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  • Open Access

    ARTICLE

    Safety-Constrained Multi-Agent Reinforcement Learning for Power Quality Control in Distributed Renewable Energy Networks

    Yongjiang Zhao, Haoyi Zhong, Chang Cyoon Lim*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 449-471, 2024, DOI:10.32604/cmc.2024.048771

    Abstract This paper examines the difficulties of managing distributed power systems, notably due to the increasing use of renewable energy sources, and focuses on voltage control challenges exacerbated by their variable nature in modern power grids. To tackle the unique challenges of voltage control in distributed renewable energy networks, researchers are increasingly turning towards multi-agent reinforcement learning (MARL). However, MARL raises safety concerns due to the unpredictability in agent actions during their exploration phase. This unpredictability can lead to unsafe control measures. To mitigate these safety concerns in MARL-based voltage control, our study introduces a novel approach: Safety-Constrained Multi-Agent Reinforcement Learning… More >

  • Open Access

    ARTICLE

    Adaptive Segmentation for Unconstrained Iris Recognition

    Mustafa AlRifaee1, Sally Almanasra2,*, Adnan Hnaif3, Ahmad Althunibat3, Mohammad Abdallah3, Thamer Alrawashdeh3

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1591-1609, 2024, DOI:10.32604/cmc.2023.043520

    Abstract In standard iris recognition systems, a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture, look-and-stare constraints, and a close distance requirement to the capture device. When these conditions are relaxed, the system’s performance significantly deteriorates due to segmentation and feature extraction problems. Herein, a novel segmentation algorithm is proposed to correctly detect the pupil and limbus boundaries of iris images captured in unconstrained environments. First, the algorithm scans the whole iris image in the Hue Saturation Value (HSV) color space for local maxima to detect the sclera region. The image… More >

  • Open Access

    REVIEW

    A Review of Lightweight Security and Privacy for Resource-Constrained IoT Devices

    Sunil Kumar1, Dilip Kumar1, Ramraj Dangi2, Gaurav Choudhary3, Nicola Dragoni4, Ilsun You5,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 31-63, 2024, DOI:10.32604/cmc.2023.047084

    Abstract The widespread and growing interest in the Internet of Things (IoT) may be attributed to its usefulness in many different fields. Physical settings are probed for data, which is then transferred via linked networks. There are several hurdles to overcome when putting IoT into practice, from managing server infrastructure to coordinating the use of tiny sensors. When it comes to deploying IoT, everyone agrees that security is the biggest issue. This is due to the fact that a large number of IoT devices exist in the physical world and that many of them have constrained resources such as electricity, memory,… More >

  • Open Access

    ARTICLE

    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

    Min Hu1,2,3, Zhimin Chen4, Yuan Xia4, Liping Zhang1,2,3,*, Qiuhua Tang1,2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2815-2840, 2023, DOI:10.32604/cmes.2023.027146

    Abstract The multi-skill resource-constrained project scheduling problem (MS-RCPSP) is a significant management science problem that extends from the resource-constrained project scheduling problem (RCPSP) and is integrated with a real project and production environment. To solve MS-RCPSP, it is an efficient method to use dispatching rules combined with a parallel scheduling mechanism to generate a scheduling scheme. This paper proposes an improved gene expression programming (IGEP) approach to explore newly dispatching rules that can broadly solve MS-RCPSP. A new backward traversal decoding mechanism, and several neighborhood operators are applied in IGEP. The backward traversal decoding mechanism dramatically reduces the space complexity in… More > Graphic Abstract

    Rules Mining-Based Gene Expression Programming for the Multi-Skill Resource Constrained Project Scheduling Problem

  • Open Access

    ARTICLE

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

    Wenchao Yi, Zhilei Lin, Yong Chen, Zhi Pei*, Jiansha Lu

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2841-2860, 2023, DOI:10.32604/cmes.2023.027055

    Abstract Effective constrained optimization algorithms have been proposed for engineering problems recently. It is common to consider constraint violation and optimization algorithm as two separate parts. In this study, a pbest selection mechanism is proposed to integrate the current mutation strategy in constrained optimization problems. Based on the improved pbest selection method, an adaptive differential evolution approach is proposed, which helps the population jump out of the infeasible region. If all the individuals are infeasible, the top 5% of infeasible individuals are selected. In addition, a modified truncated ε-level method is proposed to avoid trapping in infeasible regions. The proposed adaptive… More > Graphic Abstract

