rule extraction for tram faults via data mining for safe transportation. Transp. Res. Part A Policy Pract. 2018, 116, 568–579. [Google Scholar] [CrossRef]
- Ordonez, C. Association rule discovery with the train and test approach for heart disease prediction. IEEE Trans. Inf. Technol. Biomed. 2006, 10, 334–343. [Google Scholar] [CrossRef]
- Shaharanee, I.N.M.; Hadzic, F.; Dillon, T.S. Interestingness measures for association rules based on statistical validity. Knowl. Based Syst. 2011, 24, 386–392. [Google Scholar] [CrossRef]
- Lazcorreta, E.; Botella, F.; Fernández-Caballero, A. Towards personalized recommendation by two-step modified Apriori data mining algorithm. Expert Syst. Appl. 2008, 35, 1422–1429. [Google Scholar] [CrossRef]
- Whyte, A.; Laing, R. Deconstruction and reuse of building material, with specific reference to historic structures. In Proceedings of the 1st Australasia and South East Asia Conference in Structural Engineering and Construction (ASEA-SEC-1), Perth, Australia, 28 November–2 December 2012; pp. 171–176. [Google Scholar]
- Whyte, A. Life-Cycle Assessment of Built-Asset Waste Materials: Sustainable Disposal Options; Lambert Aademic Publishing: Saarbrucken, Germany, 2012. [Google Scholar]
- NSAI. EN 15978:2011: Sustainability of Construction Works—Assessment of Environmental Performance of Buildings—Calculation Method; British Standard Institute: London, UK, 2011. [Google Scholar]
- AFNOR Normalisation. CEN/TC 350 Sustainability of Construction Works. Available online: http://portailgroupe.afnor.fr/public_espacenormalisation/CENTC350/index.html (accessed on 10 December 2018).
- International Standards Organisation (ISO). ISO/TS 12720: Sustainability in Buildings and Civil Engineering Works—Guidelines on the Application of the General Principles in ISO 15392; ISO: Geneva, Switzerland, 2014. [Google Scholar]
- Giorgi, S.; Lavagna, M.; Campioli, A. Guidelines for Effective and Sustainable Recycling of Construction and Demolition Waste. In Designing Sustainable Technologies, Products and Policies: From Science to Innovation; Benetto, E., Gericke, K., Guiton, M., Eds.; Springer International Publishing: Cham, Switzerland, 2018; pp. 211–221. [Google Scholar]
- HM Government. Environmental Taxes, Reliefs and Schemes for Businesses. Available online: https://www.gov.uk/green-taxes-and-reliefs/aggregates-levy (accessed on 12 December 2018).
- Bleischwitz, R. Towards a resource policy—Unleashing productivity dynamics and balancing international distortions. Miner. Econ. 2012, 24, 135–144. [Google Scholar] [CrossRef]
- Coelho, A.; de Brito, J. Economic viability analysis of a construction and demolition waste recycling plant in Portugal—Part I: Location, materials, technology and economic analysis. J. Clean. Prod. 2013, 39, 338–352. [Google Scholar] [CrossRef]
- Mulley, C.; Ma, L.; Clifton, G.; Yen, B.; Burke, M. Residential property value impacts of proximity to transport infrastructure: An investigation of bus rapid transit and heavy rail networks in Brisbane, Australia. J. Transp. Geogr. 2016, 54, 41–52. [Google Scholar] [CrossRef]
