A scientifically accurate assessment of tunnel health is the prerequisite for the safe maintenance and sustainability of the in-service road tunnel. The changing trend of tunnel health is not considered in existing research. Most evaluation indicator...
In order to accurately assess the fire risk of urban utility tunnels, an evaluation method based on the improved cloud model and evidence theory is proposed. Firstly, an evaluation index system for the fire risk of urban utility tunnels is constructe...
The safety risk evaluation of foundation pit excavations in metro stations involves multiple factors with randomness and fuzziness. This study improves the Second Improved CRITIC-Cloud Model for more precise risk assessment. The approach integrates c...
Compared with highway tunnels, hydraulic tunnel linings are in the water environment for a long time, and their lining materials and structures are more vulnerable to damage. Therefore, a comprehensive scientific durability evaluation of hydraulic tu...
This study proposes a water resource pollution risk warning evaluation method. Firstly, an evaluation system is constructed, consisting of 15 secondary indicators in four aspects: water quality, ecology, utilization protection, and water disasters. T...
The rational selection of subway station locations is an interdisciplinary problem encompassing architecture, transportation, and other fields. Few evaluation index systems and quantitative evaluation methods exist for choosing subway station locatio...
Due to the broad frequency domain and nonlinear characteristics of ferroresonance signals, traditional time–frequency analysis methods often face challenges such as misjudgment, difficulty in threshold setting, and noise interference when extra...
The essential factors of information-aware systems are heterogeneous multi-sensory devices. Because of the ambiguity and contradicting nature of multi-sensor data, a data-fusion method based on the cloud model and improved evidence theory is proposed...
The complex power system and trading environment in China has led to higher requirements for the efficient and stable operation of the electricity market. With the continuous advancement of power system reforms, regular evaluation of the operation of...
Clouds seriously limit the application of optical remote sensing images. In this paper, we remove clouds from satellite images using a novel method that considers ground surface reflections and cloud top reflections as a linear mixture of image eleme...
In the process of economic development, the exploitation and utilization of resources has played an important role, but the subsequent post-mining collapse and the shortage of land resources have affected future reconstruction to a certain extent. Cu...
Frequent water and mud inrush accidents during karst tunnel construction severely impact tunnel construction safety, environmental sustainability, and the long-term use of infrastructure. Therefore, conducting practical risk assessment for karst tunn...
In order to rapidly evaluate the working performance of an Electric Power Steering System (EPS) and clarify the key indicators that affect its working condition, targeted maintenance measures can be taken to improve the vehicle’s handling, stab...
In recent years, prefabricated buildings have developed rapidly in China. Compared with traditional buildings, prefabricated buildings require higher capabilities from partners in various aspects. However, due to the early stage of development of pre...
The water cycle around the globe is significantly impacted by the moisture in the soil. However, finding a quick and practical model to cope with the enormous amount of data is a difficult issue for remote sensing practitioners. The traditional metho...
In this study, Himawari-8 Advanced Himawari Imager (AHI) longwave channel data that is sensitive to clouds and absorption gas were used to improve the accuracy of the algorithm used to calculate outgoing longwave radiation (OLR) at the top of the atm...
Traditional evaluations of revetment projects primarily focus on structural safety and economic analysis, which cannot comprehensively reflect the overall effectiveness of such projects. To address this issue, this paper establishes a comprehensive e...
The development of new electric power system is a requirement for China to realize its “carbon peaking and carbon neutrality goals”, so it is of great importance that we assess the stability of a new electric power system under certain co...
Detecting and segmenting individual trees in forest ecosystems with high-density and overlapping crowns often results in bias due to the limitations of the commonly used canopy height model (CHM). To address such limitations, this paper proposes a ne...
In order to improve the fuzzy comprehensive evaluation model of mineral resource sustainability and enhance its scientific and objective nature, in this paper, a cloud model-based risk assessment method is introduced to determine the sustainability o...
The accurate determination of the annual lightning flash number to a wind turbine is essential for designing proper lightning protection measures. However, the method to assess the lightning risk of wind turbines recommended by the IEC is not associa...
Assessing the geological suitability of urban underground space development is crucial for mitigating geological risks. Traditional 2D evaluation methods fail to capture complex vertical variations in underground space, hindering precise planning. Th...
As global warming and environmental issues become increasingly prominent, steel enterprises, as a carbon-intensive industry, face urgent challenges in energy saving and emission reduction (ESER). This study develops a novel evaluation model integrati...
Rice growth monitoring is very important as rice is one of the staple crops of the world. Rice variables as quantitative indicators of rice growth are critical for farming management and yield estimation, and synthetic aperture radar (SAR) has great...
Recently, decreasing energy consumption under the premise of building comfort has become a popular topic, especially visual comfort. Existing research on visual comfort lacks a standard of how to select indicators. Moreover, studies on individual vis...
