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Parallel System Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control
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作者 Tianyun Zhang Jun Zhang +4 位作者 Feiyue Wang Peidong Xu Tianlu Gao Haoran Zhang Ruiqi Si 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2024年第1期13-28,共16页
In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence evolution.However,there is,... In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence evolution.However,there is,currently,nearly no standard technical framework for objective and quantitative intelligence evaluation.In this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation theories.On this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment results.Experiment results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution. 展开更多
关键词 AI quantitative intelligence assessment and self-evolution automated reinforcement learning Bayesian optimization corrective control parallel system
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Using of artificial intelligence:Current and future applications in colorectal cancer screening
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作者 Georgios Zacharakis Abdulaziz Almasoud 《World Journal of Gastroenterology》 SCIE CAS 2022年第24期2778-2781,共4页
Significant developments in colorectal cancer screening are underway and include new screening guidelines that incorporate considerations for patients aged 45 years,with unique features and new techniques at the foref... Significant developments in colorectal cancer screening are underway and include new screening guidelines that incorporate considerations for patients aged 45 years,with unique features and new techniques at the forefront of screening.One of these new techniques is artificial intelligence which can increase adenoma detection rate and reduce the prevalence of colonic neoplasia. 展开更多
关键词 Basic concepts assessment of artificial intelligence in endoscopy Current applications ETHICS Safety challenge
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