{"title":"粒子能量优化解的独特计算方法","authors":"N. Akhter, Laraib Asghar, Sobia Arbab, F. Batool","doi":"10.52700/jn.v2i2.37","DOIUrl":null,"url":null,"abstract":"The “Thomson problem’ is used to determine the minimum energy configuration of electrons on the sphere’ s surface. We turned this difficulty into an optimization problem, which we addressed with the help of intelligent computational techniques like Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO). To enhance the system’s global searching ability, a Quantum behaved Particle Swarm Optimization algorithm is designed. The Thomson’s problem is investigated and appraised, and has fewer parameters to govern, according to simulation data. In this work QPSO is extremely effective and successful at delivering near- optimal results, as we compared the results with Genetic Algorithm and PSO.","PeriodicalId":16381,"journal":{"name":"JOURNAL OF NANOSCOPE (JN)","volume":"162 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Distinctive Computational Approaches for Solution of Energy Optimization of Particles\",\"authors\":\"N. Akhter, Laraib Asghar, Sobia Arbab, F. Batool\",\"doi\":\"10.52700/jn.v2i2.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The “Thomson problem’ is used to determine the minimum energy configuration of electrons on the sphere’ s surface. We turned this difficulty into an optimization problem, which we addressed with the help of intelligent computational techniques like Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO). To enhance the system’s global searching ability, a Quantum behaved Particle Swarm Optimization algorithm is designed. The Thomson’s problem is investigated and appraised, and has fewer parameters to govern, according to simulation data. In this work QPSO is extremely effective and successful at delivering near- optimal results, as we compared the results with Genetic Algorithm and PSO.\",\"PeriodicalId\":16381,\"journal\":{\"name\":\"JOURNAL OF NANOSCOPE (JN)\",\"volume\":\"162 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JOURNAL OF NANOSCOPE (JN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52700/jn.v2i2.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL OF NANOSCOPE (JN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52700/jn.v2i2.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distinctive Computational Approaches for Solution of Energy Optimization of Particles
The “Thomson problem’ is used to determine the minimum energy configuration of electrons on the sphere’ s surface. We turned this difficulty into an optimization problem, which we addressed with the help of intelligent computational techniques like Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO). To enhance the system’s global searching ability, a Quantum behaved Particle Swarm Optimization algorithm is designed. The Thomson’s problem is investigated and appraised, and has fewer parameters to govern, according to simulation data. In this work QPSO is extremely effective and successful at delivering near- optimal results, as we compared the results with Genetic Algorithm and PSO.