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  • Open Access

    ARTICLE

    Evolutionary Algorithms Applied to Estimation of Thermal Property by Inverse Problem

    V.C. Mariani1, V. J. Neckel2, L. S. Coelho3

    CMES-Computer Modeling in Engineering & Sciences, Vol.68, No.2, pp. 167-184, 2010, DOI:10.3970/cmes.2010.068.167

    Abstract In this study an inverse heat conduction problem using two optimization methods to estimate apparent thermal diffusivity at different drying temperatures is solved. Temperature and moisture versus time were obtained numerically using heat and mass transfer equations with drying temperatures in the range between 20°C to 70°C. The solution of the partial differential equation is made with a finite difference method coupled to optimization techniques of Differential Evolution (DE) and Particle Swarm Optimization (PSO) used in inverse problem. Statistical analysis shows no significant differences between reported and estimated curves, and no remarkable differences between results obtained using DE and PSO… More >

  • Open Access

    ARTICLE

    An Improved Unsupervised Image Segmentation Method Based on Multi-Objective Particle Swarm Optimization Clustering Algorithm

    Zhe Liu1,2,*, Bao Xiang1,3, Yuqing Song1, Hu Lu1, Qingfeng Liu1

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 451-461, 2019, DOI:10.32604/cmc.2019.04069

    Abstract Most image segmentation methods based on clustering algorithms use single-objective function to implement image segmentation. To avoid the defect, this paper proposes a new image segmentation method based on a multi-objective particle swarm optimization (PSO) clustering algorithm. This unsupervised algorithm not only offers a new similarity computing approach based on electromagnetic forces, but also obtains the proper number of clusters which is determined by scale-space theory. It is experimentally demonstrated that the applicability and effectiveness of the proposed multi-objective PSO clustering algorithm. More >

  • Open Access

    ARTICLE

    Research on Activated Carbon Supercapacitors Electrochemical Properties Based on Improved PSO-BP Neural Network

    Xiaoyi Liang1, Zhen Yang1,2, Xingsheng Gu3, Licheng Ling1

    CMC-Computers, Materials & Continua, Vol.13, No.2, pp. 135-152, 2009, DOI:10.3970/cmc.2009.013.135

    Abstract Supercapacitors, also called electrical double-layer capacitors (EDLCs), occupy a region between batteries and dielectric capacitors on the Ragone plot describing the relation between energy and power. BET specific surface area and specific capacitance are two important electrochemical property parameters for activated carbon EDLCs, which are usually tested by experimental method. However, it is misspent time to repeat lots of experiments for EDLCs' studies. In this investigation, we developed one theoretical model based on improved particle swarm optimization algorithm back propagation (PSO-BP) neural network (NN) to simulate and optimize BET specific surface area and specific capacitance. Comparative studies between the predicted… More >

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