"[This book] is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem...

This paper presents a framework to help educators and designers improve their design, experiences and management of computer supported collaborative learning (CSCL). With increasing interest in this subject, a number of aspects (dimensions) related to both learning and the use of technology...

Since stock markets are volatile, dynamic and complicated, forecasting stock market return is considered as a challenging task. Nevertheless, researchers have developed various linear and non linear methods for effective forecasting. Among these neural networks are most suitable for forecasting...

Absent regulatory requirements, 64% of small private commercial banks voluntarily procured an independent audit in our dataset. Hence, it can be argued that an independent audit may have a perceived value. In our study, we examine whether the decision to procure an audit is systematic. First, we...

This paper presents a computational approach for predicting the S&P CNX Nifty 50 Index. A neural network based model has been used in predicting the direction of the movement of the closing value trend of the index by predicting the seven day simple moving average value change after seven days....

We examine various and different approaches for the prediction of economic crisis periods of US economy. We examine the traditional econometric discrete choice Logit and Probit models then a feed-forward neural network (FFNN) model and finally we apply an Adaptive Neuro-Fuzzy Inference System...

The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology...

The two-objective differential evolution with Pareto-optimal set, which is researched in this paper. Firstly, it is found that there are some redundant computations in the classic multi-objective evolutionary algorithm, such as the NSGA-II. Then, based on the concept of Pareto-optimal set, the...

To achieve reliable system intelligence outstanding results, current computational system modeling and simulation community has to face and to solve two orders of modeling limitations at least. As a solution, the author proposes an exponential, pre-spatial arithmetic scheme (“all-powerful...