Brain tumor and brain stroke are two important causes of death in and around the world. The abnormalities in brain cell leads to brain stroke and obstruction in blood flow to brain cells leads to brain stroke. In this article, a computer aided automatic methodology is proposed to detect and segment ischemic stroke in brain MRI images using Adaptive Neuro Fuzzy Inference (ANFIS) classifier. The proposed method consists of preprocessing, feature extraction and classification. The brain image is enhanced using Heuristic histogram equalization technique. Then, texture and morphological features are extracted from the preprocessed image. These features are optimized using Genetic Algorithm and trained and classified using ANFIS classifier. The performance of the proposed ischemic stroke detection system is analyzed in terms of sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and Mathew's correlation coefficient.

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A proposed hybrid approaches are incorporated in Electric Vehicle (EV) fast charging station (FCS) using (RES). Hybrid approach is improved by Adaptive Hybrid Particle Swarm Optimization (AHPSO) named as AHWPSO, moreover the proposed work Grey Wolf Optimization (GWO) is assist with adaptive hybridize PSO algorithm. Therefore, an overall pricing cost should be reduced maximum Electric Vehicle Charging Station (EVCS) with minimal installation. This simulation work is verified an adaptive time varying weightage parameters to increase the AHWPSO particle diversity factor. Proposed algorithm is incorporated with improve the novelty, and compared the results are recent version of PSO used for EVCS. Its increase the charging ability, energy loss minimization, voltage deviation reduction, and cost minimization. A distribution micro-grid capacity and demand are tested. Similarly, low to peak period energy variations are controlled by proposed algorithm with reduced capacitor bank. Overall control algorithm code is executed buy MATLAB/Simulink platform, the performance of this work listed, and compare to the existing approaches with achievement of maximum efficiency.

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