- Strømann-Andersen, J.; Sattrup, P.A. The urban canyon and building energy use: Urban density versus daylight and passive solar gains. Energy Build. 2011, 43, 2011–2020. [Google Scholar] [CrossRef]
- Steemers, K. Energy and the city: Density, buildings and transport. Energy Build. 2003, 35, 3–14. [Google Scholar] [CrossRef]
- Tronchin, L.; Manfren, M.; Nastasi, B. Energy efficiency, demand side management and energy storage technologies—A critical analysis of possible paths of integration in the built environment. Renew. Sustain. Energy Rev. 2018, 95, 341–353. [Google Scholar] [CrossRef]
- Norman, J.; MacLean, H.L.; Kennedy, C.A. Comparing High and Low Residential Density: Life-Cycle Analysis of Energy Use and Greenhouse Gas Emissions. J. Urban Plan. Dev. 2006, 132, 10–21. [Google Scholar] [CrossRef]
- Cuéllar-Franca, R.M.; Azapagic, A. Environmental impacts of the UK residential sector: Life cycle assessment of houses. Build. Environ. 2012, 54, 86–99. [Google Scholar] [CrossRef]
- Stephan, A.; Crawford, R.H.; de Myttenaere, K. Towards a comprehensive life cycle energy analysis framework for residential buildings. Energy Build. 2012, 55, 592–600. [Google Scholar] [CrossRef] [Green Version]
- Stephan, A.; Crawford, R.H.; de Myttenaere, K. Towards a more holistic approach to reducing the energy demand of dwellings. Procedia Eng. 2011, 21, 1033–1041. [Google Scholar] [CrossRef]
- Anderson, J.E.; Wulfhorst, G.; Lang, W. Energy analysis of the built environment—A review and outlook. Renew. Sustain. Energy Rev. 2015, 44, 149–158. [Google Scholar] [CrossRef]
- Dell’Olio, L.; Ibeas, A.; Cecín, P. Modelling user perception of bus transit quality. Transp. Policy 2010, 17, 388–397. [Google Scholar] [CrossRef]
- De Oña, J.; de Oña, R.; Calvo, F.J. A classification tree approach to identify key factors of transit service quality. Expert Syst. Appl. 2012, 39, 11164–11171. [Google Scholar] [CrossRef] [Green Version]
- Schmid, B.; Schmutz, S.; Axhausen, K.W. Explaining mode choice, taste heterogeneity, and cost sensitivity in a post-car world. In Proceedings of the 95th Annual Meeting of the Transportation Research Board, Washington, DC, USA, 10–14 January 2016. [Google Scholar]
- Stradling, S. Determinants of Car Dependence. In Threats from Car Traffic to the Quality of Urban Life; Garling, T., Steg, L., Eds.; Emerald Group Publishing Limited: New York, NY, USA, 2007; pp. 187–204. [Google Scholar]
- Chen, C.; Gong, H.; Paaswell, R. Role of the built environment on mode choice decisions: Additional evidence on the impact of density. Transportation 2008, 35, 285–299. [Google Scholar] [CrossRef]
- Friman, M.; Fellesson, M. Service supply and customer satisfaction in public transportation: The quality paradox. J. Public Transp. 2009, 12, 57–69. [Google Scholar] [CrossRef]
- Menichetti, D.; Vuren, T.V. Modelling a low-carbon city. Proc. Inst. Civ. Eng. Transp. 2011, 164, 141–151. [Google Scholar] [CrossRef]
- Environment Agency (Abu Dhabi). Greenhouse Gas Inventory for Abu Dhabi Emirate—Inventory Results Executive Summary; Environment Agency (Abu Dhabi): Abu Dhabi, UAE, 2012; p. 25.
