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Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †

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Cited by:

  1. José M. Liceaga-Ortiz-De-La-Peña & Jorge A. Ruiz-Vanoye & Juan M. Xicoténcatl-Pérez & Ocotlán Díaz-Parra & Alejandro Fuentes-Penna & Ricardo A. Barrera-Cámara & Daniel Robles-Camarillo & Marco A. Márq, 2025. "Advancing Smart Energy: A Review for Algorithms Enhancing Power Grid Reliability and Efficiency Through Advanced Quality of Energy Services," Energies, MDPI, vol. 18(12), pages 1-33, June.
  2. Guixiang Xue & Yu Pan & Tao Lin & Jiancai Song & Chengying Qi & Zhipan Wang, 2019. "District Heating Load Prediction Algorithm Based on Feature Fusion LSTM Model," Energies, MDPI, vol. 12(11), pages 1-21, June.
  3. Azadeh Sadeghi & Roohollah Younes Sinaki & William A. Young & Gary R. Weckman, 2020. "An Intelligent Model to Predict Energy Performances of Residential Buildings Based on Deep Neural Networks," Energies, MDPI, vol. 13(3), pages 1-23, January.
  4. Abraham Kaligambe & Goro Fujita & Tagami Keisuke, 2022. "Estimation of Unmeasured Room Temperature, Relative Humidity, and CO 2 Concentrations for a Smart Building Using Machine Learning and Exploratory Data Analysis," Energies, MDPI, vol. 15(12), pages 1-12, June.
  5. Samer Chaaraoui & Matthias Bebber & Stefanie Meilinger & Silvan Rummeny & Thorsten Schneiders & Windmanagda Sawadogo & Harald Kunstmann, 2021. "Day-Ahead Electric Load Forecast for a Ghanaian Health Facility Using Different Algorithms," Energies, MDPI, vol. 14(2), pages 1-22, January.
  6. Ng, Rong Wang & Begam, Kasim Mumtaj & Rajkumar, Rajprasad Kumar & Wong, Yee Wan & Chong, Lee Wai, 2021. "An improved self-organizing incremental neural network model for short-term time-series load prediction," Applied Energy, Elsevier, vol. 292(C).
  7. Su Diao & Yajie Wan & Danyi Huang & Shijia Huang & Touseef Sadiq & Mohammad Shahbaz Khan & Lal Hussain & Badr S Alkahtani & Tehseen Mazhar, 2025. "Optimizing Bi-LSTM networks for improved lung cancer detection accuracy," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-24, February.
  8. Alexandru Pîrjan & George Căruțașu & Dana-Mihaela Petroșanu, 2018. "Designing, Developing, and Implementing a Forecasting Method for the Produced and Consumed Electricity in the Case of Small Wind Farms Situated on Quite Complex Hilly Terrain," Energies, MDPI, vol. 11(10), pages 1-42, October.
  9. Mehmet Türker Takcı & Tuba Gözel, 2022. "Effects of Predictors on Power Consumption Estimation for IT Rack in a Data Center: An Experimental Analysis," Sustainability, MDPI, vol. 14(21), pages 1-19, November.
  10. Liu, Jinyuan & Wang, Shouxi & Wei, Nan & Qiao, Weibiao & Li, Ze & Zeng, Fanhua, 2023. "A clustering-based feature enhancement method for short-term natural gas consumption forecasting," Energy, Elsevier, vol. 278(PB).
  11. Suriyan Jomthanachai & Wai Peng Wong & Khai Wah Khaw, 2024. "An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 741-792, February.
  12. Gülsah Erdogan & Wiem Fekih Hassen, 2023. "Charging Scheduling of Hybrid Energy Storage Systems for EV Charging Stations," Energies, MDPI, vol. 16(18), pages 1-29, September.
  13. Chengyue Huang & Yahe Yang, 2024. "Time Series Feature Redundancy Paradox: An Empirical Study Based on Mortgage Default Prediction," Papers 2501.00034, arXiv.org.
  14. Benjiang Ma & Qing Tang & Yifang Qin & Muhammad Farhan Bashir, 2021. "Policyholder cluster divergence based differential premium in diabetes insurance," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(7), pages 1793-1807, October.
