The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, fire detection technology based on multi-sensors information fusion is presented for the complexity of fire process and the multiplicity of fire environment. And support vector machines are used to establish fire detecting model of information fusion, for Support vector machines show excellent performance in generalization and optimization. The improved genetic algorithm by Auto-adaptive...
The nuclear function parameter and penalty parameter is a pivotal factor which decides performance of Least Squares Support Vector Machines (LSSVM). Common used parameters selection method for LSSVM is cross-validation, which is complicated calculation and takes a very long time. To solve these problems, a new approach based on an adaptive genetic algorithm (AGA) was proposed, which automatically...
The generalization error of support vector machine usually depends on its kernel parameters, but there is no analytic method to choose kernel parameters for SVM. In order to choose the kernel parameters for SVM, the simulated annealing algorithm and genetic algorithm are combined, which is called simulated annealing genetic algorithm (SA-GA), to choose the SVM kernel parameters. SA-GA makes use of...
This paper investigates the multi-class minimax probability machine (MPM). MPM constructs a binary classifier that provides a worst-case bound on the probability of misclassification of future data points, based on reliable estimates of means and covariance matrices of the classes from the training data points. We propose a method to adapt MPM to multi-class datasets using the one-against-all strategy...
The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms (EDAs) based method to solve the PSP problem on HP model. Firstly, a composite fitness function containing the information of folding structure core formation is introduced to replace the traditional fitness function of HP...
The precondition of accurate visual system is accurate camera calibration. Used Least Squares Support Vector Machines (LS-SVM) can achieve the camera calibration. The nuclear function parameter and penalty parameter is a pivotal factor which decides performance of LS-SVM. Usually, most users select parameters for an LS-SVM by rule of thumb, so they frequently fail to generate the optimal approaching...
Sakuma and Kobayashi have proposed a density estimation method that utilizes real-coded crossover operators. However, their method was used only to estimate normal distribution functions. In order to estimate more complicated PDFs, this study proposes a new density estimation method of utilizing crossover operators. When we try to solve function optimization problems, on the other hand, real-coded...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.