Cat Swarm with Fuzzy Cognitive Maps for Automated Soil Classification

作     者：Ashit Kumar Dutta Yasser Albagory Manal Al Faraj Majed Alsanea Abdul Rahaman Wahab Sait 

作者机构：Department of Computer Science and Information SystemsCollege of Applied SciencesAlMaarefa UniversityAd DiriyahRiyadh13713Kingdom of Saudi Arabia Department of Computer EngineeringCollege of Computers and Information TechnologyTaif UniversityTaif21944Kingdom of Saudi Arabia Department of ComputingArabeast CollegesRiyadh11583Kingdom of Saudi Arabia Department of Archives and CommunicationKing Faisal UniversityAl AhsaHofuf31982Kingdom of Saudi Arabia 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2023年第44卷第2期

页      面：1419-1432页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 07[理学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 070101[理学-基础数学] 

基　　金：supported by the Researchers Supporting Program(TUMA-Project-2021-27) Almaarefa University,Riyadh,Saudi Arabia.Taif University Researchers Supporting Project Number(TURSP-2020/161) Taif University,Taif,Saudi Arabia 

主　　题：Soil classification intelligent models fuzzy cognitive maps cat swarm optimization fuzzy logic 

摘      要：Accurate soil prediction is a vital parameter involved to decide appro-priate crop,which is commonly carried out by the *** an auto-mated soil prediction tool helps to considerably improve the efficacy of the *** the same time,fuzzy logic(FL)approaches can be used for the design of predictive models,particularly,Fuzzy Cognitive Maps(FCMs)have involved the concept of uncertainty representation and cognitive *** other words,the FCM is an integration of the recurrent neural network(RNN)and FL involved in the knowledge engineering *** this aspect,this paper introduces effective fuzzy cognitive maps with cat swarm optimization for automated soil classifica-tion(FCMCSO-ASC)*** goal of the FCMCSO-ASC technique is to identify and categorize seven different types of *** accomplish this,the FCMCSO-ASC technique incorporates local diagonal extrema pattern(LDEP)as a feature extractor for producing a collection of feature *** addition,the FCMCSO model is applied for soil classification and the weight values of the FCM model are optimally adjusted by the use of CSO *** exam-ining the enhanced soil classification outcomes of the FCMCSO-ASC technique,a series of simulations were carried out on benchmark dataset and the experimen-tal outcomes reported the enhanced performance of the FCMCSO-ASC technique over the recent techniques with maximum accuracy of 96.84%.