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81

Day-ahead Multiple Households Load Forecasting using Deep Learning and Unsupervised Clustering
Budin, Luka ; Duilo, Ivan ; Delimar, Marko ; et al.
2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO). :30-35

electrical energy household load forecasti... deep learning artificial neural networ... unsupervised clustering Keras Tuner …
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82

Isolation Forest-Based Anomaly Detection Through Generation Offers and Optimal Dispatch Data
Ahmad, Muhammad ; Imran, Kashif ; Attar, Hani ; et al.
2025 International Conference on Emerging Power Technologies (ICEPT). :1-6

Genco Dispatch Isolation Forest Control and Optimization Sustainability and the E... Computer Networks and Co... Anomaly Detection …
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83

Day-Ahead Wind Power Forecasting Using Machine Learning Algorithms
Akash. R ; A. G. Rangaraj ; R. Meenal ; et al.
Advances in Intelligent Systems and Computing ISBN: 9789811568756

13. Climate action 7. Clean energy
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84

Deep Neural Networks for Predicting Solar Radiation at Hail Region, Saudi Arabia
Sahbi Boubaker ; M. Benghanem ; A. Mellit ; et al.
IEEE Access, Vol 9, Pp 36719-36729 (2021)

Artificial neural networ... Artificial intelligence Electricity Price and Lo... GRU Global horizontal irradi... 0211 other engineering a... …
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85

A cross-sectional exploration of cognitive ability across age via stacked ensembles.
Congdon, Eliza L. ; Liu, Samuel ; Upton, Elizabeth M.
Psychol Aging

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86

Prediction of the river water environment carrying capacity using LSTM networks
Long Ta Bui ; Tran Ngoc Dang ; Dan Phuoc Nguyen
Water Supply, Vol 24, Iss 7, Pp 2518-2533 (2024)

Environmental Engineerin... Rainfall-Runoff Modeling lstm water quality 01 natural sciences 7. Clean energy …
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87

APPLICATION OF BIG DATA TECHNOLOGIES TO ASSESS THE NATURAL MOISTURE OF THE TERRITORY
Anna I. Pavlova
Siberian Journal of Life Sciences and Agriculture, Vol 15, Iss 3, Pp 139-154 (2023)

2. Zero hunger Science Agriculture 15. Life on land 7. Clean energy climatic conditions …
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88

Development Of Prediction Models Of Day-Ahead Hourly Building Electricity Consumption And Peak Power Demand Using The Machine Learning Method
Dalin Si ; Azizan Aziz ; Lasternas, Bertrand

0202 electrical engineer... 02 engineering and techn... 7. Clean energy
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89

Weather Forecasting in Python Django with Machine Learning
Soumya Meshram
International Journal for Research in Applied Science and Engineering Technology. 10:487-489

13. Climate action
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90

Machine Learning Approach for Solar Irradiance Estimation on Tilted Surfaces in Comparison with Sky Models Prediction
Mbah, O.M. ; Madueke, C.I. ; Umunakwe, R. ; et al.
Журнал інженерних наук, Vol 9, Iss 2, Pp G1-G6 (2022)

machine learning tilted surface solar radiation sky models solar energy 0202 electrical engineer... …
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91

Machine Learning-Based Predictive Techno-Economic Analysis of Power System
Hephzibah Jose Queen ; Jayakumar J. ; Deepika T. J. ; et al.
IEEE Access, Vol 9, Pp 123504-123516 (2021)

machine learning renewable generation voltage stability predictive analysis Cost analysis 0202 electrical engineer... …
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92

Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark
Jesus Lago ; Grzegorz Marcjasz ; Bart De Schutter ; et al.
Applied Energy. 293:116983

FOS: Computer and inform... FOS: Economics and busin... Computer Science - Machi... Statistical Finance (q-f... 0211 other engineering a... 0202 electrical engineer... …
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93

Design of Short-Term Wind Production Forecasting Model using Machine Learning Algorithms
Marius Eugen Tiboaca ; Sorina Costinas ; Petrica Radan
2021 12th International Symposium on Advanced Topics in Electrical Engineering (ATEE). :1-6

0203 mechanical engineer... 0202 electrical engineer... 02 engineering and techn... 7. Clean energy
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94

A day-ahead Multi-Approach Machine L earning Technique for Photovoltaic Power Forecasting
Aime C. Nyoungue ; Hajej Zied ; Aisha Sa'ad
2020 9th International Conference on Renewable Energy Research and Application (ICRERA). :257-262

13. Climate action 0202 electrical engineer... 02 engineering and techn... 7. Clean energy
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95

A Hybrid Time Series Forecasting Method Based on Supervised Machine Learning Program
Sarat Chandra Swain ; Prashant Bawaney ; Ganesh Prasad Khuntia ; et al.
Lecture Notes on Data Engineering and Communications Technologies ISBN: 9789811509773

7. Clean energy
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96

A million cycles in a day: Enabling high-throughput computing of lithium-ion battery degradation with physics-based models
Ruihe Li ; Simon O'Kane ; Jianbo Huang ; et al.
Journal of Power Sources. 598:234184

Chemical Physics (physic... Physics - Chemical Physi... 0211 other engineering a... 0202 electrical engineer... FOS: Physical sciences 02 engineering and techn... …
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97

Graph neural networks for solar energy nowcasting and intra-day prediction in Central Europe
Irene Schicker ; Petrina Papazek

13. Climate action 7. Clean energy
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98

Signal processing and machine learning with transdermal alcohol concentration to predict natural environment alcohol consumption.
Didier, Nathan A. ; King, Andrea C. ; Polley, Eric C. ; et al.
Exp Clin Psychopharmacol

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99

Advanced machine learning techniques for building performance simulation: a comparative analysis
Debaditya Chakraborty ; Hazem Elzarka
Journal of Building Performance Simulation. 12:193-207

13. Climate action 11. Sustainability 0202 electrical engineer... 02 engineering and techn... 7. Clean energy
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100

Fast, Cheap, and Turbulent—Global Ocean Modeling With GPU Acceleration in Python
Dion Häfner ; Roman Nuterman ; Markus Jochum
Häfner, D, Nuterman, R & Jochum, M 2021, ' Fast, Cheap, and Turbulent—Global Ocean Modeling With GPU Acceleration in Python ', Journal of Advances in Modeling Earth Systems (JAMES), vol. 13, no. 12, e2021MS002717 . https://doi.org/10.1029/2021MS002717

0207 environmental engin... 02 engineering and techn... 14. Life underwater 01 natural sciences 7. Clean energy 0105 earth and related e...
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