T
Ta-Peng Tsao
Researcher at National Sun Yat-sen University
Publications - 23
Citations - 700
Ta-Peng Tsao is an academic researcher from National Sun Yat-sen University. The author has contributed to research in topics: Genetic algorithm & Tabu search. The author has an hindex of 11, co-authored 23 publications receiving 656 citations. Previous affiliations of Ta-Peng Tsao include National Taipei University of Technology & Fortune Institute of Technology.
Papers
More filters
Journal ArticleDOI
Application of a fuzzy neural network combined with a chaos genetic algorithm and simulated annealing to short-term load forecasting
Gwo-Ching Liao,Ta-Peng Tsao +1 more
TL;DR: A fuzzy neural network combined with a chaos-search genetic algorithm (CGA) and simulated annealing (SA) applied to short-term power-system load forecasting as a sample test demonstrates an encouraging degree of accuracy superior to other commonly used forecasting methods available.
Journal ArticleDOI
Quantum genetic algorithm for dynamic economic dispatch with valve-point effects and including wind power system
TL;DR: In this article, an optimization algorithm is proposed to solve the problem of the economic dispatch that includes wind power generation using quantum genetic algorithm (QGA), which is able to find the optimal solution most quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time).
Journal ArticleDOI
Application of fuzzy neural networks and artificial intelligence for load forecasting
Gwo-Ching Liao,Ta-Peng Tsao +1 more
TL;DR: An integrated evolving fuzzy neural network and simulated annealing (AIFNN) for load forecasting method to improve the shortcoming of the traditional ANN training where the weights and biases are always trapped into a local optimum.
Journal ArticleDOI
Study of Partial Discharge Measurement in Power Equipment Using Acoustic Technique and Wavelet Transform
TL;DR: In this paper, a noncontact type of acoustic measurement system and applies wavelet transform to noise suppression in order to raise the correct partial discharge (PD) signal identification rate was proposed.
Journal ArticleDOI
New diagnosis approach to epoxy resin transformer partial discharge using acoustic technology
TL;DR: This paper compares acoustic signals' three-dimensional patterns with their polar-coordinate patterns and provides a new analyzing and identification method for partial discharge (PD) fault types that can help identify epoxy-resin transformers' PD fault types.