- Al Tayer, S.M. UAE is committed to reducing carbon footprint. In Khaleej Times; Galadari Printing and Publishing LLC: Dubai, UAE, 2018. [Google Scholar]
- Liu, F.; Xu, R.; Fan, W.; Jiang, Z. Data analytics approach for train timetable performance measures using automatic train supervision data. IET Intell. Transp. Syst. 2018, 12, 568–577. [Google Scholar] [CrossRef]
- IPCC. Climate Change 2007: The Physical Science Basis. Contribution of Working Group I, II and III to the Fourth Assessment Report of the IPCC; Pachauri, R.K., Reisinger, A., Core Writing Team, Eds.; Intergovernmental Panel on Climate Change: Geneva, Switzerland, 2008; p. 104. [Google Scholar]
- Hasan, U.; Chegenizadeh, A.; Budihardjo, M.A.; Nikraz, H. Experimental Evaluation of Construction Waste and Ground Granulated Blast Furnace Slag as Alternative Soil Stabilisers. Geotech. Geol. Eng. 2016, 34, 1707–1722. [Google Scholar] [CrossRef]
- Hasan, U.; Chegenizadeh, A.; Budihardjo, M.A.; Nikraz, H. Shear Strength Evaluation Of Bentonite Stabilised With Recycled Materials. J. GeoEng. 2016, 11, 59–73. [Google Scholar]
- Hasan, U.; Chegenizadeh, A.; Nikraz, H. Nanotechnology Future and Present in Construction Industry: Applications in Geotechnical Engineering. In Advanced Research on Nanotechnology for Civil Engineering Applications; IGI Global: Hershey, PA, USA, 2016; pp. 141–179. [Google Scholar]
- Ponte, C.; Melo, H.P.M.; Caminha, C.; Andrade, J.S., Jr.; Furtado, V. Traveling heterogeneity in public transportation. EPJ Data Sci. 2018, 7, 42. [Google Scholar] [CrossRef]
- Agrawal, R.; Imieliński, T.; Swami, A. Mining association rules between sets of items in large databases. In Proceedings of the ACM SIGMOD International Conference on Management of Data, Washington, DC, USA, 25–28 March 1993; pp. 207–216. [Google Scholar]
- Agrawal, R.; Srikant, R. Fast algorithms for mining association rules. In Proceedings of the 20th Very Large Data Bases (VLDB) Conference, Santiago de Chile, Chile, 12–15 September 1994; Bocca, J.B., Jarke, M., Zaniolo, C., Eds.; Morgan Kaufmann Publishers Inc.: San Francisco, CA, USA, 1994; pp. 487–499. [Google Scholar]
- Nahar, J.; Imam, T.; Tickle, K.S.; Chen, Y.-P.P. Association rule mining to detect factors which contribute to heart disease in males and females. Expert Syst. Appl. 2013, 40, 1086–1093. [Google Scholar] [CrossRef]
- Hu, L.; Zhuo, G.; Qiu, Y. Application of Apriori Algorithm to the Data Mining of the Wildfire. In Proceedings of the 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, Tianjin, China, 14–16 August 2009; pp. 426–429. [Google Scholar]
- Pande, A.; Abdel-Aty, M. Discovering indirect associations in crash data through probe attributes. Transp. Res. Rec. J. Transp. Res. Board 2008, 2083, 170–179. [Google Scholar] [CrossRef]
- Tan, P.-N.; Kumar, V.; Srivastava, J. Selecting the right objective measure for association analysis. Inf. Syst. 2004, 29, 293–313. [Google Scholar] [CrossRef] [Green Version]
- Nosratabadi, H.E.; Pourdarab, S.; Nadali, A.; Khalilinezhad, M. Evaluating discovered rules from association rules mining based on interestingness measures using fuzzy expert system. In Proceedings of the Fourth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2011), Stevens Point, WI, USA, 4–6 August 2011; pp. 112–117. [Google Scholar]
- Ma, W.-M.; Wang, K.; Liu, Z.-P. Mining potentially more interesting association rules with fuzzy interest measure. Soft Comput. 2011, 15, 1173–1182. [Google Scholar] [CrossRef]
- Wu, X.; Zhang, C.; Zhang, S. Efficient mining of both positive and negative association rules. ACM Trans. Inf. Syst. 2004, 22, 381–405. [Google Scholar] [CrossRef] [Green Version]
- Cherchi, E.; Cirillo, C.; de Dios Ortúzar, J. Modelling correlation patterns in mode choice models estimated on multiday travel data. Transp. Res. Part A Policy Pract. 2017, 96, 146–153. [Google Scholar] [CrossRef]
- Arbabi, H.; Mayfield, M. Urban and Rural—Population and Energy Consumption Dynamics in Local Authorities within England and Wales. Buildings 2016, 6, 34. [Google Scholar] [CrossRef]
- AECOM. Working Paper No. 1: Task 3 Review and Recommendations on the Proposed Travel Surveys; Abu Dhabi Department of Transport: Abu Dhabi, UAE, 2015; p. 94.
