A5111784946- Odor and Emission Control Technologies
- Metal Forming Simulation Techniques
- Human Pose and Action Recognition
- Neural Networks and Applications
- Environmental Chemistry and Analysis
- Domain Adaptation and Few-Shot Learning
- Advanced Computational Techniques and Applications
- Neurofibromatosis and Schwannoma Cases
- Machine Learning in Materials Science
- Advanced Control Systems Optimization
- Silicon and Solar Cell Technologies
- Metal Alloys Wear and Properties
- Anomaly Detection Techniques and Applications
- Water Quality Monitoring and Analysis
- Spinal Dysraphism and Malformations
- Microstructure and Mechanical Properties of Steels
- Glioma Diagnosis and Treatment
- Technology and Security Systems
- Fault Detection and Control Systems
University of Warwick
2024
Masteel (China)
2017
Huashan Hospital
2016
Fudan University
2016
Feminist Archive North
2000
Nanjing University
1999
Two methods for estimation of kinetic parameters in the Arrhenius reaction rate function, logarithmic and learning method using a neural mini— net, are proposed, sucessfully applied to certain taking place CSTR. More implortantly, application example shows plausibility introduction up datable activation function into networks, background chemical kinetics.
Both multiple linear regressions (MLR) and artificial neural network (ANN) models have been developed to fit predict aerobic microbial degradation rate constants of 25 aromatic sulfur‐containing compounds. First, the codes function groups were used as structural descriptors establish models. It turned out be a useful way extract information from molecule. Then, performance MLR ANN was compared. Due its special ability automatically including couplings interactions between in molecule, led...