Zhong-kai Feng
Biographic Data
| ID | 7997838 |
|---|---|
| NAME | Zhong-kai Feng |
| GIVEN NAMES | Zhong-kai |
| FAMILY NAME | Feng |
| SIGNATURE | FENG Z |
| AFFILIATIONS | Huazhong University of Science and Technology |
| ORCID | 0000-0002-0166-8956 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
Theoretical analysis of advanced intelligent computing in environmental research
Evaluating the performances of several artificial intelligence methods in forecasting daily streamflow time series for sustainable water resources management
Parallel computing and swarm intelligence based artificial intelligence model for multi-step-ahead hydrological time series prediction
Enhanced harmony search algorithm for sustainable ecological operation of cascade hydropower reservoirs in river ecosystem
With the merits of superior performance and easy implementation, the harmony search (HS), a famous population-based evolutionary method, has been widely adopted to resolve global optimization problems in practice. However, the standard HS method still suffers from the defects of premature convergence and local stagnation in the complex multireservoir operation problem. Thus, this study develops an enhanced harmony search (EHS) method to improve t…
Short-term electricity load time series prediction by machine learning model via feature selection and parameter optimization using hybrid cooperation search algorithm
Reliable load time series forecasting plays an important role in guaranteeing the safe and stable operation of modern power system. Due to the volatility and randomness of electricity demand, the conventional forecasting method may fail to effectively capture the dynamic change of load curves. To satisfy this practical necessity, the goal of this paper is set to develop a practical machine learning model based on feature selection and parameter o…
No prominent works on this page.
Evaluating the performances of several artificial intelligence methods in forecasting daily streamflow time series for sustainable water resources management
Parallel computing and swarm intelligence based artificial intelligence model for multi-step-ahead hydrological time series prediction
Enhanced harmony search algorithm for sustainable ecological operation of cascade hydropower reservoirs in river ecosystem
With the merits of superior performance and easy implementation, the harmony search (HS), a famous population-based evolutionary method, has been widely adopted to resolve global optimization problems in practice. However, the standard HS method still suffers from the defects of premature convergence and local stagnation in the complex multireservoir operation problem. Thus, this study develops an enhanced harmony search (EHS) method to improve t…
Short-term electricity load time series prediction by machine learning model via feature selection and parameter optimization using hybrid cooperation search algorithm
Reliable load time series forecasting plays an important role in guaranteeing the safe and stable operation of modern power system. Due to the volatility and randomness of electricity demand, the conventional forecasting method may fail to effectively capture the dynamic change of load curves. To satisfy this practical necessity, the goal of this paper is set to develop a practical machine learning model based on feature selection and parameter o…
Theoretical analysis of advanced intelligent computing in environmental research
Computer Science (5 works) · Hydrological Forecasting Using AI (4 works) · Artificial Intelligence (3 works) · Energy Load and Power Forecasting (3 works) · Machine learning (3 works) · Engineering (2 works) · Hydropower (2 works) · Mathematical optimization (2 works) · Mathematics (2 works) · Particle swarm optimization (2 works)