    An Enhanced Adaptive Differential Evolution Approach for Constrained Optimization Problems

  • Open Access

    ARTICLE

    Optimal Configuration Method for the Installed Capacity of the Solar-Thermal Power Stations

    Yan Wang1, Zhicheng Ma2, Jinping Zhang2, Qiang Zhou2, Ruiping Zhang1, Haiying Dong1,*

    Energy Engineering, Vol.120, No.4, pp. 949-963, 2023, DOI:10.32604/ee.2023.025668

    Abstract Because of the randomness of wind power and photovoltaic (PV) output of new energy bases, the problem of peak regulation capability and voltage stability of ultra-high voltage direct current (UHVDC) transmission lines, we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work. Firstly, we established the uncertainty model of wind power and PV based on the chance constrained planning theory. Then we used the K-medoids clustering method to cluster the scenarios considering the actual operation scenarios throughout the year. Secondly, we established the optimal configuration model based on… More >

  • Open Access

    ARTICLE

    A Machine Learning Approach for Artifact Removal from Brain Signal

    Sandhyalati Behera, Mihir Narayan Mohanty*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1455-1467, 2023, DOI:10.32604/csse.2023.029649

    Abstract Electroencephalography (EEG), helps to analyze the neuronal activity of a human brain in the form of electrical signals with high temporal resolution in the millisecond range. To extract clean clinical information from EEG signals, it is essential to remove unwanted artifacts that are due to different causes including at the time of acquisition. In this piece of work, the authors considered the EEG signal contaminated with Electrocardiogram (ECG) artifacts that occurs mostly in cardiac patients. The clean EEG is taken from the openly available Mendeley database whereas the ECG signal is collected from the Physionet database to create artifacts in… More >

  • Open Access

    ARTICLE

    Underconstrained Cable-Driven Parallel Suspension System of Virtual Flight Test Model in Wind Tunnel

    Huisong Wu, Kaichun Zeng, Li Yu, Yan Li, Xiping Kou*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 395-416, 2023, DOI:10.32604/cmes.2022.021650

    Abstract An underconstrained cable-driven parallel robot (CDPR) suspension system was designed for a virtual flight testing (VFT) model. This mechanism includes two identical upper and lower kinematic chains, each of which comprises a cylindrical pair, rotating pair, and cable parallelogram. The model is pulled via two cables at the top and bottom and fixed by a yaw turntable, which can realize free coupling and decoupling with three rotational degrees of freedom of the model. First, the underconstrained CDPR suspension system of the VFT model was designed according to the mechanics theory, the degrees of freedom were verified, and the support platform… More >

  • Open Access

    ARTICLE

    Modified Differential Evolution Algorithm for Solving Dynamic Optimization with Existence of Infeasible Environments

    Mohamed A. Meselhi*, Saber M. Elsayed, Daryl L. Essam, Ruhul A. Sarker

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1-17, 2023, DOI:10.32604/cmc.2023.027448

    Abstract Dynamic constrained optimization is a challenging research topic in which the objective function and/or constraints change over time. In such problems, it is commonly assumed that all problem instances are feasible. In reality some instances can be infeasible due to various practical issues, such as a sudden change in resource requirements or a big change in the availability of resources. Decision-makers have to determine whether a particular instance is feasible or not, as infeasible instances cannot be solved as there are no solutions to implement. In this case, locating the nearest feasible solution would be valuable information for the decision-makers.… More >

  • Open Access

    ARTICLE

    Optimization of Multi-Execution Modes and Multi-Resource-Constrained Offshore Equipment Project Scheduling Based on a Hybrid Genetic Algorithm

    Qi Zhou1,2, Jinghua Li1,3, Ruipu Dong1,*, Qinghua Zhou3,*, Boxin Yang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1263-1281, 2023, DOI:10.32604/cmes.2022.020744

    Abstract Offshore engineering construction projects are large and complex, having the characteristics of multiple execution modes and multiple resource constraints. Their complex internal scheduling processes can be regarded as resourceconstrained project scheduling problems (RCPSPs). To solve RCPSP problems in offshore engineering construction more rapidly, a hybrid genetic algorithm was established. To solve the defects of genetic algorithms, which easily fall into the local optimal solution, a local search operation was added to a genetic algorithm to defend the offspring after crossover/mutation. Then, an elitist strategy and adaptive operators were adopted to protect the generated optimal solutions, reduce the computation time and… More >

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