Cheng-Chien Kuo

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Support vector regression (SVR) has been very successful in pattern recognition, text categorization, and function approximation. The theory of SVR is based on the idea of structural risk minimization. In real application systems, data domain often suffers from noise and outliers. When there is noise and/or out-liers exist in sampling data, the SVR may try(More)
This paper presents new solution methods and results based on a refined binary particle swarm optimization (RBPSO) for solving the generation/pumping scheduling problem within the power system operation with pumped-storage units. The proposed RBPSO approach combines a basic particle swarm optimization (PSO) with binary encoding/decoding techniques. Complete(More)
Insulation material for power systems subjected to long-tern operation may deteriorate because of various reasons. If equipment are poorly maintained, the power system may collapse and cause blackouts. To protect high-voltage power system equipment, identifying and analyzing the partial discharge phenomenon caused by insulation deterioration has become an(More)
A methodology for common failure types classification of wind turbine based on the Hilbert-Huang Transform (HHT) with Fractal feature enhancement is proposed. Firstly, failure types of wind turbines were established according to the frequency of happened for wind turbine. The current of generators from pre-failure wind turbines under operating are measured(More)
This paper presents a novel solution algorithm based on a refined genetic algorithm for solving the hydro generation scheduling problem. In this work, complete solution algorithms and encoding/decoding techniques are proposed for solving different types of hydro plants involving hydraulically independent plants, hydraulically coupled plants, and(More)