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Titlebook: Next Generation Systems and Networks; Proceedings of BITS Hari Om Bansal,Pawan K. Ajmera,Chandra Shekhar Conference proceedings 2023 The E

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书目名称Next Generation Systems and Networks
副标题Proceedings of BITS
编辑Hari Om Bansal,Pawan K. Ajmera,Chandra Shekhar
视频video
概述Presents recent advances on next-generation systems and networks.Discusses the outcomes of BITS EEE CON 2022, held at BITS Pilani, India.Serves as a reference guide for researchers and practitioners i
丛书名称Lecture Notes in Networks and Systems
图书封面Titlebook: Next Generation Systems and Networks; Proceedings of BITS  Hari Om Bansal,Pawan K. Ajmera,Chandra Shekhar Conference proceedings 2023 The E
描述The book is a collection of high-quality research papers presented at International Conference on Next Generation Systems and Networks (BITS EEE CON 2022), held at Birla Institute of Technology & Science, Pilani, Rajasthan, India, during November 4–5, 2022. This book provides reliable and efficient design solutions for the next-generation networks and systems. The book covers research areas in energy, power and control; communication and signal processing; and electronics and nanotechnology.
出版日期Conference proceedings 2023
关键词5G/6G Communication; Intelligent Reflecting Surfaces; Smart Grid Communications; AI in Wireless Communi
版次1
doihttps://doi.org/10.1007/978-981-99-0483-9
isbn_softcover978-981-99-0482-2
isbn_ebook978-981-99-0483-9Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Nature-Inspired Optimization Algorithm-Assisted Optimal Sensor Node Positioning for Precision Agricsing nodes on the field. This is done by minimizing an innovatively designed cost function which is an indication of the un-scrutinized field area and overlapping coverage area of the sensor nodes. Five different nature-inspired optimization algorithms are applied in this paper for the said task, an
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Stock Price Prediction Using GRU and BiLSTM Models,d comparing the performances of both models to predict future stock prices. The experiments were carried out using a freely available dataset of stock market, which contained the stock prices of various companies. It was observed that the BiLSTM model performed better than the GRU model. However, GR
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Intelligent Cost Estimation Engine for EV Charging Stations: A Deep Learning-Based Approach,-driven and deep learning-based intelligent cost estimation engine proposed here will leverage the IOT connectivity for EV to forecast the load demand at charging station and efficient price estimation for EV charging. EV will provide details like battery state parameters and user historical data, e
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Sonar Signal Prediction Using Explainable AI for IoT Environment,ed to convert them into a glass box with the help of explainable AI. In this research, we have developed a model that can not only classify the sonar signals but also explain the predictions given by the model. These predictions can then be used for making business decisions and further help the dev
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