Titlebook: Soft Computing Applications in Modern Power and Energy Systems; Select Proceedings o Krishna Murari,Narayana Prasad Padhy,Sukumar Kamal Con

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书目名称Soft Computing Applications in Modern Power and Energy Systems影响因子(影响力)




书目名称Soft Computing Applications in Modern Power and Energy Systems影响因子(影响力)学科排名




书目名称Soft Computing Applications in Modern Power and Energy Systems网络公开度




书目名称Soft Computing Applications in Modern Power and Energy Systems网络公开度学科排名




书目名称Soft Computing Applications in Modern Power and Energy Systems被引频次




书目名称Soft Computing Applications in Modern Power and Energy Systems被引频次学科排名




书目名称Soft Computing Applications in Modern Power and Energy Systems年度引用




书目名称Soft Computing Applications in Modern Power and Energy Systems年度引用学科排名




书目名称Soft Computing Applications in Modern Power and Energy Systems读者反馈




书目名称Soft Computing Applications in Modern Power and Energy Systems读者反馈学科排名

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Krishna Murari,Narayana Prasad Padhy,Sukumar KamalPresents select proceedings of the Electric Power and Renewable Energy Conference 2022.Discusses findings in soft computing and its applications in the field of power system.Serves as a reference reso

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Conference proceedings 2023wer electronics-based equipment, biomedical engineering, and image processing. The readers would be benefitted from enhancing their knowledge and skills in the domain areas. This book also helps the readers in developing new and innovative ideas..

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Soft Computing Applications in Modern Power and Energy Systems978-981-19-8353-5Series ISSN 1876-1100 Series E-ISSN 1876-1119

Seminar

IoT-Based Kalman Filtering and Particle Swarm Optimization for Detecting Skin Lesion,time and modified Kalman filtering is used for classification. The proposed classifier is evaluated using the HAM10000 benchmark dataset, and standard metrics are utilized to assess the proposed classifier. It seems the suggested classifier outperforms the current classifier in terms of performance.

BULLY

Detection of Fault Disturbances in a DG Integrated Hybrid Power System Using HS-Transform and Wavelugh WT and HST, it is evaluated that WT is unable to identify the signal due to noise, whereas in HST the disturbances present in the signal in the corresponding instants is nicely captured and detected. This shows the robustness in HST under noisy conditions. It simplifies the complexity in identif

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Dorsal

Classification of Fault Disturbances in a DG Integrated Hybrid Power System Using Support Vector Mato categorize fault-related disturbances in a DG-infiltrated hybrid power system. To categorize the Line-Line fault and Line-Line-Ground fault, an unique technique based on SVM and DT is proposed. Based on these analyzes, it is observed that DT Gives the highest viable accuracy as compared to other