The nature of statistical learning theory
The nature of statistical learning theory
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A distributed PSO-SVM hybrid system with feature selection and parameter optimization
Applied Soft Computing
Expert Systems with Applications: An International Journal
The forecasting model based on wavelet ν-support vector machine
Expert Systems with Applications: An International Journal
Fault diagnosis of pneumatic systems with artificial neural network algorithms
Expert Systems with Applications: An International Journal
Fault diagnosis of power transformer based on support vector machine with genetic algorithm
Expert Systems with Applications: An International Journal
The hybrid forecasting model based on chaotic mapping, genetic algorithm and support vector machine
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Regression application based on fuzzy ν-support vector machine in symmetric triangular fuzzy space
Expert Systems with Applications: An International Journal
Journal of Computational and Applied Mathematics
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In view of the bad diagnosing capability of standard support vector classifier machine (SVC) for fault diagnosis pattern series with Gaussian noises, Gaussian function is used as loss function of SVC and a new SVC based on Gaussian loss function technique, by name g-SVC, is proposed. To seek the optimal parameter combination of g-SVC, particle swarm optimization (PSO) is proposed. And then, a intelligent fault diagnosing method based on g-SVC and PSO is put forward. The results of its application to car assembly line diagnosis indicate that the diagnosing method is effective and feasible.