23rd IAEA Fusion Energy Conference: summary of sessions EX/C and ICC

An overview is given of recent experimental results in the areas of innovative confinement concepts, operational scenarios and confinement experiments as presented at the 2010 IAEA Fusion Energy Conference. Important new findings are presented from fusion devices worldwide, with a strong focus towards the scientific and technical issues associated with ITER and W7-X devices, presently under construction

Pattern Classification

Pattern recognition systems play a role in applications as diverse as speech recognition, optical character recognition, image processing, and signal analysis. This reference provides information needed to choose the most appropriate of the many available techniques for a given class of problems. The latest edition includes explanations of classical and new methods, including neural networks, stochastic methods, genetic algorithms, and theory of learning. It provides algorithms to explain specific pattern-recognition and learning techniques as well as appendices covering the necessary mathematical background

An improved Gbest guided artificial bee colony (IGGABC) algorithm for classification and prediction tasks

Artificial Neural Networks (ANN) performance depends on network topology, activation function, behaviors of data, suitable synapse\u27s values and learning algorithms. Many existing works used different learning algorithms to train ANN for getting high performance. Artificial Bee Colony (ABC) algorithm is one of the latest successfully Swarm Intelligence based technique for training Multilayer Perceptron (MLP). Normally Gbest Guided Artificial Bee Colony (GGABC) algorithm has strong exploitation process for solving mathematical problems, however the poor exploration creates problems like slow convergence and trapping in local minima. In this paper, the Improved Gbest Guided Artificial Bee Colony (IGGABC) algorithm is proposed for finding global optima. The proposed IGGABC algorithm has strong exploitation and exploration processes. The experimental results show that IGGABC algorithm performs better than that standard GGABC, BP and ABC algorithms for Boolean data classification and time-series prediction tasks