neural network is one of the most widely used algorithms in the field of machine learning, on the other hand, neural network training is a complicated and important process. supervised learning needs to be organized to reach the goal as soon as possible. a supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.  hen...

according to this fact that wind is now a part of global energy portfolio and due to unreliable and discontinuous production of wind energy; prediction of wind power value is proposed as a main necessity. in recent years, various methods have been proposed for wind power prediction. in this paper the prediction structure involves feature selection and use of artificial neural network (ann). in ...

cerebellar model articulation controller neural network is a computational model of cerebellum which acts as a lookup table. the advantages of cmac are fast learning convergence, and capability of mapping nonlinear functions due to its local generalization of weight updating, single structure and easy processing. in the training phase, the disadvantage of some cmac models is unstable phenomenon...

We investigate the problem of training a Support Vector Machine (SVM) 1, 2, 7] on a very large date base (e.g. 50,000 data points) in the case in which the number of support vectors is also very large (e.g. 40,000). Training a SVM is equivalent to solving a linearly constrained quadratic programming (QP) problem in a number of variables equal to the number of data points. This optimization prob...

the large amount of computation necessary for obtaining time optimal solution for moving a manipulator on specified path has made it impossible to introduce an on line time optimal control algorithm. most of this computational burden is due to calculation of switching points. in this paper a learning algorithm is proposed for finding the switching points. the method, which can be used for both ...

multiple people detection and tracking is a challenging task in real-world crowded scenes. in this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. we have detected objects with deformable part models and a visual background extractor. in the tracking phase we have used a combination of support vector machine (svm) person-specific classifie...