- Osborne, J.W. Conceptual and Practical Introduction to Testing Assumptions and Cleaning Data for Logistic Regression. In Best Practices in Logistic Regression; SAGE Publications: Thousand Oaks, CA, USA, 2014; p. 488. [Google Scholar]
- Shaheen, M.; Shahbaz, M. An Algorithm of Association Rule Mining for Microbial Energy Prospection. Sci. Rep. 2017, 7, 46108. [Google Scholar] [CrossRef]
- Bachman, W.; Katzev, R. The effects of non-contingent free bus tickets and personal commitment on urban bus ridership. Transp. Res. Part A Gen. 1982, 16, 103–108. [Google Scholar] [CrossRef]
- Savage, I. The dynamics of fare and frequency choice in urban transit. Transp. Res. Part A Policy Pract. 2010, 44, 815–829. [Google Scholar] [CrossRef]
- Tirachini, A. Estimation of travel time and the benefits of upgrading the fare payment technology in urban bus services. Transp. Res. Part C Emerg. Technol. 2013, 30, 239–256. [Google Scholar] [CrossRef]
- Tirachini, A.; Hensher, D.A.; Rose, J.M. Multimodal pricing and optimal design of urban public transport: The interplay between traffic congestion and bus crowding. Transp. Res. Part B Methodol. 2014, 61, 33–54. [Google Scholar] [CrossRef] [Green Version]
- Wang, T.; Chen, C. Attitudes, mode switching behavior, and the built environment: A longitudinal study in the Puget Sound Region. Transp. Res. Part A Policy Pract. 2012, 46, 1594–1607. [Google Scholar] [CrossRef]
- Horner, M.W.; Mefford, J.N. Examining the Spatial and Social Variation in Employment Accessibility: A Case Study of Bus Transit in Austin, Texas. In Access to Destinations; Emerald Group Publishing Limited: New York, NY, USA, 2005; pp. 193–214. [Google Scholar]
- Currie, G.; De Gruyter, C. Exploring links between the sustainability performance of urban public transport and land use in international cities. J. Transp. Land Use 2018, 11, 325–342. [Google Scholar] [CrossRef]
- Kennedy, C.; Miller, E.; Shalaby, A.; Maclean, H.; Coleman, J. The Four Pillars of Sustainable Urban Transportation. Transp. Rev. 2005, 25, 393–414. [Google Scholar] [CrossRef]
- Abu Dhabi Government. Abu Dhabi Emirate: Facts and Figures. Available online: https://www.abudhabi.ae/portal/public/en/abu-dhabi-emirate/abu-dhabi-emirate-facts-and-figures;jsessionid=zKnROF_msRJQoP3Lu22DJzCLFXxFVXf5ED6y_2KpOCR0wIG8-4k7!496354345!-733067616!1541108424678 (accessed on 2 November 2018).
- Flint, S. Living in: Abu Dhabi. Available online: http://www.bbc.com/travel/story/20131203-living-in-abu-dhabi (accessed on 2 November 2018).