  15. Arash Moradzadeh & Sahar Zakeri & Maryam Shoaran & Behnam Mohammadi-Ivatloo & Fazel Mohammadi, 2020. "Short-Term Load Forecasting of Microgrid via Hybrid Support Vector Regression and Long Short-Term Memory Algorithms," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
  16. Yan, Wan-Lin, 2023. "Stock index futures price prediction using feature selection and deep learning," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
  17. Junhwa Hwang & Dongjun Suh & Marc-Oliver Otto, 2020. "Forecasting Electricity Consumption in Commercial Buildings Using a Machine Learning Approach," Energies, MDPI, vol. 13(22), pages 1-29, November.
  18. Andreea Valeria Vesa & Tudor Cioara & Ionut Anghel & Marcel Antal & Claudia Pop & Bogdan Iancu & Ioan Salomie & Vasile Teodor Dadarlat, 2020. "Energy Flexibility Prediction for Data Center Engagement in Demand Response Programs," Sustainability, MDPI, vol. 12(4), pages 1-23, February.
  19. Salah Bouktif & Ali Fiaz & Ali Ouni & Mohamed Adel Serhani, 2020. "Multi-Sequence LSTM-RNN Deep Learning and Metaheuristics for Electric Load Forecasting," Energies, MDPI, vol. 13(2), pages 1-21, January.
  20. Fatma Yaprakdal, 2022. "An Ensemble Deep-Learning-Based Model for Hour-Ahead Load Forecasting with a Feature Selection Approach: A Comparative Study with State-of-the-Art Methods," Energies, MDPI, vol. 16(1), pages 1-13, December.
  21. Hadjout, D. & Torres, J.F. & Troncoso, A. & Sebaa, A. & Martínez-Álvarez, F., 2022. "Electricity consumption forecasting based on ensemble deep learning with application to the Algerian market," Energy, Elsevier, vol. 243(C).
  22. Mst. Shapna Akter & Hossain Shahriar & Reaz Chowdhury & M. R. C. Mahdy, 2022. "Forecasting the Risk Factor of Frontier Markets: A Novel Stacking Ensemble of Neural Network Approach," Future Internet, MDPI, vol. 14(9), pages 1-23, August.
  23. Zaki Masood & Rahma Gantassi & Ardiansyah & Yonghoon Choi, 2022. "A Multi-Step Time-Series Clustering-Based Seq2Seq LSTM Learning for a Single Household Electricity Load Forecasting," Energies, MDPI, vol. 15(7), pages 1-11, April.
  24. Miseta, Tamás & Fodor, Attila & Vathy-Fogarassy, Ágnes, 2022. "Energy trading strategy for storage-based renewable power plants," Energy, Elsevier, vol. 250(C).
  25. Fanidhar Dewangan & Almoataz Y. Abdelaziz & Monalisa Biswal, 2023. "Load Forecasting Models in Smart Grid Using Smart Meter Information: A Review," Energies, MDPI, vol. 16(3), pages 1-55, January.
  26. Gergo Barta & Benedek Pasztor & Venkat Prava, 2021. "Optimized Charge Controller Schedule in Hybrid Solar-Battery Farms for Peak Load Reduction," Energies, MDPI, vol. 14(22), pages 1-18, November.
  27. Meng, Qinglong & Wei, Ying'an & Fan, Jingjing & Li, Yanbo & Zhao, Fan & Lei, Yu & Sun, Hang & Jiang, Le & Yu, Lingli, 2024. "Peak regulation strategies for ground source heat pump demand response of based on load forecasting: A case study of rural building in China," Renewable Energy, Elsevier, vol. 224(C).
  28. Kang-Min Koo & Kuk-Heon Han & Kyung-Soo Jun & Gyumin Lee & Jung-Sik Kim & Kyung-Taek Yum, 2021. "Performance Assessment for Short-Term Water Demand Forecasting Models on Distinctive Water Uses in Korea," Sustainability, MDPI, vol. 13(11), pages 1-18, May.
  29. You-Da Jhong & Chang-Shian Chen & Bing-Chen Jhong & Cheng-Han Tsai & Song-Yue Yang, 2024. "Optimization of LSTM Parameters for Flash Flood Forecasting Using Genetic Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(3), pages 1141-1164, February.
