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Application of chaotic ant swarm optimization in electric load forecasting

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  1. Ko, Chia-Nan & Lee, Cheng-Ming, 2013. "Short-term load forecasting using SVR (support vector regression)-based radial basis function neural network with dual extended Kalman filter," Energy, Elsevier, vol. 49(C), pages 413-422.
  2. Barman, Mayur & Dev Choudhury, Nalin Behari, 2019. "Season specific approach for short-term load forecasting based on hybrid FA-SVM and similarity concept," Energy, Elsevier, vol. 174(C), pages 886-896.
  3. Talaat, M. & Farahat, M.A. & Mansour, Noura & Hatata, A.Y., 2020. "Load forecasting based on grasshopper optimization and a multilayer feed-forward neural network using regressive approach," Energy, Elsevier, vol. 196(C).
  4. Chen, Shuixia & Wang, Jian-qiang & Zhang, Hong-yu, 2019. "A hybrid PSO-SVM model based on clustering algorithm for short-term atmospheric pollutant concentration forecasting," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 41-54.
  5. Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
  6. Suganthi, L. & Samuel, Anand A., 2012. "Energy models for demand forecasting—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1223-1240.
  7. Kelachukwu J. Iheanetu, 2022. "Solar Photovoltaic Power Forecasting: A Review," Sustainability, MDPI, vol. 14(24), pages 1-31, December.
  8. Kong, Xiangyu & Li, Chuang & Wang, Chengshan & Zhang, Yusen & Zhang, Jian, 2020. "Short-term electrical load forecasting based on error correction using dynamic mode decomposition," Applied Energy, Elsevier, vol. 261(C).
  9. Erik Heilmann & Janosch Henze & Heike Wetzel, 2021. "Machine learning in energy forecasts with an application to high frequency electricity consumption data," MAGKS Papers on Economics 202135, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
  10. Afshar, K. & Bigdeli, N., 2011. "Data analysis and short term load forecasting in Iran electricity market using singular spectral analysis (SSA)," Energy, Elsevier, vol. 36(5), pages 2620-2627.
  11. Wang, Jianzhou & Jia, Ruiling & Zhao, Weigang & Wu, Jie & Dong, Yao, 2012. "Application of the largest Lyapunov exponent and non-linear fractal extrapolation algorithm to short-term load forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 45(9), pages 1277-1287.
  12. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  13. Hong, Wei-Chiang, 2011. "Electric load forecasting by seasonal recurrent SVR (support vector regression) with chaotic artificial bee colony algorithm," Energy, Elsevier, vol. 36(9), pages 5568-5578.
  14. Zhineng Hu & Jing Ma & Liangwei Yang & Liming Yao & Meng Pang, 2019. "Monthly electricity demand forecasting using empirical mode decomposition-based state space model," Energy & Environment, , vol. 30(7), pages 1236-1254, November.
  15. Singh, Priyanka & Dwivedi, Pragya & Kant, Vibhor, 2019. "A hybrid method based on neural network and improved environmental adaptation method using Controlled Gaussian Mutation with real parameter for short-term load forecasting," Energy, Elsevier, vol. 174(C), pages 460-477.
  16. Barman, Mayur & Dev Choudhury, N.B. & Sutradhar, Suman, 2018. "A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India," Energy, Elsevier, vol. 145(C), pages 710-720.
  17. Min-Liang Huang, 2016. "Hybridization of Chaotic Quantum Particle Swarm Optimization with SVR in Electric Demand Forecasting," Energies, MDPI, vol. 9(6), pages 1-16, May.
  18. Zhang, Wen Yu & Hong, Wei-Chiang & Dong, Yucheng & Tsai, Gary & Sung, Jing-Tian & Fan, Guo-feng, 2012. "Application of SVR with chaotic GASA algorithm in cyclic electric load forecasting," Energy, Elsevier, vol. 45(1), pages 850-858.
  19. Lijia Han & Xiaohong Wang & Yin Yu & Duan Wang, 2024. "Power Load Forecast Based on CS-LSTM Neural Network," Mathematics, MDPI, vol. 12(9), pages 1-17, May.
  20. Cheng-Wen Lee & Bing-Yi Lin, 2016. "Application of Hybrid Quantum Tabu Search with Support Vector Regression (SVR) for Load Forecasting," Energies, MDPI, vol. 9(11), pages 1-16, October.
  21. Pascal da Costa & Wenhui Tian, 2015. "A Sectoral Prospective Analysis of CO2 Emissions in China, USA and France, 2010-2050," Working Papers hal-01026302, HAL.
  22. Zhou, Kaile & Fu, Chao & Yang, Shanlin, 2016. "Big data driven smart energy management: From big data to big insights," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 215-225.
  23. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
  24. Ma, Weiwu & Fang, Song & Liu, Gang & Zhou, Ruoyu, 2017. "Modeling of district load forecasting for distributed energy system," Applied Energy, Elsevier, vol. 204(C), pages 181-205.
  25. Niu Dongxiao & Ma Tiannan & Liu Bingyi, 2017. "Power load forecasting by wavelet least squares support vector machine with improved fruit fly optimization algorithm," Journal of Combinatorial Optimization, Springer, vol. 33(3), pages 1122-1143, April.
  26. Wei-Chiang Hong & Yucheng Dong & Chien-Yuan Lai & Li-Yueh Chen & Shih-Yung Wei, 2011. "SVR with Hybrid Chaotic Immune Algorithm for Seasonal Load Demand Forecasting," Energies, MDPI, vol. 4(6), pages 1-18, June.
  27. Das, Utpal Kumar & Tey, Kok Soon & Seyedmahmoudian, Mehdi & Mekhilef, Saad & Idris, Moh Yamani Idna & Van Deventer, Willem & Horan, Bend & Stojcevski, Alex, 2018. "Forecasting of photovoltaic power generation and model optimization: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 912-928.
  28. Sun, Shaolong & Qiao, Han & Wei, Yunjie & Wang, Shouyang, 2017. "A new dynamic integrated approach for wind speed forecasting," Applied Energy, Elsevier, vol. 197(C), pages 151-162.
  29. Guo-Feng Fan & Shan Qing & Hua Wang & Wei-Chiang Hong & Hong-Juan Li, 2013. "Support Vector Regression Model Based on Empirical Mode Decomposition and Auto Regression for Electric Load Forecasting," Energies, MDPI, vol. 6(4), pages 1-15, April.
  30. Ahmad, Tanveer & Huanxin, Chen & Zhang, Dongdong & Zhang, Hongcai, 2020. "Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions," Energy, Elsevier, vol. 198(C).
  31. R. J. Kuo & Y. S. Tseng & Zhen-Yao Chen, 2016. "Integration of fuzzy neural network and artificial immune system-based back-propagation neural network for sales forecasting using qualitative and quantitative data," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1191-1207, December.
  32. Sahraei, Mohammad Ali & Çodur, Merve Kayaci, 2022. "Prediction of transportation energy demand by novel hybrid meta-heuristic ANN," Energy, Elsevier, vol. 249(C).
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