{"title":"基于入侵杂草优化算法和灰狼优化算法的混合算法","authors":"W. Qasim, B. Mitras","doi":"10.5121/ijaia.2020.11103","DOIUrl":null,"url":null,"abstract":"In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm\n represents invasive weed optimization. This algorithm is a random numerical algorithm and the second\n algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm\n intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as\n the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds\n are a serious threat to cultivated plants because of their adaptability and are a threat to the overall\n planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm.\n The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to\n reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and\n taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new\n hybridization process between the previous algorithms GWO and IWO and we will symbolize the new\n algorithm IWOGWO.Comparing the suggested hybrid algorithm with the orig.","PeriodicalId":93188,"journal":{"name":"International journal of artificial intelligence & applications","volume":"11 1","pages":"31-44"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.5121/ijaia.2020.11103","citationCount":"0","resultStr":"{\"title\":\"A Hybrid Algorithm Based on Invasive Weed Optimization Algorithm and Grey Wolf Optimization Algorithm\",\"authors\":\"W. Qasim, B. Mitras\",\"doi\":\"10.5121/ijaia.2020.11103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm\\n represents invasive weed optimization. This algorithm is a random numerical algorithm and the second\\n algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm\\n intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as\\n the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds\\n are a serious threat to cultivated plants because of their adaptability and are a threat to the overall\\n planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm.\\n The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to\\n reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and\\n taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new\\n hybridization process between the previous algorithms GWO and IWO and we will symbolize the new\\n algorithm IWOGWO.Comparing the suggested hybrid algorithm with the orig.\",\"PeriodicalId\":93188,\"journal\":{\"name\":\"International journal of artificial intelligence & applications\",\"volume\":\"11 1\",\"pages\":\"31-44\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.5121/ijaia.2020.11103\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of artificial intelligence & applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5121/ijaia.2020.11103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of artificial intelligence & applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5121/ijaia.2020.11103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Hybrid Algorithm Based on Invasive Weed Optimization Algorithm and Grey Wolf Optimization Algorithm
In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm
represents invasive weed optimization. This algorithm is a random numerical algorithm and the second
algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm
intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as
the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds
are a serious threat to cultivated plants because of their adaptability and are a threat to the overall
planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm.
The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to
reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and
taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new
hybridization process between the previous algorithms GWO and IWO and we will symbolize the new
algorithm IWOGWO.Comparing the suggested hybrid algorithm with the orig.