  30. Hofmeister, Markus & Mosbach, Sebastian & Hammacher, Jörg & Blum, Martin & Röhrig, Gerd & Dörr, Christoph & Flegel, Volker & Bhave, Amit & Kraft, Markus, 2022. "Resource-optimised generation dispatch strategy for district heating systems using dynamic hierarchical optimisation," Applied Energy, Elsevier, vol. 305(C).
  31. Xiaoyu Liu & Jiangfeng Song & Hai Tao & Peng Wang & Haihua Mo & Wenjie Du, 2025. "Quarter-Hourly Power Load Forecasting Based on a Hybrid CNN-BiLSTM-Attention Model with CEEMDAN, K-Means, and VMD," Energies, MDPI, vol. 18(11), pages 1-29, May.
  32. Yiang Wang & Chong Luo & Wenqi Zhang & Xiangtian Meng & Qiong Liu & Xinle Zhang & Huanjun Liu, 2022. "Remote Sensing Prediction Model of Cultivated Land Soil Organic Matter Considering the Best Time Window," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
  33. Sana Mujeeb & Nadeem Javaid & Manzoor Ilahi & Zahid Wadud & Farruh Ishmanov & Muhammad Khalil Afzal, 2019. "Deep Long Short-Term Memory: A New Price and Load Forecasting Scheme for Big Data in Smart Cities," Sustainability, MDPI, vol. 11(4), pages 1-29, February.
  34. Hossein Hassani & Mohammad Reza Yeganegi & Xu Huang, 2021. "Fusing Nature with Computational Science for Optimal Signal Extraction," Stats, MDPI, vol. 4(1), pages 1-15, January.
  35. Rafael Sánchez-Durán & Joaquín Luque & Julio Barbancho, 2019. "Long-Term Demand Forecasting in a Scenario of Energy Transition," Energies, MDPI, vol. 12(16), pages 1-23, August.
  36. Monika Zimmermann & Florian Ziel, 2024. "Efficient mid-term forecasting of hourly electricity load using generalized additive models," Papers 2405.17070, arXiv.org, revised Feb 2025.
  37. Dana-Mihaela Petroșanu & Alexandru Pîrjan, 2020. "Electricity Consumption Forecasting Based on a Bidirectional Long-Short-Term Memory Artificial Neural Network," Sustainability, MDPI, vol. 13(1), pages 1-31, December.
  38. Fekri, Mohammad Navid & Patel, Harsh & Grolinger, Katarina & Sharma, Vinay, 2021. "Deep learning for load forecasting with smart meter data: Online Adaptive Recurrent Neural Network," Applied Energy, Elsevier, vol. 282(PA).
  39. Salam, Abdulwahed & El Hibaoui, Abdelaaziz, 2021. "Energy consumption prediction model with deep inception residual network inspiration and LSTM," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 97-109.
  40. Morais, Lucas Barros Scianni & Aquila, Giancarlo & de Faria, Victor Augusto Durães & Lima, Luana Medeiros Marangon & Lima, José Wanderley Marangon & de Queiroz, Anderson Rodrigo, 2023. "Short-term load forecasting using neural networks and global climate models: An application to a large-scale electrical power system," Applied Energy, Elsevier, vol. 348(C).
  41. Nikita Dmitrievich Senchilo & Denis Anatolievich Ustinov, 2021. "Method for Determining the Optimal Capacity of Energy Storage Systems with a Long-Term Forecast of Power Consumption," Energies, MDPI, vol. 14(21), pages 1-25, October.
  42. Seon Hyeog Kim & Gyul Lee & Gu-Young Kwon & Do-In Kim & Yong-June Shin, 2018. "Deep Learning Based on Multi-Decomposition for Short-Term Load Forecasting," Energies, MDPI, vol. 11(12), pages 1-17, December.
  43. Pinheiro, Marco G. & Madeira, Sara C. & Francisco, Alexandre P., 2023. "Short-term electricity load forecasting—A systematic approach from system level to secondary substations," Applied Energy, Elsevier, vol. 332(C).
