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    Studies from Guangxi Power Grid Co. Ltd. in the Area of Machine Learning Published (An Advanced Accurate Intrusion Detection System for Smart Grid Cybersecurity Based on Evolving Machine Learning)


    June 16, 2022 - Daily Asia Business

     

      2022 JUN 15 (NewsRx) -- By a News Reporter-Staff News Editor at Daily Asia Business -- Fresh data on artificial intelligence are presented in a new report. According to news reporting from Nanning, People’s Republic of China, by NewsRx journalists, research stated, “Smart grids, the next generation of electricity systems, would be intelligent and self-aware of physical and cyber activity in the control area.”

      The news reporters obtained a quote from the research from Guangxi Power Grid Co. Ltd.: “As a cyber-embedded infrastructure, it must be capable of detecting cyberattacks and responding appropriately in a timely and effective manner. This article tries to introduce an advanced and unique intrusion detection model capable of classifying binary-class, trinary-class, and multiple-class CDs and electrical network incidents for smart grids. It makes use of the gray wolf algorithm (GWA) for evolving training of artificial neural networks (ANNs) as a successful machine learning model for intrusion detection. In this way, the intrusion detection model’s weight vectors are initialized and adjusted using the GWA in order to reach the smallest mean square error possible. With the suggested evolving machine learning model, the issues of cyberattacks, failure forecast, and failure diagnosing would be addressed in the smart grid energy sector properly. Using a real dataset from the Mississippi State Laboratory in the United States, the proposed model is illustrated and the experimental results are explained.”

      According to the news editors, the research concluded: “The proposed model is compared to some of the most widely used classifiers in the area. The results show that the suggested intrusion detection model outperforms other well-known models in this field.”

      For more information on this research see: An Advanced Accurate Intrusion Detection System for Smart Grid Cybersecurity Based on Evolving Machine Learning. Frontiers in Energy Research, 2022,10. (Frontiers in Energy Research - http://www.frontiersin.org/energy_research). The publisher for Frontiers in Energy Research is Frontiers Media S.A.

      A free version of this journal article is available at https://doi.org/10.3389/fenrg.2022.903370.

      Our news journalists report that more information may be obtained by contacting Tong Yu, Guangxi Power Grid Co. Ltd., Electric Power Research Institute, NanNing, People’s Republic of China. Additional authors for this research include Kai Da, Zhiwen Wang, Ying Ling, Xin Li, Dongmei Bin, Chunyan Yang.

      (Our reports deliver fact-based news of research and discoveries from around the world.)

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