This study investigates the prediction model of compressive strength of self–compacting concrete (SCC) by utilizing soft computing techniques. The techniques consist of adaptive neuro–based fuzzy inference system (ANFIS), artificial neural network (ANN) and the hybrid of particle swarm optimization with passive congregation (PSOPC) and ANFIS called PSOPC–ANFIS. Their perf...

Churn prediction is an important task for Customer Relationship Management (CRM) in telecommunication companies. Accurate churn prediction helps CRM in planning effective strategies to retain their valuable customers. However, churn prediction is a complex and challenging task. In this paper, a hybrid churn prediction model is proposed based on combining two approaches; Neighborhood Cleaning Ru...

Artificial neural networks (ANNs) have become common data driven tools for modeling complex, nonlinear problems in science and engineering. Many previous applications have relied on gradient-based search techniques, such as the back propagation (BP) algorithm, for ANN training. Such techniques, however, are highly susceptible to premature convergence to local optima and require a trial-and-erro...

Due to the six unreasonable assumptions companioned with the Black-Scholes options pricing model (BSM), which often make the miss-pricing result because of the difference of market convention in practical. This study try to combine the BSM and extended Kalman filters-based artificial neural networks (EKF-ANN) to deal with the limitation of consideration of the influences from many unexpected re...

Discriminative methods for speech include using criteria such as MMI (maximum mutual information) and MCE (minimum classification error) during the training of HMMs (hidden Markov models). Connectionist methods bring to mind the use of ANNs (artificial neural networks). These methods are in fact closely related, sharing common solutions for tackling the complex problem of how to design MAP (max...

This paper deals with the more recent results obtained by the application of the CSLU Toolkit frame-based hybrid HMM/ANN architecture on the connected digit recognition task for the Italian language. The hybrid architecture for speaker independent recognition is described and the last obtained results are introduced in detail.

This paper proposes two hybrid connectionist structural acoustical models for robust context independent phone like and word like units for speaker-independent recognition system. Such structure combines strength of Hidden Markov Models (HMM) in modeling stochastic sequences and the non-linear classification capability of Artificial Neural Networks (ANN). Two kinds of Neural Networks (NN) are i...

Hybrid pediatric cardiac surgery is an emerging field that combines skills and techniques used by pediatric cardiac surgeons and interventional pediatric cardiologists. This article describes the emerging indications and techniques in hybrid pediatric cardiac surgery and discusses potential future applications. It focuses on peratrial and perventricular septal defect closure, intraoperative ste...