  44. Alfonso P. Ramallo-González & Aurora González-Vidal & Fernando Terroso-Saenz & Antonio F. Skarmeta-Gómez, 2022. "A Novel Learning Algorithm Based on Bayesian Statistics: Modelling Thermostat Adjustments for Heating and Cooling in Buildings," Mathematics, MDPI, vol. 10(14), pages 1-13, July.
  45. Jin Sol Hwang & Jung-Su Kim & Hwachang Song, 2022. "Handling Load Uncertainty during On-Peak Time via Dual ESS and LSTM with Load Data Augmentation," Energies, MDPI, vol. 15(9), pages 1-20, April.
  46. Chi Hua & Erxi Zhu & Liang Kuang & Dechang Pi, 2019. "Short-term power prediction of photovoltaic power station based on long short-term memory-back-propagation," International Journal of Distributed Sensor Networks, , vol. 15(10), pages 15501477198, October.
  47. Musaed Alhussein & Syed Irtaza Haider & Khursheed Aurangzeb, 2019. "Microgrid-Level Energy Management Approach Based on Short-Term Forecasting of Wind Speed and Solar Irradiance," Energies, MDPI, vol. 12(8), pages 1-27, April.
  48. Wang, Yijun & Andreeva, Galina & Martin-Barragan, Belen, 2023. "Machine learning approaches to forecasting cryptocurrency volatility: Considering internal and external determinants," International Review of Financial Analysis, Elsevier, vol. 90(C).
  49. Renxi Gong & Xianglong Li, 2023. "A Short-Term Load Forecasting Model Based on Crisscross Grey Wolf Optimizer and Dual-Stage Attention Mechanism," Energies, MDPI, vol. 16(6), pages 1-24, March.
  50. Kamil Misiurek & Tadeusz Olkuski & Janusz Zyśk, 2025. "Review of Methods and Models for Forecasting Electricity Consumption," Energies, MDPI, vol. 18(15), pages 1-27, July.
  51. Jun-Hyeok Kim & Byung-Sung Lee & Chul-Hwan Kim, 2020. "A Study on the Development of Machine-Learning Based Load Transfer Detection Algorithm for Distribution Planning," Energies, MDPI, vol. 13(17), pages 1-12, August.
  52. Tan, Quanwei & Cao, Chunhua & Xue, Guijun & Xie, Wenju, 2024. "Short-term heating load forecasting model based on SVMD and improved informer," Energy, Elsevier, vol. 312(C).
  53. Han Qiu & Rong Hu & Jiaqing Chen & Zihao Yuan, 2025. "Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Network–Bidirectional Lon," Mathematics, MDPI, vol. 13(5), pages 1-32, February.
  54. Donghun Lee & Seok Mann Yoon & Jaeseung Lee & Kwanho Kim & Sang Hwa Song, 2020. "Applying Deep Learning to the Heat Production Planning Problem in a District Heating System," Energies, MDPI, vol. 13(24), pages 1-17, December.
  55. Kostadin Yotov & Emil Hadzhikolev & Stanka Hadzhikoleva & Stoyan Cheresharov, 2022. "Neuro-Cybernetic System for Forecasting Electricity Consumption in the Bulgarian National Power System," Sustainability, MDPI, vol. 14(17), pages 1-18, September.
  56. Dong, Xianzhou & Guo, Weiyong & Zhou, Cheng & Luo, Yongqiang & Tian, Zhiyong & Zhang, Limao & Wu, Xiaoying & Liu, Baobing, 2024. "Hybrid model for robust and accurate forecasting building electricity demand combining physical and data-driven methods," Energy, Elsevier, vol. 311(C).
  57. Salah Bouktif & Ali Ouni & Sanja Lazarova-Molnar, 2022. "Towards a Rigorous Consideration of Occupant Behaviours of Residential Households for Effective Electrical Energy Savings: An Overview," Energies, MDPI, vol. 15(5), pages 1-30, February.
  58. Shree Krishna Acharya & Young-Min Wi & Jaehee Lee, 2019. "Short-Term Load Forecasting for a Single Household Based on Convolution Neural Networks Using Data Augmentation," Energies, MDPI, vol. 12(18), pages 1-19, September.
  59. Mengkun Liang & Renjing Guo & Hongyu Li & Jiaqi Wu & Xiangdong Sun, 2023. "T-LGBKS: An Interpretable Machine Learning Framework for Electricity Consumption Forecasting," Energies, MDPI, vol. 16(11), pages 1-27, May.
