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18th International Symposium on Advanced Intelligent Systems (ISIS2017)

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (15 April 2018) | Viewed by 15432

Special Issue Editors

Division of Electrical and Computer Engineering, Chonnam National University, Daehak-ro 50, Yeosu 59626, Republic of Korea
Interests: intelligent system; deep learning; chaotic dynamics; nonlinear control; energy prediction; fuzzy and neural network; robot control; digital twins and CPS (cyber–physical system)
Special Issues, Collections and Topics in MDPI journals
Department of Management and Information Systems Science, Nagaoka University of Technology, 1603-1, Kamitomioka-machi, Nagaoka, Niigata 940-2188, Japan
Interests: Uncertainty in AI; Rough Sets; Knowledge Discovery; Machine Learning

Special Issue Information

Dear Colleagues,

We are pleased to invite you to the 18th International Symposium on Advanced Intelligent Systems (ISIS2017) which will be held on October 11-14, 2017 at EXCO in Daegu, South Korea. The ISIS2017 will provide all the presenters and participants with a great opportunity to present the special issue on advanced intelligence systems, or intelligent system with power system and energy. We will select excellent papers among submitted papers to 18th International Symposium on Advanced Intelligent Systems (ISIS2017) and then we will recommend to guest editors. The Special Issue will be subject to a peer review procedure with the aim of rapid and wide dissemination of their contents.

For more information about the 18th International Symposium on Advanced Intelligent Systems (ISIS2017) please click on: www.isis2017.org

The special issue topics include, but are not limited to;

- Energy and power system, or Energy and power system with following as;

  • - Artificial Intelligence
  • - Fuzzy Logic and Reasoning
  • - Neural Networks
  • - Neuro-Fuzzy Systems
  • - Genetic/Evolutionary Algorithms
  • - Machine Learning
  • - Computational Intelligence
  • - Data Mining
  • - Big Data Analysis
  • - Learning and Adaptive Systems
  • - Multi-Agent Systems
  • - Information Fusion
  • - Cognitive Modeling
  • - Mathematical Models
  • - Intelligent Control and Robotics
  • - Vision and Sensors
  • - Fault Detection and Diagnosis

- Others

Prof. Youngchul Bae
Prof. Koichi Yamada
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