- Hensher, D.A.; Stopher, P.; Bullock, P. Service quality––Developing a service quality index in the provision of commercial bus contracts. Transp. Res. Part A Policy Pract. 2003, 37, 499–517. [Google Scholar] [CrossRef]
- Redman, L.; Friman, M.; Gärling, T.; Hartig, T. Quality attributes of public transport that attract car users: A research review. Transp. Policy 2013, 25, 119–127. [Google Scholar] [CrossRef]
- Sottile, E.; Cherchi, E.; Meloni, I. Measuring Soft Measures Within a Stated Preference Survey: The Effect of Pollution and Traffic Stress on Mode Choice. Transp. Res. Procedia 2015, 11, 434–451. [Google Scholar] [CrossRef] [Green Version]
- Santos, G.; Bhakar, J. The impact of the London congestion charging scheme on the generalised cost of car commuters to the city of London from a value of travel time savings perspective. Transp. Policy 2006, 13, 22–33. [Google Scholar] [CrossRef] [Green Version]
- Trigaux, D.; Wijnants, L.; De Troyer, F.; Allacker, K. Life cycle assessment and life cycle costing of road infrastructure in residential neighbourhoods. Int. J. Life Cycle Assess. 2017, 22, 938–951. [Google Scholar] [CrossRef]
- Kuo, Y. Using simulated annealing to minimize fuel consumption for the time-dependent vehicle routing problem. Comput. Ind. Eng. 2010, 59, 157–165. [Google Scholar] [CrossRef]
- Biswas, W.K.; Thompson, B.C.; Islam, M.N. Environmental life cycle feasibility assessment of hydrogen as an automotive fuel in Western Australia. Int. J. Hydrogen Energy 2013, 38, 246–254. [Google Scholar] [CrossRef]
- Nguyen-Phuoc, D.Q.; Currie, G.; De Gruyter, C.; Young, W. How do public transport users adjust their travel behaviour if public transport ceases? A qualitative study. Transp. Res. Part F Traffic Psychol. Behav. 2018, 54, 1–14. [Google Scholar] [CrossRef]
- Nobis, C. Multimodality: Facets and Causes of Sustainable Mobility Behavior. Transp. Res. Rec. J. Transp. Res. Board 2007, 2010, 35–44. [Google Scholar] [CrossRef]
- Thøgersen, J. Promoting public transport as a subscription service: Effects of a free month travel card. Transp. Policy 2009, 16, 335–343. [Google Scholar] [CrossRef]
- Hrelja, R. Integrating transport and land-use planning? How steering cultures in local authorities affect implementation of integrated public transport and land-use planning. Transp. Res. Part A Policy Pract. 2015, 74, 1–13. [Google Scholar] [CrossRef] [Green Version]
- Rowe, D.H.; Christine Bae, C.H.; Shen, Q. Evaluating the Impact of Transit Service on Parking Demand and Requirements. Transp. Res. Rec. 2011, 2245, 56–62. [Google Scholar] [CrossRef]
- Chien, S.I.; Qin, Z. Optimization of bus stop locations for improving transit accessibility. Transp. Plan. Technol. 2004, 27, 211–227. [Google Scholar] [CrossRef]
- Heinen, E.; Chatterjee, K. The same mode again? An exploration of mode choice variability in Great Britain using the National Travel Survey. Transp. Res. Part A Policy Pract. 2015, 78, 266–282. [Google Scholar] [CrossRef]
- Milakis, D.; Cervero, R.; Van Wee, B. Stay local or go regional? Urban form effects on vehicle use at different spatial scales: A theoretical concept and its application to the San Francisco Bay Area. J. Transp. Land Use 2015, 8, 59–86. [Google Scholar] [CrossRef]
