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Titlebook: Intelligent Computing Techniques for Smart Energy Systems; Proceedings of ICTSE Anshuman Tripathi,Amit Soni,Jagrati Sahariya Conference pro

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发表于 2025-3-21 18:14:31 | 显示全部楼层 |阅读模式
书目名称Intelligent Computing Techniques for Smart Energy Systems
副标题Proceedings of ICTSE
编辑Anshuman Tripathi,Amit Soni,Jagrati Sahariya
视频video
概述Presents research works in the field of intelligent computing techniques.Gathers the outcomes of the ICTSES 2021, held in Jaipur, India.Offers a reference guide for researchers and practitioners in ac
丛书名称Lecture Notes in Electrical Engineering
图书封面Titlebook: Intelligent Computing Techniques for Smart Energy Systems; Proceedings of ICTSE Anshuman Tripathi,Amit Soni,Jagrati Sahariya Conference pro
描述This book compiles the best selected research papers presented during the 2nd International Conference on Intelligent Computing Techniques for Smart Energy Systems (ICTSES 2021), held at Manipal University, Jaipur, Rajasthan, India. It presents the diligent work of the research community where intelligent computing techniques are applied in allied fields of engineering ranging from engineering materials to electrical engineering to electronics and communication engineering- to computer-related fields. The theoretical research concepts are supported with extensive reviews highlighting the trends in the possible and real-life applications of computational intelligence. The high-quality content with broad range of the topics is thoroughly peer-reviewed and published on suitable recommendations..
出版日期Conference proceedings 2022
关键词Smart Grid; Smart Innovations; Cyber Security and Power System Communication; Big Data Application in P
版次1
doihttps://doi.org/10.1007/978-981-19-0252-9
isbn_softcover978-981-19-0254-3
isbn_ebook978-981-19-0252-9Series ISSN 1876-1100 Series E-ISSN 1876-1119
issn_series 1876-1100
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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发表于 2025-3-21 23:44:40 | 显示全部楼层
Comparative Analysis of 10T SRAM Cell using Nanodevices,94 μW and 0.5001 μW. The CNTFET cell has 42%, 43%, and 41% improved values of HSNM, RSNM, and WSNM, respectively, from the FinFET cell. The FinFET schemes yield substantially lower leakage power compared to CMOS and CNTFET-based cells.
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发表于 2025-3-22 06:44:03 | 显示全部楼层
Conference proceedings 2022nergy Systems (ICTSES 2021), held at Manipal University, Jaipur, Rajasthan, India. It presents the diligent work of the research community where intelligent computing techniques are applied in allied fields of engineering ranging from engineering materials to electrical engineering to electronics an
发表于 2025-3-22 09:34:50 | 显示全部楼层
Microgrid Energy Management Strategy for Low Dynamics Load Applications Using Simulink,ithin the individual source limits. Simulation is carried out using MATLAB. Simulation results show that the developed energy management strategy is able to meet the instantaneous load demand in varying irradiance, wind speed, and load conditions keeping the battery state of charge and electrolyzer hydrogen pressure in allowable limits.
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发表于 2025-3-22 18:31:45 | 显示全部楼层
Dynamics Modeling and Motion Simulation of a Segway Robotic Transportation System,anged in state space model format. The SRTP is simulated using the derived state space model using MATLAB. The introduced modeling and simulation processes have shown their ability to produce and plot the motion of the Segway parts with monitoring the effect of the Segway physical parameters such as mass of cart.
发表于 2025-3-22 21:48:59 | 显示全部楼层
Conference proceedings 2022s in the possible and real-life applications of computational intelligence. The high-quality content with broad range of the topics is thoroughly peer-reviewed and published on suitable recommendations..
发表于 2025-3-23 03:39:28 | 显示全部楼层
Fault Analysis and Protection Scheme for DC Microgrid, the steady-state power flow conditions. This is followed by the EMTP to determine selected microgrid behavior during transient conditions and decide on protection schemes. A hardware-in-loop (HIL) environment is developed and discussed to verify the effectiveness of the protection scheme.
发表于 2025-3-23 07:22:35 | 显示全部楼层
Comparative Analysis of Machine Learning Techniques for Software Effort Estimation,orms the other models with better prediction accuracy, and it reduces the error rate for SVR_SG and GLR_SG by 58.4%, and 48.2% respectively. It can be concluded from the experimental results that the ANN_SG is best performer among the candidate models for SEE statistically.
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