Applying particle swarm optimization algorithm for tuning a neuro-fuzzy inference system for sensor monitoring |
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Authors: | MV Oliveira R Schirru |
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Affiliation: | 1. Divisão de Instrumentação e Confiabilidade Humana, Instituto de Engenharia Nuclear, CNEN, Rua Hélio de Almeida, 75 Caixa Postal 68550, Cidade Universitária, 21945-970 Rio de Janeiro, Brazil;2. Laboratório de Monitoração de Processos, Programa de Engenharia Nuclear, UFRJ, Av. Brigadeiro Tronpowski s/n, Caixa Postal 68509, Cidade Universitária, 21945-970 Rio de Janeiro, Brazil;1. Department of Mechanical Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan;2. Center for Measurement Standards, Industrial Technology Research Institute, Hsinchu 30011, Taiwan;1. School of Chemical and Petroleum Engineering, Shiraz University, Shiraz, Iran;2. Thermodynamics Research Unit, School of Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa;3. National Iranian Gas Company (NIGC), South Pars Gas Complex (SPGC), Asaluyeh, Iran;4. Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran;5. School of Chemical Engineering, Yeungnam University, Gyeungsan, Republic of Korea;6. Southern Cross University, School of Environment, Science and Engineering, Lismore, NSW 2480, Australia;1. Department of Agricultural Machinery Engineering, Faculty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran;2. Department of Food, Agricultural and Biological Engineering, The Ohio State University, Wooster, Ohio, United States;1. Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia;2. Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, 50603 Kuala Lumpur, Malaysia;3. Department of Electrical & Electronic Engineering, Federal University of Technology, PMB 65, Minna, Nigeria;4. University of Ni?, Faculty of Mechanical Engineering, Department for Mechatronics and Control, Aleksandra Medvedeva 14, 18000 Ni?, Serbia |
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Abstract: | A neuro-fuzzy inference system (ANFIS) tuned by particle swarm optimization (PSO) algorithm has been developed for monitoring the relevant sensor in a nuclear power plant (NPP) using the information of other sensors. The antecedent parameters of the ANFIS that estimates the relevant sensor signal are optimized by a PSO algorithm and consequent parameters use a least-squares algorithm. The proposed methodology to monitor sensor output signals was demonstrated through the estimation of the nuclear power value in a pressurized water reactor using as input to the ANFIS six other correlated signals. The obtained results are compared to two similar ANFIS using one gradient descendent (GD) and other genetic algorithm (GA), as antecedent parameters' training algorithm. |
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