- Yao, B.; Hu, P.; Lu, X.; Gao, J.; Zhang, M. Transit network design based on travel time reliability. Transp. Res. Part C Emerg. Technol. 2014, 43, 233–248. [Google Scholar] [CrossRef]
- Kingham, S.; Dickinson, J.; Copsey, S. Travelling to work: Will people move out of their cars. Transp. Policy 2001, 8, 151–160. [Google Scholar] [CrossRef]
- Eriksson, L.; Friman, M.; Gärling, T. Stated reasons for reducing work-commute by car. Transp. Res. Part F Traffic Psychol. Behav. 2008, 11, 427–433. [Google Scholar] [CrossRef]
- Thøgersen, J.; Møller, B. Breaking car use habits: The effectiveness of a free one-month travelcard. Transportation 2008, 35, 329–345. [Google Scholar] [CrossRef]
- Trépanier, M.; Habib, K.M.N.; Morency, C. Are transit users loyal? Revelations from a hazard model based on smart card data. Can. J. Civ. Eng. 2012, 39, 610–618. [Google Scholar] [CrossRef]
Outer-Urban or Suburban Routes | Route Number |
---|---|
Al Mina Souq ↔ Khalifa Park | 056 |
Petroleum Institute ↔ Tourist Club Municipality | 054 |
Abu Dhabi Courts ↔ Al Marina | 034 |
Downtown City and Urban Routes | Route Number |
Al Mina Fish Harbour ↔ Al Marina Mall | 011 |
Al Mina Souq ↔ Al Marina Mall | 009 |
Al Mina Road Tourist Club ↔ Al Marina | 008 |
Tourist Club Municipality ↔ Al Marina | 007 |
Al Mina ISC and Tourist Club ↔ Ras Al Akhdhar | 006 |
Rules | Predictor Variables | Odds Ratio | Response Variable Category | Model χ2 *** | – 2LL † | Group |
---|---|---|---|---|---|---|
1 | Employed full-time Willingness to pay more for seat | 6.71*** 0.47*** | Bus travel > 2 times a week | 72.68 | 72.68 | PS |
2 | 5–15 min to bus stop No cars | 2.22** 1.86* | Bus travel > 2 times a week | 67.18 | 67.18 | PS |
1 | Car/taxi is inexpensive Weekday | 1.30* 0.27*** | Once a week by car | 140.07 | 1.54 | OMD |
1 | Living near friends & family is important Car/taxi is inexpensive | 0.47*** 0.85* | First time by bus | 39.96 | 46.46 | EI |
2 | Buses are crowded 5–15 min to bus stop | 2.04*** 2.21** | First time by bus | 57.41 | 41.62 | EI |
1 | Male Bus travel is easy | 14.1*** 1.27* | Very satisfied with frequency of bus | 42.48 | 57.41 | Good LoS |
2 | Very satisfied with network coverage Very Satisfied with quality of ride | 2.88* 2.67** | Very satisfied with frequency of bus | 352.27 | 167.16 | Good LoS |
3 | Very satisfied with frequency of buses | 7.49*** | Very satisfied with network coverage | 354.67 | 140.07 | Good LoS |
4 | Male Employed full-time Bus travel is easy | 6.06** 5.61** 1.30* | Satisfied with network coverage | 39.23 | 139.62 | Good LoS |
5 | Satisfied with journey time | 13.22*** | Satisfied with network coverage | 214.14 | 42.48 | Good LoS |
1 | Neutral on network coverage | 7.08*** | Neutral on frequency of buses | 348.09 | 140.74 | Borderline LoS |
2 | Willingness to pay more for seat 5–15 min to bus stop | 1.87*** 0.56* | Neutral on network coverage | 47.70 | 352.27 | Borderline LoS |
1 | Car/taxi is inexpensive Buses are crowded | 0.53*** 1.62*** | Dissatisfied with frequency of bus | 38.145 | 155.53 | Bad LoS |
2 | Dissatisfied with frequency of buses | 10.45*** | Dissatisfied with network coverage | 354.67 | 385.31 | Bad LoS |
1 | Satisfied with frequency of buses | 9.65*** | Satisfied with quality of ride | 164.79 | 38.15 | Good VfM |
