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On implementations of H-2 preview output feedback law with application to LFC with load demand prediction
Hashikura K, Hotchi R, Kojima A, Masuta T
International Journal of Control, 93(4), 844, 2020 |
| 2 |
Deep learning framework to forecast electricity demand
Bedi J, Toshniwal D
Applied Energy, 238, 1312, 2019 |
| 3 |
Thermal load prediction in district heating systems
Guelpa E, Marincioni L, Capone M, Deputato S, Verda V
Energy, 176, 693, 2019 |
| 4 |
Energy storage based MG connected system for optimal management of energy: An ANFMDA technique
Murugaperumal K, Raj PADV
International Journal of Hydrogen Energy, 44(16), 7996, 2019 |
| 5 |
Machine learning-based thermal response time ahead energy demand prediction for building heating systems
Guo YB, Wang JY, Chen HX, Li GN, Liu JY, Xu CL, Huang RG, Huang Y
Applied Energy, 221, 16, 2018 |
| 6 |
Water source heat pump energy demand prognosticate using disparate data-mining based approaches
Ahmad T, Chen HX, Shair J
Energy, 152, 788, 2018 |
| 7 |
Day-ahead prediction of hourly electric demand in non-stationary operated commercial buildings: A clustering-based hybrid approach
Chen YB, Tan HW, Berardi U
Energy and Buildings, 148, 228, 2017 |
| 8 |
Forecasting the natural gas demand in China using a self-adapting intelligent grey model
Zeng B, Li C
Energy, 112, 810, 2016 |
| 9 |
A hybrid self-adaptive Particle Swarm Optimization-Genetic Algorithm-Radial Basis Function model for annual electricity demand prediction
Yu SW, Wang K, Wei YM
Energy Conversion and Management, 91, 176, 2015 |
| 10 |
Development of an energy prediction tool for commercial buildings using case-based reasoning
Monfet D, Corsi M, Choiniere D, Arkhipova E
Energy and Buildings, 81, 152, 2014 |
