Z
Zhile Yang
Researcher at Chinese Academy of Sciences
Publications - 168
Citations - 3114
Zhile Yang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Computer science & Optimization problem. The author has an hindex of 22, co-authored 141 publications receiving 1644 citations. Previous affiliations of Zhile Yang include Fudan University & Queen's University Belfast.
Papers
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Proceedings ArticleDOI
TRIZ based teaching strategy for wind turbine control
TL;DR: In this article, a TRIZ-based strategy is developed for teaching the wind turbine control module, which can help to strengthen the appreciation and application of wind turbine knowledge for the students majoring in wind energy and power engineering.
Book ChapterDOI
The Design and Simulation of a Two-Layer Network Protocol for Industrial Wireless Monitoring and Control System
TL;DR: The result shows that the network based on the WICN-TL protocol performs well in communication and the covered range is sufficient to apply to the normal industrial application demand.
Book ChapterDOI
A Regression Model for Short-Term COVID-19 Pandemic Assessment
TL;DR: In this article, a time series regression model is built to assess the short-term progression of the COVID-19 pandemic, and the same model structure and parameters are applied to a few other countries for day ahead forecasting, showing a good fit of the model.
Book ChapterDOI
A Novel Optimization Algorithm for Solving Parameters Identification of Battery Model
TL;DR: In this article, an improved JAYA (IJAYA) optimization algorithm is presented to extract the parameters of the battery model, which can increase the probability of obtaining the best solution and enhance the population diversity.
Posted ContentDOI
Chaos Moth Flame Algorithm for Multi-Objective Dynamic Economic Dispatch Integrating with Plug-In Electric Vehicles
TL;DR: In this paper , an improved chaos moth flame optimization algorithm (CMFO) is introduced to solve the model, which has a faster convergence rate and better global optimization capabilities due to the incorporation of chaotic mapping.