Optimizing mine fan operations in underground coal mines is important for ensuring proper ventilation, enhancing safety, and improving operational efficiency. A single main ventilation fan is insufficient to meet the ventilation demands of the entire...
Retrieving farmland soil water content with both high accuracy and physical interpretability remains a significant challenge, particularly for winter wheat. To bridge the gap between purely empirical data-driven approaches and mechanistic scattering...
Forest aboveground biomass (AGB) retrieval using synthetic aperture radar (SAR) backscatter has received extensive attention. The water cloud model (WCM), because of its simplicity and physical significance, has been one of the most commonly used mod...
Steam channeling significantly affects the production performance of cyclic steam stimulation (CSS) wells in offshore heavy oil reservoirs. However, there remains a lack of effective methods for evaluating the steam channeling severity between CSS we...
Existing risk assessment approaches for soft rock tunnels in fault-fractured zones typically employ single weighting schemes, inadequately integrate subjective and objective weights, and fail to define clear risk. This study proposes a risk-grading m...
Cloud computational service is one of the renowned services utilized by employees, employers, and organizations collaboratively. It is accountable for data management and processing through virtual machines and is independent of end users’ syst...
Predicting the shape evolution and movement of remote sensing satellite cloud images is a difficult task requiring the effective monitoring and rapid prediction of thunderstorms, gales, rainstorms, and other disastrous weather conditions. We proposed...
Ignoring real decision contexts in linguistic multi-criteria classification (MCC) causes unreasonable weights, rank reversal and unreliable classification. This paper develops a context-constrained MCC framework integrating case-based reasoning, grey...
In cloud manufacturing systems, the multi-granularity of service resource and design task models leads to the complexity of cloud service matching. In order to satisfy the preference of resource requesters for large-granularity service resources, we...
It will be a huge challenge for China to achieve carbon neutrality by 2060. At present, China needs to understand its own carbon neutrality status and then scientifically plan a path to achieve carbon neutrality. In order to evaluate the carbon neutr...
14 October 2022
The first step in the application of Landsat 9 imagery is cloud screening, and the International Satellite Cloud Climatology Project (ISCCP) has made cloud screening an important part of the World Climate Research Program. The accurate identification...
Reconstructing 3D point cloud models from image sequences tends to be impacted by illumination variations and textureless cases in images, resulting in missing parts or uneven distribution of retrieved points. To improve the reconstructing completene...
The water cloud model (WCM) is a widely used radar backscatter model applied to SAR images to retrieve soil moisture over vegetated areas. The WCM needs vegetation descriptors to account for the impact of vegetation on SAR backscatter. The commonly u...
Heritage Building Information Modelling (HBIM) requires the accurate classification of diverse building elements from 3D point clouds. This study presents a novel classification approach integrating a bespoke Uniclass-derived taxonomy with a hierarch...
Soil moisture effects limit radar-based aboveground biomass carbon (AGBC) prediction accuracy as well as lead to stripes between adjacent paths in regional mosaics due to varying soil moisture conditions on different acquisition dates. In this study,...
Machine learning (ML) in cloud architectures is used to manage powerful servers that run distributed systems over the internet. ML predicts the workload and traffic from cloud consumers and allocates resources according to the demand. ML in cloud arc...
Cloud and snow recognition technology is of great significance in the field of meteorology, and is also widely used in remote sensing mapping, aerospace, and other fields. Based on the traditional method of manually labeling cloud-snow areas, a metho...
Cloud detection is a key step in the preprocessing of optical satellite remote sensing images. In the existing literature, cloud detection methods are roughly divided into threshold methods and deep-learning methods. Most of the traditional threshold...
In animal husbandry applications, segmenting live pigs in complex farming environments faces many challenges, such as when pigs lick railings and defecate within the acquisition environment. The pig’s behavior makes point cloud segmentation mor...
The effect of geological modeling largely depends on the normal estimation results of geological sampling points. However, due to the sparse and uneven characteristics of geological sampling points, the results of normal estimation have great uncerta...
This study develops an objective deep-learning-based model for tropical cyclone (TC) intensity estimation. The model’s basic structure is a convolutional neural network (CNN), which is a widely used technology in computer vision tasks. In order...
Clouds critically influence Earth’s radiation balance and climate, making accurate cloud detection essential for improving climate models. This study develops the TSAR model to improve the cloud detection accuracy of the FY-4A CLM product by in...
Shadow cumulus clouds are widely distributed globally. They carry critical information to analyze environmental and climate changes. They can also shape the energy and water cycles of the global ecosystem at multiple scales by impacting solar radiati...
In the fields of meteorological simulation and computer graphics, precise simulation of clouds has been a recent research hotspot. The existing cloud modeling methods often ignore the differentiated characteristics of cloud layers at different height...
In precision livestock farming, 3D point clouds provide important data support for analyzing pig behavior and monitoring their health. However, due to environmental occlusions, limited sensor viewpoints, and mutual shielding between pigs, the acquire...
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