| 1 |
Introducing a hybrid artificial intelligence method for high-throughput modeling and optimizing plant tissue culture processes: the establishment of a new embryogenesis medium for chrysanthemum, as a case study
Hesami M, Naderi R, Tohidfar M
Applied Microbiology and Biotechnology, 104(23), 10249, 2020 |
| 2 |
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 |
| 3 |
Data-driven modeling for river flood forecasting based on a piecewise linear ARX system identification
Hadid B, Duviella E, Lecoeuche S
Journal of Process Control, 86, 44, 2020 |
| 4 |
Data-driven modeling of product crystal size distribution and optimal input design for batch cooling crystallization processes
Liu JX, Liu T, Chen JH, Yue H, Zhang FK, Sun FR
Journal of Process Control, 96, 1, 2020 |
| 5 |
Data-driven Bayesian network model for early kick detection in industrial drilling process
Nhat DM, Venkatesan R, Khan F
Process Safety and Environmental Protection, 138, 130, 2020 |
| 6 |
Machine-learning based study on the on-site renewable electrical performance of an optimal hybrid PCMs integrated renewable system with high-level parameters' uncertainties
Zhou YK, Zheng SQ, Zhang GQ
Renewable Energy, 151, 403, 2020 |
| 7 |
A hybrid building thermal modeling approach for predicting temperatures in typical, detached, two-story houses
Cui BR, Fan C, Munk J, Mao N, Xiao F, Dong J, Kuruganti T
Applied Energy, 236, 101, 2019 |
| 8 |
Hierarchical batch-to-batch optimization of cobalt oxalate synthesis process based on data-driven model
Jia RD, Mao ZZ, He DK, Chu F
Chemical Engineering Research & Design, 144, 185, 2019 |
| 9 |
A systematic feature selection procedure for short-term data-driven building energy forecasting model development
Zhang L, Wen J
Energy and Buildings, 183, 428, 2019 |
| 10 |
Early predicting cooling loads for energy-efficient design in office buildings by machine learning
Ngo NT
Energy and Buildings, 182, 264, 2019 |
