IRIS flower data is a class of multi variable data set, which is widely applied in data classification. This paper aims at the parameter optimization problem of least squares support vector machine (LS-SVM) in data classification, an improved particle swarm optimization(IMPSO) algorithm is introduced into the LS-SVM model for improving the learning performance and generalization ability of LS-S...

In hybrid simulation, the structure is divided into numerical and physical substructures to achieve more accurate responses in comparison to a full computational analysis. As a consequence of the lack of test facilities and actuators, and the budget limitation, only a few substructures can be modeled experimentally, whereas the others have to be modeled numerically. In this paper, a new hybrid ...

For assessing and selecting sustainable suppliers, this study considers a triple-bottom-line approach, including profit, people and planet, and regards business operations, environmental effects along with social responsibilities of the suppliers. Diverse metrics are acquainted with measure execution in these three issues. This study builds up a new hybrid intelligent model, namely COA-LS-SVM, ...

an important property that has been extensively studied in quantitative structure activityrelationship (qsar) is the chromatographic retention index. qsar study is suggested for theprediction of retention index of alkanes and alkenes compounds. modeling of the retention indexof alkanes and alkenes compounds as a function of molecular structures was established bydifferent chemometrics methods. ...

Among Neural Network methods, the Support Vector Machine (SVM) solutions are attracting increasing attention, mostly because they automatically derive the “optimal” network structure, in respect to generalization error for a given problem. In practice it means, that a lot of decisions that had to be made during the design of a traditional NN (e.g. the number of neurons, the length and type of t...

This paper presents a SVM-based local search (SVM-LS) approach to the problem of gene selection and classification of microarray data. The proposed approach is highlighted by the use of a SVM classifier both as an essential part of the evaluation function and as a “provider” of useful information for designing effective LS algorithms. The SVM-LS approach is assessed on a set of three well-known...

Gas concentration, which is a chaotic time series in essence, is a key factor of the coal mine safety. An accurate forecast of gas concentration is required to guarantee safety and has very highly social and economic benefits. Least squares support vector machine (LS-SVM) has been receiving increasing interest in areas ranging from its original application in pattern recognition to other applic...

In this paper, we propose some improvements for the implementations of least squares support vector machine classifiers (LS-SVM). An improved conjugate gradient scheme is proposed for solving the optimization problems in LS-SVM, and an improved SMO algorithm is put forward for the general unconstrained quadratic programming problems which is the case of LS-SVM without the bias term. Numerical e...