Article citationsMore>>

Ni, L.J., Zhang, L.G., Tang, M.Y., Xue, Z.B., Zhang, X., Gu, X. and Huang, S.X. (2012) Discrimination of Adulteration Cow Milk by Improved v-Support Vector Machines and near Infrared Spectroscopy. 2012 8th International Conference on Natural Computation, Chongqing, 29-31 May 2012, 69-73.
http://dx.doi.org/10.1109/ICNC.2012.6234508

has been cited by the following article:

• TITLE: The Validity Analysis of Regression: Combining Uniform Experiment Design with Nonlinear Regression

  AUTHORS: Nan Yang, Dawei Zhang, Yanling Tian

  KEYWORDS: the enclosing simplex, support vector machine, uniform experiment design, the smallest enclosing hyper sphere

  JOURNAL NAME: Applied Mathematics, Vol.6 No.6, June 5, 2015

  ABSTRACT: The data topology structure of uniform experiment design (UD) is too complex to be reasonable regressed. In this paper, the principle and method of distinguish the training data and testing data were described to make a reasonable regression when uniform experiment design combined with support vector regression (SVR). Two equivalent ways which were the smallest enclosing hypersphere perceptron (SEH) and the enclosing simplex perceptron (ES) were provided to discover the topology relationship of the process parameter datum. To give an application, a series of experiments about laser cladding layer quality were conducted by UD to get the relationship of load, velocity and wearing capacity. Results showed that only the testing datum recommended by the two perceptrons got a good forecasting by SVR. Therefore, the two perceptrons could guide experiments with process parameter data of complex topology structure. Further, the application could be extended over a much wider field of experiments.