| 1 |
Modeling and optimizing callus growth and development in Cannabis sativa using random forest and support vector machine in combination with a genetic algorithm
Hesami M, Jones AMP
Applied Microbiology and Biotechnology, 105(12), 5201, 2021 |
| 2 |
LightGBM Technique and Differential Evolution Algorithm-Based Multi-Objective Optimization Design of DS-APMM
Pan ZB, Fang SH, Wang H
IEEE Transactions on Energy Conversion, 36(1), 441, 2021 |
| 3 |
Computer-assisted demand-side energy management in residential smart grid employing novel pooling deep learning algorithm
Jeyaraj PR, Nadar ERS
International Journal of Energy Research, 45(5), 7961, 2021 |
| 4 |
Demand response model based on improved Pareto optimum considering seasonal electricity prices for Dongfushan Island
Wu XM, Cao WH, Wang DH, Ding M, Yu LJ, Nakanishi Y
Renewable Energy, 164, 926, 2021 |
| 5 |
Application of artificial intelligence models and optimization algorithms in plant cell and tissue culture
Hesami M, Jones AMP
Applied Microbiology and Biotechnology, 104(22), 9449, 2020 |
| 6 |
Q-Learning based Maximum Power Extraction for Wind Energy Conversion System With Variable Wind Speed
Kushwaha A, Gopal M, Singh B
IEEE Transactions on Energy Conversion, 35(3), 1160, 2020 |
| 7 |
Application of optimized artificial intelligence algorithm to evaluate the heating energy demand of non-residential buildings at European level
Ciulla G, D'Amico A, Lo Brano V, Traverso M
Energy, 176, 380, 2019 |
| 8 |
Online Markov Chain-based energy management for a hybrid tracked vehicle with speedy Q-learning
Liu T, Wang B, Yang CL
Energy, 160, 544, 2018 |
| 9 |
An approximate dynamic programming method for the optimal control of Alkai-Surfactant-Polymer flooding
Ge YL, Li SR, Chan P
Journal of Process Control, 64, 15, 2018 |
| 10 |
An artificial neural network approach to determine the rheological behavior of pickering-type diesel-in-water emulsion prepared with the use of β-cyclodextrin
Monazzami A, Vahabzadeh F, Aroujalian A, Mogharei A
Korean Journal of Chemical Engineering, 35(4), 847, 2018 |