2 | FBT 5 or more times a week Employed full-time Weekday | 6.72*** 3.66*** 3.69*** | Very satisfied with level of fare | 671.05 | 214.14 | Good VfM |
3 | Very Satisfied with quality of ride | 2.86*** | Very satisfied with level of fare | 97.02 | 47.71 | Good VfM |
4 | Employed full-time Car/taxi is inexpensive | 3.48*** 1.24* | Very satisfied with level of fare | 54.11 | 354.67 | Good VfM |
5 | Satisfied with journey time Employed full-time | 3.68** 6.36*** | Satisfied with level of fare | 66.09 | 26.66 | Good VfM |
1 | Neutral on network coverage | 3.89*** | Neutral on quality of ride | 210.79 | 354.67 | Borderline VfM |
2 | Neutral on frequency of buses | 8.48*** | Neutral on quality of ride | 164.79 | 39.23 | Borderline VfM |
3 | Employed full-time Willingness to pay more for seat | 4.95** 1.16* | Neutral on level of fare | 62.22 | 7.68 | Borderline VfM |
1 | Dissatisfied with bus-station 5–15 min to bus stop | 14.3*** 2.68*** | Dissatisfied with quality of ride | 288.16 | 21.18 | Bad VfM |
2 | Willingness to pay more for seat Delayed by traffic congestion Weekend | 0.71** 0.75* 0.04*** | Very dissatisfied with level of fare | 632.49 | 164.80 | Bad VfM |
Rules | Antecedent | Consequent | Group | Support | Confidence | Interest | |
---|---|---|---|---|---|---|---|
1 | >5 times/week by bus, Weekday, No cars | ⟹ | First time by car | PS | 0.526 | 0.837 | 0.493 |
2 | Work-related commute, Employed full-time | ⟹ | >5 times/week by bus | PS | 0.389 | 0.702 | 0.215 |
3 | Residential apartment, 5–15 minto bus stop | ⟹ | >5 times/week by bus | PS | 0.380 | 0.705 | 0.115 |
4 | No driving license, Living near friends & family is important | ⟹ | 2–4 times/week by bus | PS | 0.206 | 0.724 | 0.076 |
1 | Cash ticket, No driving license, Pay seat, Buses are crowded | ⟹ | 1–3 times/month by bus | OMD | 0.319 | 0.681 | 0.295 |
2 | Male, No driving license, No delays by traffic congestion | ⟹ | 1–3 times/month by bus | OMD | 0.291 | 0.662 | 0.264 |
3 | Work commute, Employed full-time, Weekday | ⟹ | 1–3 times/month by car | OMD | 0.198 | 0.850 | 0.160 |
4 | Male, Employed full-time, 5–15 minto bus stop, Weekday | ⟹ | Less often by car | OMD | 0.239 | 0.633 | 0.113 |
1 | Employed full-time, Buses are crowded, Weekday | ⟹ | Once a week by car | FrCT | 0.441 | 0.857 | 0.422 |
2 | 25–34 years old, Weekday, Employed full-time | ⟹ | Once a week by car | FrCT | 0.310 | 0.725 | 0.291 |
3 | Work commute, Employed full-time, Pay for seat | ⟹ | Once a week by car | FrCT | 0.296 | 0.791 | 0.282 |
4 | No delays by traffic congestion, Weekday | ⟹ | Once a week by car | FrCT | 0.235 | 0.884 | 0.213 |
5 | Male, Willing to pay more for seat | ⟹ | Less often by bus | FrCT | 0.251 | 0.826 | 0.201 |
1 | Cash ticket, Satisfied with level of fare, 5–15 minto bus stop | ⟹ | >5 times/week by car | EI | 0.221 | 0.830 | 0.214 |
1 | Very satisfied with journey time, Employed full-time | ⟹ | Very satisfied with frequency of buses | Good LoS | 0.467 | 0.756 | 0.406 |
2 | Very satisfied with network coverage, No cars | ⟹ | Very satisfied with frequency of buses | Good LoS | 0.432 | 0.835 | 0.376 |
3 | Very satisfied with journey time, Male | ⟹ | Very satisfied with network coverage | Good LoS | 0.417 | 0.883 | 0.357 |
