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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書(shū)目名稱(chēng)Next Generation Systems and Networks影響因子(影響力)




書(shū)目名稱(chēng)Next Generation Systems and Networks影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Next Generation Systems and Networks網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Next Generation Systems and Networks網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Next Generation Systems and Networks被引頻次




書(shū)目名稱(chēng)Next Generation Systems and Networks被引頻次學(xué)科排名




書(shū)目名稱(chēng)Next Generation Systems and Networks年度引用




書(shū)目名稱(chēng)Next Generation Systems and Networks年度引用學(xué)科排名




書(shū)目名稱(chēng)Next Generation Systems and Networks讀者反饋




書(shū)目名稱(chēng)Next Generation Systems and Networks讀者反饋學(xué)科排名

Connotation

慢跑鞋

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

AWL

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

無(wú)情

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

現(xiàn)任者

CODA

CRUE

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

Motilin

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