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Shu-Chuan Chu
Researcher at Shandong University of Science and Technology
Publications - 303
Citations - 5475
Shu-Chuan Chu is an academic researcher from Shandong University of Science and Technology. The author has contributed to research in topics: Computer science & Wireless sensor network. The author has an hindex of 28, co-authored 231 publications receiving 3652 citations. Previous affiliations of Shu-Chuan Chu include University of South Australia & Sewanee: The University of the South.
Papers
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Journal ArticleDOI
Adaptively weighted sub-directional two-dimensional linear discriminant analysis for face recognition
TL;DR: A novel image classification algorithm named Adaptively Weighted Sub-directional Two-Dimensional Linear Discriminant Analysis (AWS2DLDA) can extract the directional features of images in the frequency domain, and it is applied to face recognition.
Journal ArticleDOI
Golden eagle optimizer with double learning strategies for 3D path planning of UAV in power inspection
Hu Li,Jeng-Shyang Pan,Jeng-Shyang Pan,Ji-Xiang Lv,Lijun Yan,Shao-Wei Weng,Shu-Chuan Chu,Shu-Chuan Chu,Jian-Kai Xue +8 more
TL;DR: In this paper, a Golden eagle optimizer with double learning strategies (GEO-DLS) is proposed to solve the problem of UAV path planning in the complex environment.
Book ChapterDOI
A Reduce Identical Event Transmission Algorithm for Wireless Sensor Networks
TL;DR: In the simulation, the RIET algorithm can enhance sensor nodes’ life time about 12.9 times and saving power consumption about 52.43 % than tradition algorithms.
Journal ArticleDOI
Wind power prediction based on neural network with optimization of adaptive multi-group salp swarm algorithm
Jeng-Shyang Pan,Jeng-Shyang Pan,Jeng-Shyang Pan,Jie Shan,Shi-Guang Zheng,Shu-Chuan Chu,Shu-Chuan Chu,Cheng-Kuo Chang +7 more
TL;DR: A adaptive multi-group salp swarm algorithm (AMSSA) with three new communication strategies is presented and it is shown that the AMSSA-BP neural network prediction model can achieve a better prediction effect of wind power.
Journal ArticleDOI
A Transmission Power Optimization with a Minimum Node Degree for Energy-Efficient Wireless Sensor Networks with Full-Reachability
TL;DR: In this study, an optimization approach to an energy-efficient and full reachability wireless sensor network is proposed that focuses on topology control and optimization of the transmission range according to node degree and node density.