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A Hybrid Approach for Energy Consumption Forecasting With a New Feature Engineering and Optimization Framework in Smart Grid

  • Published:2020 Issue: Volume:8 Page:96210-96226
  • ISSN:2169-3536
  • Container-title:IEEE Access
  • language:
  • Short-container-title:IEEE Access

Author:

Hafeez GhulamORCID,Alimgeer Khurram SaleemORCID,Qazi Abdul Baseer,Khan Imran,Usman MuhammadORCID,Khan Farrukh AslamORCID,Wadud ZahidORCID

Funder

Deanship of Scientific Research at King Saud University, Saudi Arabia, through the Research Group Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 28 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An Integrated Model of Deep Learning and Heuristic Algorithm for Load Forecasting in Smart Grid;Mathematics;2023-11-06

2. Optimized deep learning-based intrusion detection framework for vehicular network;Journal of Intelligent & Fuzzy Systems;2023-10-28

3. Attention-PVS for Domestic Hot Water Consumption Forecasting in Individual Household;IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society;2023-10-16

4. Data-driven models of crude distillation units for production planning and for operations monitoring;Computers & Chemical Engineering;2023-09

5. Comparative Analysis Between Feedforward Neural Network and CNN-LSTM Neural Network To Predict Household Electrical Energy Consumption;2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME);2023-07-19
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