Enhancing Industrial Load Scheduling through Demand Side Management and Advanced Optimization Techniques Using Neuro-Fuzzy and Deep Learning Approaches-Reference-Cited by-同舟云学术

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Enhancing Industrial Load Scheduling through Demand Side Management and Advanced Optimization Techniques Using Neuro-Fuzzy and Deep Learning Approaches

Published:2023-11-03 Issue: Volume:356 Page:1107-1112
ISSN:
Container-title:2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)
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Author:

Agarwal Shivani¹,Sharma Ritu²,Tamilselvi M.³,Sharma Harsh Mohan⁴,Sahu Dinesh Prasad⁵,Singh Jagendra⁵

Affiliation:

1. Ajay Kumar Garg Engineering College,Department of Information Technology,Ghaziabad,India

2. Gyan Ganga Institute Of Technology and science,Dept. Of Electrical And Electronics Engineering,Jabalpur,India

3. Roever Engineering College Perambalur,Deartment of Computer Science And Engineering,Perambalur,India

4. Raj kumar Goel Institute of Technology,Department of Management,Ghaziabad,India

5. School of Computer Science Engineering and Technology, Bennett University,Greater Noida,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424970/10424704/10425357.pdf?arnumber=10425357

Reference13 articles.

1. An edge computing based anomaly detection method in IoT industrial sustainability

2. Malware Analysis in IoT & Android Systems with Defensive Mechanism

3. Change Detection in Remote Sensing Image Data Comparing Algebraic and Machine Learning Methods

4. IoT-Based Wireless Polysomnography Intelligent System for Sleep Monitoring

5. A Comprehensive Study of XSS Attack and the Digital Forensic Models to Gather the Evidence

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