4 | Very satisfied with quality of ride, Male | ⟹ | Very satisfied with network coverage | Good LoS | 0.394 | 0.854 | 0.329 |
5 | Satisfied with quality of ride, Male | ⟹ | Satisfied with frequency of buses | Good LoS | 0.411 | 0.829 | 0.217 |
6 | Male, 5–15 minto bus stop | ⟹ | Very satisfied with network coverage | Good LoS | 0.342 | 0.752 | 0.185 |
7 | Living near friends & family important, Bus travel is easy | ⟹ | Satisfied with network coverage | Good LoS | 0.352 | 0.773 | 0.158 |
8 | Male, Cash ticket, No delays by traffic congestion | ⟹ | Very satisfied with network coverage | Good LoS | 0.247 | 0.730 | 0.111 |
9 | Rent under 10,000 AED per annum | ⟹ | Very satisfied with frequency of buses | Good LoS | 0.206 | 0.628 | 0.094 |
1 | Employed full-time, Living near work important, No cars | ⟹ | Neutral on frequency of buses | Borderline LoS | 0.362 | 0.660 | 0.260 |
2 | No driving license, Employed full-time, No cars | ⟹ | Neutral on frequency of buses | Borderline LoS | 0.258 | 0.607 | 0.148 |
1 | Work commute, Male, Living near work important, Weekday | ⟹ | Very dissatisfied with frequency of buses | Bad LoS | 0.169 | 0.715 | 0.164 |
1 | >5 times/week by bus, Cash ticket, Employed full-time | ⟹ | Satisfied with level of fare | Good VfM | 0.518 | 0.937 | 0.354 |
2 | Very satisfied with quality of ride | ⟹ | Very satisfied with level of fare | Good VfM | 0.400 | 0.770 | 0.335 |
3 | Cash ticket, Employed full-time, Weekday | ⟹ | Very satisfied with level of fare | Good VfM | 0.249 | 0.799 | 0.165 |
4 | Satisfied with journey time, Male | ⟹ | Satisfied with quality of ride | Good VfM | 0.351 | 0.881 | 0.163 |
5 | Living near friends & family is important, No cars | ⟹ | Satisfied with quality of ride | Good VfM | 0.369 | 0.826 | 0.105 |
6 | Bus travel is easy, No cars | ⟹ | Very satisfied with quality of ride | Good VfM | 0.270 | 0.832 | 0.103 |
7 | South Asian, Weekend, Cash ticket | ⟹ | Satisfied with level of fare | Good VfM | 0.307 | 0.819 | 0.091 |
1 | No driving license, 5–15 minto bus stop, No cars | ⟹ | Neutral on quality of ride | Borderline VfM | 0.268 | 0.736 | 0.188 |
2 | Buses are crowded, Cash ticket | ⟹ | Neutral on level of fare | Borderline VfM | 0.278 | 0.742 | 0.159 |
1 | Cash ticket, Employed full-time, Weekend | ⟹ | Dissatisfied with level of fare | Bad VfM | 0.427 | 0.877 | 0.403 |
2 | Cash ticket, Dissatisfied with bus-station | ⟹ | Dissatisfied with quality of ride | Bad VfM | 0.266 | 0.922 | 0.262 |
3 | Cash ticket, Neutral on journey time, Weekend | ⟹ | Very dissatisfied with quality of ride | Bad VfM | 0.188 | 0.739 | 0.186 |
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Hasan, U.; Whyte, A.; Al Jassmi, H. Life-Cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-Mining Algorithm. Buildings 2019, 9, 1. https://doi.org/10.3390/buildings9010001
Hasan U, Whyte A, Al Jassmi H. Life-Cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-Mining Algorithm. Buildings. 2019; 9(1):1. https://doi.org/10.3390/buildings9010001
Chicago/Turabian StyleHasan, Umair, Andrew Whyte, and Hamad Al Jassmi. 2019. "Life-Cycle Asset Management in Residential Developments Building on Transport System Critical Attributes via a Data-Mining Algorithm" Buildings 9, no. 1: 1. https://doi.org/10.3390/buildings9010001