15 pages, 1026 KiB  
Article
A Robust Suboptimal Current Control of an Interlink Converter for a Hybrid AC/DC Microgrid
by Ismi Rosyiana Fitri, Jung-Su Kim and Hwachang Song
Energies 2018, 11(6), 1382; https://doi.org/10.3390/en11061382 - 29 May 2018
Cited by 13 | Viewed by 2943
Abstract
A hybrid AC/DC microgrid is established with the aim of exploiting numerous types of renewable energy to meet the needs of different loads. The microgrid is decomposed by AC DC sub-grids which are connected by an interlink converter (IC). To maintain the security [...] Read more.
A hybrid AC/DC microgrid is established with the aim of exploiting numerous types of renewable energy to meet the needs of different loads. The microgrid is decomposed by AC DC sub-grids which are connected by an interlink converter (IC). To maintain the security and reliability of the microgrid, an automatic controller for the interlink converter is needed. In this paper, we propose a Linear Matrix Inequalities (LMI)-based current control method for the interlink converter. As the main features here, the interlink converter permits bidirectional power exchange between both sub-grids when a power–demand imbalance occurs in one sub-grid regardless of the converter system parameters. Simulations with various filter parameters are performed using the Matlab/Simulink software to validate the effectiveness of the proposed controller. In comparison with the existing Linear Quadratic Regulator (LQR)-based current control, the proposed method is more robust against unknown system parameters and high load perturbation. Full article
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15 pages, 2949 KiB  
Article
Dynamic Programming-Based Vessel Speed Adjustment for Energy Saving and Emission Reduction
by Kwang-Il Kim and Keon Myung Lee
Energies 2018, 11(5), 1273; https://doi.org/10.3390/en11051273 - 16 May 2018
Cited by 18 | Viewed by 3259
Abstract
Maritime transportation is an economic form of mass transportation, but it is associated with significant energy consumption and pollutant emissions. External forces such as tidal currents, waves, and wind strongly influence the energy efficiency of ships. The effective management of external forces can [...] Read more.
Maritime transportation is an economic form of mass transportation, but it is associated with significant energy consumption and pollutant emissions. External forces such as tidal currents, waves, and wind strongly influence the energy efficiency of ships. The effective management of external forces can save energy and reduce emissions. This study presents a method to build an optimal speed adjustment plan for a ship to navigate a given route. The method takes a dynamic programming (DP)-based approach to finding such an optimal plan to utilize external forces. To estimate the speed changes caused by external forces, the proposed method uses the mapping information from a combined database of ship status, marine environmental conditions, and speed changes. For the efficient manipulation of externally forced speed-change information, we used MapReduce-based operations that can handle big data and support the easy retrieval of associated data in specific situations. To evaluate the applicability of the proposed method, we applied it to real navigation situations in the southwestern sea of the Korean Peninsula. In the simulation experiments, we used real automatic identification system data and marine environmental data. The proposed method built more efficient speed adjustment plans than the fixed-speed navigation in terms of energy savings and pollutant emission reduction. The results also showed that the speed adjustment exploits external forces in a beneficial manner. Full article
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19 pages, 5247 KiB  
Article
A Fault Isolation Method via Classification and Regression Tree-Based Variable Ranking for Drum-Type Steam Boiler in Thermal Power Plant
by Jungwon Yu, Jaeyel Jang, Jaeyeong Yoo, June Ho Park and Sungshin Kim
Energies 2018, 11(5), 1142; https://doi.org/10.3390/en11051142 - 03 May 2018
Cited by 8 | Viewed by 4305
Abstract
Accurate detection and isolation of possible faults are indispensable for operating complex industrial processes more safely, effectively, and economically. In this paper, we propose a fault isolation method for steam boilers in thermal power plants via classification and regression tree (CART)-based variable ranking. [...] Read more.
Accurate detection and isolation of possible faults are indispensable for operating complex industrial processes more safely, effectively, and economically. In this paper, we propose a fault isolation method for steam boilers in thermal power plants via classification and regression tree (CART)-based variable ranking. In the proposed method, binary classification trees are constructed by applying the CART algorithm to a training dataset which is composed of normal and faulty samples for classifier learning then, to perform faulty variable isolation, variable importance values for each input variable are extracted from the constructed trees. The importance values for non-faulty variables are not influenced by faulty variables, because the values are extracted from the trees with decision boundaries only in the original input space; the proposed method does not suffer from smearing effect. Furthermore, the proposed method, based on the nonparametric CART classifier, can be applicable to nonlinear processes. To confirm the effectiveness, the proposed and comparison methods are applied to two benchmark problems and 250 MW drum-type steam boiler. Experimental results show that the proposed method isolates faulty variables more clearly without the smearing effect than the comparison methods. Full article
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9 pages, 1635 KiB  
Article
Blood Volume Pulse Extraction for Non-Contact Heart Rate Measurement by Digital Camera Using Singular Value Decomposition and Burg Algorithm
by Iman Rahmansyah Tayibnapis, Yeon-Mo Yang and Ki Moo Lim
Energies 2018, 11(5), 1076; https://doi.org/10.3390/en11051076 - 27 Apr 2018
Cited by 6 | Viewed by 4336
Abstract
Conventional photoplesthymograph (PPG) measurements for heart rate (HR) determination require direct contact between the patient and the PPG device sensor. When using the conventional method, it is possible for users to suffer undesirable skin irritation, discomfort and soreness. Thus, the development of non-contact [...] Read more.
Conventional photoplesthymograph (PPG) measurements for heart rate (HR) determination require direct contact between the patient and the PPG device sensor. When using the conventional method, it is possible for users to suffer undesirable skin irritation, discomfort and soreness. Thus, the development of non-contact PPG has been investigated with various technologies and methods. One of the technologies that able to measure PPG in a non-contact way and at low cost is using digital cameras such as webcams. Various filters have been implemented to do non-contact PPG using digital cameras. This paper proposes a non-contact PPG filter system utilizing singular value decomposition (SVD) and Burg’s algorithm. The main role of SVD is for noise removal and as PPG signal extractor. As for the Burg algorithm, it was utilized for estimating the heart rate value from the filtered PPG signal. In this paper, we show and analyze an experiment for HR measurement using our method and a previous method that used independent component analysis (ICA). We compare and contrast both of them with HR measurements acquired by a commercial oximeter. The experiments were conducted at various distance between 30~110 cm and light intensities between 5~2000 lux. The estimated HR showed 2.25 bpm of mean error and 0.73 of Pearson correlation coefficient. The optimal distance between the mirror and user for HR measurement was 50 cm with medium light intensity, around 550 lux. Full article
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