  60. Stefenon, Stefano Frizzo & Seman, Laio Oriel & Aquino, Luiza Scapinello & Coelho, Leandro dos Santos, 2023. "Wavelet-Seq2Seq-LSTM with attention for time series forecasting of level of dams in hydroelectric power plants," Energy, Elsevier, vol. 274(C).
  61. Seok-Jun Bu & Sung-Bae Cho, 2020. "Time Series Forecasting with Multi-Headed Attention-Based Deep Learning for Residential Energy Consumption," Energies, MDPI, vol. 13(18), pages 1-16, September.
  62. João Vitor Leme & Wallace Casaca & Marilaine Colnago & Maurício Araújo Dias, 2020. "Towards Assessing the Electricity Demand in Brazil: Data-Driven Analysis and Ensemble Learning Models," Energies, MDPI, vol. 13(6), pages 1-20, March.
  63. Caroline L Alves & Rubens Gisbert Cury & Kirstin Roster & Aruane M Pineda & Francisco A Rodrigues & Christiane Thielemann & Manuel Ciba, 2022. "Application of machine learning and complex network measures to an EEG dataset from ayahuasca experiments," PLOS ONE, Public Library of Science, vol. 17(12), pages 1-26, December.
  64. Yukta Mehta & Vincent Lo & Vijen Mehta & Kunal Agrawal & Charan Teja Madabathula & Eugene Chang & Jerry Gao, 2025. "Renewable Electricity Management Cloud System for Smart Communities Using Advanced Machine Learning," Energies, MDPI, vol. 18(6), pages 1-29, March.
  65. Davut Solyali, 2020. "A Comparative Analysis of Machine Learning Approaches for Short-/Long-Term Electricity Load Forecasting in Cyprus," Sustainability, MDPI, vol. 12(9), pages 1-34, April.
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  67. Huixin Tian & Daixu Ren & Kun Li & Zhen Zhao, 2021. "An adaptive update model based on improved Long Short Term Memory for online prediction of vibration signal," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 37-49, January.
  68. Sameh Mahjoub & Sami Labdai & Larbi Chrifi-Alaoui & Bruno Marhic & Laurent Delahoche, 2023. "Short-Term Occupancy Forecasting for a Smart Home Using Optimized Weight Updates Based on GA and PSO Algorithms for an LSTM Network," Energies, MDPI, vol. 16(4), pages 1-18, February.
  69. Bingjie Jin & Guihua Zeng & Zhilin Lu & Hongqiao Peng & Shuxin Luo & Xinhe Yang & Haojun Zhu & Mingbo Liu, 2022. "Hybrid LSTM–BPNN-to-BPNN Model Considering Multi-Source Information for Forecasting Medium- and Long-Term Electricity Peak Load," Energies, MDPI, vol. 15(20), pages 1-20, October.
  70. Ramadhan, Raden A.A. & Heatubun, Yosca R.J. & Tan, Sek F. & Lee, Hyun-Jin, 2021. "Comparison of physical and machine learning models for estimating solar irradiance and photovoltaic power," Renewable Energy, Elsevier, vol. 178(C), pages 1006-1019.
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  73. Zimmermann, Monika & Ziel, Florian, 2025. "Efficient mid-term forecasting of hourly electricity load using generalized additive models," Applied Energy, Elsevier, vol. 388(C).
  74. Juncheng Zhu & Zhile Yang & Monjur Mourshed & Yuanjun Guo & Yimin Zhou & Yan Chang & Yanjie Wei & Shengzhong Feng, 2019. "Electric Vehicle Charging Load Forecasting: A Comparative Study of Deep Learning Approaches," Energies, MDPI, vol. 12(14), pages 1-19, July.
  75. Hany Habbak & Mohamed Mahmoud & Khaled Metwally & Mostafa M. Fouda & Mohamed I. Ibrahem, 2023. "Load Forecasting Techniques and Their Applications in Smart Grids," Energies, MDPI, vol. 16(3), pages 1-33, February.
