Fault diagnosis using a probability least squares support vector classification machine
โ Scribed by Yang GAO; Xuesong WANG; Yuhu CHENG; Jie PAN
- Publisher
- Elsevier
- Year
- 2010
- Tongue
- English
- Weight
- 180 KB
- Volume
- 20
- Category
- Article
- ISSN
- 1674-5264
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
In this paper we apply a recently proposed technique of optimal control by support vector machines (SVMs) to chaos control. Vapnik's support vector method, which is based on the structural risk minimization principle and has been very successful in classi"cation and function estimation problems, is
We study the problem of repeat-purchase modeling in a direct marketing setting using Belgian data. More specifically, we investigate the detection and qualification of the most relevant explanatory variables for predicting purchase incidence. The analysis is based on a wrapped form of input selectio
A method for the rapid identification of the genuineness of Chinese medicines based on near infrared (NIR) spectroscopy and least squares support vector machines (LSSVM) was proposed. In this study, NIR spectra of the powdered Danshen (Radix Salviae Miltiorrhizae) were collected, and the nonlinear c
This paper presents a new method for fault diagnosis using a newly developed method, support vector machine (SVM). First, the basic theory of the SVM is briefly reviewed. Next, a fast implementation algorithm is given. Then the method is applied for the fault diagnosis in sheet metal stamping proces