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Recurrent Neural Networks Application to Forecasting with Two Cases: Load and Pollution

Tao Q., Liu F., Sidorov D. Recurrent Neural Networks Application to Forecasting with Two Cases: Load and Pollution // Advances in Intelligent Systems and Computing. Vol.1072. 2020. P.369-378. ISBN (print): 9783030335847. DOI: 10.1007/978-3-030-33585-4_37 Forecasting problems exist widely in our life. Its purpose is to enable decision makers to make effective responses to future changes. The traditional prediction methods based on probability and statistics cannot guarantee the accuracy of multivariable...

Теги: deep learning , forecasting , gru , lstm , decision making , intelligent computing , learning algorithms , machine learning , pollution , forecasting modeling , forecasting models , forecasting problems , neural netwo
Раздел: ИСЭМ СО РАН
Multi-criteria Decision Making Problems in Hierarchical Technology of Electric Power System Expansion Planning

Voropai N.I. Multi-criteria Decision Making Problems in Hierarchical Technology of Electric Power System Expansion Planning // Advances in Intelligent Systems and Computing. Vol.866. 2019. P.362-368. ISBN (print): 9783030009786. DOI: 10.1007/978-3-030-00979-3_38 This paper deals with expansion planning problem of large electric power systems. The initial complicate multi-criteria problem is presented as hierarchical set of step-by-step solved sub-problems. Each sub-problem is characterized its own...

Теги: electric power system , expansion planning , multi-criteria problem , decision making , electric power systems , expansion , intelligent computing , electric power , expansion planning problems , initial problem , multi-criteria , multi-criteria decision mak
Раздел: ИСЭМ СО РАН


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