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  80. Barja-Martinez, Sara & Aragüés-Peñalba, Mònica & Munné-Collado, Íngrid & Lloret-Gallego, Pau & Bullich-Massagué, Eduard & Villafafila-Robles, Roberto, 2021. "Artificial intelligence techniques for enabling Big Data services in distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
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  83. Sarah Hadri & Mehdi Najib & Mohamed Bakhouya & Youssef Fakhri & Mohamed El Arroussi, 2021. "Performance Evaluation of Forecasting Strategies for Electricity Consumption in Buildings," Energies, MDPI, vol. 14(18), pages 1-17, September.
  84. Thomas Steens & Jan-Simon Telle & Benedikt Hanke & Karsten von Maydell & Carsten Agert & Gian-Luca Di Modica & Bernd Engel & Matthias Grottke, 2021. "A Forecast-Based Load Management Approach for Commercial Buildings Demonstrated on an Integration of BEV," Energies, MDPI, vol. 14(12), pages 1-25, June.
  85. Umar Javed & Khalid Ijaz & Muhammad Jawad & Ejaz A. Ansari & Noman Shabbir & Lauri Kütt & Oleksandr Husev, 2021. "Exploratory Data Analysis Based Short-Term Electrical Load Forecasting: A Comprehensive Analysis," Energies, MDPI, vol. 14(17), pages 1-22, September.
  86. Hao Wang & Chen Peng & Bolin Liao & Xinwei Cao & Shuai Li, 2023. "Wind Power Forecasting Based on WaveNet and Multitask Learning," Sustainability, MDPI, vol. 15(14), pages 1-22, July.
  87. Jin Sol Hwang & Ismi Rosyiana Fitri & Jung-Su Kim & Hwachang Song, 2020. "Optimal ESS Scheduling for Peak Shaving of Building Energy Using Accuracy-Enhanced Load Forecast," Energies, MDPI, vol. 13(21), pages 1-18, October.
  88. Fatma Yaprakdal & M. Berkay Yılmaz & Mustafa Baysal & Amjad Anvari-Moghaddam, 2020. "A Deep Neural Network-Assisted Approach to Enhance Short-Term Optimal Operational Scheduling of a Microgrid," Sustainability, MDPI, vol. 12(4), pages 1-27, February.
  89. Abdullah Alrasheedi & Abdulaziz Almalaq, 2022. "Hybrid Deep Learning Applied on Saudi Smart Grids for Short-Term Load Forecasting," Mathematics, MDPI, vol. 10(15), pages 1-22, July.
  90. Xue-Bo Jin & Wei-Zhen Zheng & Jian-Lei Kong & Xiao-Yi Wang & Yu-Ting Bai & Ting-Li Su & Seng Lin, 2021. "Deep-Learning Forecasting Method for Electric Power Load via Attention-Based Encoder-Decoder with Bayesian Optimization," Energies, MDPI, vol. 14(6), pages 1-18, March.
  91. Heung-gu Son & Yunsun Kim & Sahm Kim, 2020. "Time Series Clustering of Electricity Demand for Industrial Areas on Smart Grid," Energies, MDPI, vol. 13(9), pages 1-14, May.
  92. Stanislaw Osowski & Robert Szmurlo & Krzysztof Siwek & Tomasz Ciechulski, 2022. "Neural Approaches to Short-Time Load Forecasting in Power Systems—A Comparative Study," Energies, MDPI, vol. 15(9), pages 1-21, April.
  93. Salah Bouktif & Ali Fiaz & Ali Ouni & Mohamed Adel Serhani, 2019. "Single and Multi-Sequence Deep Learning Models for Short and Medium Term Electric Load Forecasting," Energies, MDPI, vol. 12(1), pages 1-21, January.
  94. Munseok Chang & Sungwoo Bae & Gilhwan Cha & Jaehyun Yoo, 2021. "Aggregated Electric Vehicle Fast-Charging Power Demand Analysis and Forecast Based on LSTM Neural Network," Sustainability, MDPI, vol. 13(24), pages 1-17, December.
  95. Changping Li & Xiaohui Wang & Longchen Duan & Bo Lei, 2022. "Study on a Discharge Circuit Prediction Model of High-Voltage Electro-Pulse Boring Based on Bayesian Fusion," Energies, MDPI, vol. 15(10), pages 1-12, May.
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