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Jeng-Shyang Pan

Researcher at Shandong University of Science and Technology

Publications -  889
Citations -  14887

Jeng-Shyang Pan is an academic researcher from Shandong University of Science and Technology. The author has contributed to research in topics: Digital watermarking & Computer science. The author has an hindex of 50, co-authored 789 publications receiving 11645 citations. Previous affiliations of Jeng-Shyang Pan include National Kaohsiung Normal University & Technical University of Ostrava.

Papers
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Journal Article

An Efficient Differential Evolution Via Both Top Collective and p-Best Information

TL;DR: Experimental results show that CIpBDE outperforms the seven state-of-the-art DE variants in terms of classification accuracy and improved parameter adaptation strategy to adaptability to adjust the parameters crossover probability and scale factor value in each generation.
Proceedings ArticleDOI

The QUATRE structure: An efficient approach to tackling the structure bias in Differential Evolution

TL;DR: This paper first presents the reason why an exploration bias is still existing in the binomial crossover, and then presents a novel QUATRE structure to tackle this bias, and the experiment results show its superiority.
Proceedings ArticleDOI

Statistical Based Waveform Classification for Cloud Intrusion Detection

TL;DR: This paper proposes a cloud intrusion detection with a new statistical waveform based classification that records network connections over a period of time to form a waveform, and then computes the suspicious characteristics of the waveform.
Journal ArticleDOI

A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application

TL;DR: It is confirmed that Quasi-affine Transformation evolutionary for the Fruit fly Optimization Algorithm can achieve better vehicle routes planning and is compared with the contrast algorithms to prove its effectiveness.
Book ChapterDOI

Study of PSO Optimized BP Neural Network and Smith Predictor for MOCVD Temperature Control in 7 nm 5G Chip Process

TL;DR: In this article, the authors proposed PID controller of PSO and BP neural network algorithm to improve the control ability of MOCVD temperature, which has better dynamic performance, and the value from 150 to 500 s is stable from 0 to 1 no vibration, any overshoot and short adjustment time, ideal control.