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Search Results (18)
  • Open Access

    ARTICLE

    Blockchain-Based Power Transaction Method for Active Distribution Network

    Fei Zeng1, Zhinong Wei1, Haiteng Han1,*, Yang Chen2

    Energy Engineering, Vol.120, No.5, pp. 1067-1080, 2023, DOI:10.32604/ee.2023.022479

    Abstract A blockchain-based power transaction method is proposed for Active Distribution Network (ADN), considering the poor security and high cost of a centralized power trading system. Firstly, the decentralized blockchain structure of the ADN power transaction is built and the transaction information is kept in blocks. Secondly, considering the transaction needs between users and power suppliers in ADN, an energy request mechanism is proposed, and the optimization objective function is designed by integrating cost aware requests and storage aware requests. Finally, the particle swarm optimization algorithm is used for multi-objective optimal search to find the power More >

  • Open Access

    ARTICLE

    Multi-Objective Optimization with Artificial Neural Network Based Robust Paddy Yield Prediction Model

    S. Muthukumaran1,*, P. Geetha2, E. Ramaraj1

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 215-230, 2023, DOI:10.32604/iasc.2023.027449

    Abstract Agriculture plays a vital role in the food production process that occupies nearly one-third of the total surface of the earth. Rice is propagated from the seeds of paddy and it is a stable food almost used by fifty percent of the total world population. The extensive growth of the human population alarms us to ensure food security and the country should take proper food steps to improve the yield of food grains. This paper concentrates on improving the yield of paddy by predicting the factors that influence the growth of paddy with the help… More >

  • Open Access

    ARTICLE

    Optimal Energy Consumption Optimization in a Smart House by Considering Electric Vehicles and Demand Response via a Hybrid Gravitational Search and Particle Swarm Optimization Algorithm

    Rongxin Zhang1,*, Chengying Yang2,3, Xuetao Li1

    Energy Engineering, Vol.119, No.6, pp. 2489-2511, 2022, DOI:10.32604/ee.2022.021517

    Abstract Buildings are the main energy consumers across the world, especially in urban communities. Building smartization, or the smartification of housing, therefore, is a major step towards energy grid smartization too. By controlling the energy consumption of lighting, heating, and cooling systems, energy consumption can be optimized. All or some part of the energy consumed in future smart buildings must be supplied by renewable energy sources (RES), which mitigates environmental impacts and reduces peak demand for electrical energy. In this paper, a new optimization algorithm is applied to solve the optimal energy consumption problem by considering… More >

  • Open Access

    ARTICLE

    Bio-inspired Hybrid Feature Selection Model for Intrusion Detection

    Adel Hamdan Mohammad1,*, Tariq Alwada’n2, Omar Almomani3, Sami Smadi3, Nidhal ElOmari4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 133-150, 2022, DOI:10.32604/cmc.2022.027475

    Abstract Intrusion detection is a serious and complex problem. Undoubtedly due to a large number of attacks around the world, the concept of intrusion detection has become very important. This research proposes a multilayer bio-inspired feature selection model for intrusion detection using an optimized genetic algorithm. Furthermore, the proposed multilayer model consists of two layers (layers 1 and 2). At layer 1, three algorithms are used for the feature selection. The algorithms used are Particle Swarm Optimization (PSO), Grey Wolf Optimization (GWO), and Firefly Optimization Algorithm (FFA). At the end of layer 1, a priority value… More >

  • Open Access

    ARTICLE

    Optimizing the Multi-Objective Discrete Particle Swarm Optimization Algorithm by Deep Deterministic Policy Gradient Algorithm

    Sun Yang-Yang, Yao Jun-Ping*, Li Xiao-Jun, Fan Shou-Xiang, Wang Zi-Wei

    Journal on Artificial Intelligence, Vol.4, No.1, pp. 27-35, 2022, DOI:10.32604/jai.2022.027839

    Abstract Deep deterministic policy gradient (DDPG) has been proved to be effective in optimizing particle swarm optimization (PSO), but whether DDPG can optimize multi-objective discrete particle swarm optimization (MODPSO) remains to be determined. The present work aims to probe into this topic. Experiments showed that the DDPG can not only quickly improve the convergence speed of MODPSO, but also overcome the problem of local optimal solution that MODPSO may suffer. The research findings are of great significance for the theoretical research and application of MODPSO. More >

  • Open Access

    ARTICLE

    Milling Parameters Optimization of Al-Li Alloy Thin-Wall Workpieces Using Response Surface Methodology and Particle Swarm Optimization

    Haitao Yue1, Chenguang Guo1,*, Qiang Li1, Lijuan Zhao1, Guangbo Hao2

    CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.3, pp. 937-952, 2020, DOI:10.32604/cmes.2020.010565

    Abstract To improve the milling surface quality of the Al-Li alloy thin-wall workpieces and reduce the cutting energy consumption. Experimental research on the milling processing of AA2195 Al-Li alloy thin-wall workpieces based on Response Surface Methodology was carried out. The single factor and interaction of milling parameters on surface roughness and specific cutting energy were analyzed, and the multi-objective optimization model was constructed. The Multiobjective Particle Swarm Optimization algorithm introducing the Chaos Local Search algorithm and the adaptive inertial weight was applied to determine the optimal combination of milling parameters. It was observed that surface roughness… More >

  • Open Access

    ARTICLE

    A Novel Quantum-Behaved Particle Swarm Optimization Algorithm

    Tao Wu1, Lei Xie1, Xi Chen2, Amir Homayoon Ashrafzadeh3, Shu Zhang4, *

    CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 873-890, 2020, DOI:10.32604/cmc.2020.07478

    Abstract The efficient management of ambulance routing for emergency requests is vital to save lives when a disaster occurs. Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is a kind of metaheuristic algorithms applied to deal with the problem of scheduling. This paper analyzed the motion pattern of particles in a square potential well, given the position equation of the particles by solving the Schrödinger equation and proposed the Binary Correlation QPSO Algorithm Based on Square Potential Well (BCQSPSO). In this novel algorithm, the intrinsic cognitive link between particles’ experience information and group sharing information was created by More >

  • Open Access

    ARTICLE

    Analysis of OSA Syndrome from PPG Signal Using CART-PSO Classifier with Time Domain and Frequency Domain Features

    N. Kins Burk Sunil1, *, R. Ganesan2, B. Sankaragomathi3

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.2, pp. 351-375, 2019, DOI:10.31614/cmes.2018.04484

    Abstract Obstructive Sleep Apnea (OSA) is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen saturation. The aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea (SA) activity. In the proposed method, the time domain and frequency domain features of respiration signal obtained from the PPG device are extracted. These features are applied to the Classification and Regression Tree (CART)-Particle Swarm Optimization (PSO) classifier which classifies the More >

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