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Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM Approaches

Computers, Materials & Continua 2021年第2期66卷 1479-1496页

作者： jalal sadoon hameed al-bayati Burak Berk Üstündağ jalal sadoon hameed al-bayati Istanbul Technical UniversityIstanbul34469Turkey Burak BerkÜstündağ Istanbul Technical UniversityIstanbul34469Turkey

The Fused Modified Grasshopper Optimization algorithm has been proposed,which selects the most specific feature sets from images of the disease of plant *** Proposed algorithm ensures the detection of diseases during the early stages of the diagnosis of leaf disease by farmers and,finally,the crop needed to be controlled by farmers to ensure the survival and protection of *** this study,a novel approach has been suggested based on the standard optimization algorithm for grasshopper and the selection of *** conditions in plants are a major factor in reducing crop yield and *** delay or errors in the diagnosis of the disease can lead to delays in the management of plant disease spreading and damage and related material *** new heuristic optimization of swarm intelligence,Grasshopper Optimization algorithm was inspired by grasshopper movements for their feeding *** simulates the attitude and social interaction of grasshopper swarm in terms of gravity and wind *** the decision on features extracted by an accelerated feature selection algorithm,popular approaches such as ANN and SVM classifiers had been *** the evaluation of the proposed model,different data sets of plant leaves were *** proposed model was successful in the diagnosis of the diseases of leaves the plant with an accuracy of 99.41 percent(average).The proposed biologically inspired model was sufficiently satisfied,and the best or most desirable characteristics were ***,the results of the research for these data sets were estimated by the proposed Fused Modified Grasshopper Optimization algorithm(FMGOA).The results of that experiment were demonstrated to allow classification models to reduce input features and thus to increase the precision with the presented Modified Grasshopper Optimization *** and analysis were performed to prove the model validity through model parameters such as precision,recall,f-

关键词： Fusion machine learning plant leaves diseases feature selection fused modified grasshopper algorithm

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