{"title":"基于混合蝙蝠框架的高精度改进蓝鲸方法和局部搜索算法对图像融合算法的最优性","authors":"S. Dutta, A. Banerjee","doi":"10.36548/jscp.2020.4.001","DOIUrl":null,"url":null,"abstract":"Image fusion has gained huge popularity in the field of medical and satellite imaging for image analysis. The lack of usages of image fusion is due to a deficiency of suitable optimization techniques and dedicated hardware. In recent days WOA (whale optimization algorithm) is gaining popularity. Like another straightforward nature-inspired algorithm, WOA has some problems in its searching process. In this paper, we have tried to improve the WOA algorithm by modifying the WOA algorithm. This MWOA (modified whale optimization algorithm) algorithm is amalgamed with LSA (local search algorithm) and BA (bat algorithm). The LSA algorithm helps the system to be faster, and BA algorithm helps to increase the accuracy of the system. This optimization algorithm is checked using MATLAB R2018b. Simulated using ModelSim, and the synthesizing is done using Xilinx Vivado 18.2 synthesis tool. The outcome of the simulation result and the synthesis result outshine other metaheuristic optimization algorithms.","PeriodicalId":48202,"journal":{"name":"Journal of Social and Clinical Psychology","volume":"2 1","pages":"195-208"},"PeriodicalIF":1.0000,"publicationDate":"2020-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":"{\"title\":\"Highly Precise Modified Blue Whale Method Framed by Blending Bat and Local Search Algorithm for the Optimality of Image Fusion Algorithm\",\"authors\":\"S. Dutta, A. Banerjee\",\"doi\":\"10.36548/jscp.2020.4.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image fusion has gained huge popularity in the field of medical and satellite imaging for image analysis. The lack of usages of image fusion is due to a deficiency of suitable optimization techniques and dedicated hardware. In recent days WOA (whale optimization algorithm) is gaining popularity. Like another straightforward nature-inspired algorithm, WOA has some problems in its searching process. In this paper, we have tried to improve the WOA algorithm by modifying the WOA algorithm. This MWOA (modified whale optimization algorithm) algorithm is amalgamed with LSA (local search algorithm) and BA (bat algorithm). The LSA algorithm helps the system to be faster, and BA algorithm helps to increase the accuracy of the system. This optimization algorithm is checked using MATLAB R2018b. Simulated using ModelSim, and the synthesizing is done using Xilinx Vivado 18.2 synthesis tool. The outcome of the simulation result and the synthesis result outshine other metaheuristic optimization algorithms.\",\"PeriodicalId\":48202,\"journal\":{\"name\":\"Journal of Social and Clinical Psychology\",\"volume\":\"2 1\",\"pages\":\"195-208\"},\"PeriodicalIF\":1.0000,\"publicationDate\":\"2020-09-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"29\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Social and Clinical Psychology\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.36548/jscp.2020.4.001\",\"RegionNum\":4,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"PSYCHOLOGY, CLINICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Social and Clinical Psychology","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.36548/jscp.2020.4.001","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PSYCHOLOGY, CLINICAL","Score":null,"Total":0}
Highly Precise Modified Blue Whale Method Framed by Blending Bat and Local Search Algorithm for the Optimality of Image Fusion Algorithm
Image fusion has gained huge popularity in the field of medical and satellite imaging for image analysis. The lack of usages of image fusion is due to a deficiency of suitable optimization techniques and dedicated hardware. In recent days WOA (whale optimization algorithm) is gaining popularity. Like another straightforward nature-inspired algorithm, WOA has some problems in its searching process. In this paper, we have tried to improve the WOA algorithm by modifying the WOA algorithm. This MWOA (modified whale optimization algorithm) algorithm is amalgamed with LSA (local search algorithm) and BA (bat algorithm). The LSA algorithm helps the system to be faster, and BA algorithm helps to increase the accuracy of the system. This optimization algorithm is checked using MATLAB R2018b. Simulated using ModelSim, and the synthesizing is done using Xilinx Vivado 18.2 synthesis tool. The outcome of the simulation result and the synthesis result outshine other metaheuristic optimization algorithms.
期刊介绍:
This journal is devoted to the application of theory and research from social psychology toward the better understanding of human adaptation and adjustment, including both the alleviation of psychological problems and distress (e.g., psychopathology) and the enhancement of psychological well-being among the psychologically healthy. Topics of interest include (but are not limited to) traditionally defined psychopathology (e.g., depression), common emotional and behavioral problems in living (e.g., conflicts in close relationships), the enhancement of subjective well-being, and the processes of psychological change in everyday life (e.g., self-regulation) and professional settings (e.g., psychotherapy and counseling). Articles reporting the results of theory-driven empirical research are given priority, but theoretical articles, review articles, clinical case studies, and essays on professional issues are also welcome. Articles describing the development of new scales (personality or otherwise) or the revision of existing scales are not appropriate for this journal.