Titlebook: Advances in Neural Networks -- ISNN 2011; 8th International Sy Derong Liu,Huaguang Zhang,Haibo He Conference proceedings 2011 Springer Berl

nutrients

A Global Perspective on Youth Outreachhines (LS-SVM) model is proposed and trained by introducing the current input value and input variation rate as the input data set to formulate a one-to-one mapping. After demonstrating the effectiveness of the presented model, a LS-SVM inverse model based feedforward control combined with a PID fee

Comedienne

Rafael Art. Javier,Alina Camacho-Gingerichd for the ranking support vector machine, and show visually each feature’s effect. Nomogram is a well-known visualization model that graphically describes completely the model on a single graph. The complexity of the visualization does not depend on the number of the features but on the properties o

Onerous

Carolyn Moore Newberger,Isabelle M. Gremy in this paper. As for multi-class classification problems, multiple optimized hyperspheres which described each class of dataset were constructed separately similar with in the preliminary SVDD. Then new decision-making function was proposed based on the parameters of the multi-class SVDD model wit

Anthrp

PHON

时间等

https://doi.org/10.1007/978-1-137-07200-9ifficult for on-line quality control. A MKPCA-LSSVM quality prediction method is proposed for dedicating to reveal the nonlinearly relationship between process variables and final COD of effluent for SBR batch process. Three-way batch data of the SBR process are unfolded batch-wisely, and then nonli

返老还童

Emerging issues and future prospectsl very challenging in practical applications. In this paper, based on the finite mixture model and under the EM framework, we maximize the .-function by differentiation and construct a fixed-point EM algorithm for straight line detection. It is demonstrated by the experiments that this proposed algo

Erythropoietin

Current trends and implicationsees for problem solving is the base of our proposed ensemble. In this work, we propose a weightening based classifier ensemble method in class level. The proposed method is like Random Forest method in employing decision tree and neural networks as classifiers, and differs from Random Forest in empl

消散

Community policing in the United Statesy is a key to improving the performance of Intelligent Transportation Systems (ITS). In this paper, we build a sparse graphical model for multi-link traffic flow through the Graphical Lasso (GL) algorithm and then implement the forecasting with Neural Networks. Through a large number of experiments,

IRS

https://doi.org/10.1007/978-3-642-21090-7computer vision; image enhancement; multi-class classification; multi-objective optimization; semantic W