Innovations in Bio-inspired Computing and Applications

This volume of Advances in Intelligent Systems and Computing contains accepted papers presented at IBICA2013, the 4th International Conference on Innovations in Bio-inspired Computing and Applications. The aim of IBICA 2013 was to provide a platform for world research leaders and practitioners, to discuss the full spectrum of current theoretical developments, emerging technologies, and innovative applications of Bio-inspired Computing. Bio-inspired Computing is currently one of the most exciting research areas, and it is continuously demonstrating exceptional strength in solving complex real life problems. The main driving force of the conference is to further explore the intriguing potential of Bio-inspired Computing. IBICA 2013 was held in Ostrava, Czech Republic and hosted by the VSB - Technical University of Ostrava.

Presents current theoretical developments, emerging technologies, and innovative applications of Bio-inspired Computing Proceedings of the 4th International Conference on Innovations in Bio-Inspired Computing and Applications IBICA 2013, held in Ostrava, Czech Republic Written by leading experts in the field

Autorentext
Dr. Ajith Abraham is Director of the Machine Intelligence Research (MIR) Labs, a global network of research laboratories with headquarters near Seattle, WA, USA. He is an author/co-author of more than 750 scientific publications. He is founding Chair of the International Conference of Computational Aspects of Social Networks (CASoN), Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (since 2008), and a Distinguished Lecturer of the IEEE Computer Society representing Europe (since 2011).

Inhalt
From the Contents: Power output models of Ordinary Differential Equations by Polynomial and Recurrent Neural Networks.- An Experimental Analysis of Reservoir Parameters of the Echo State Queuing Network model.- Measuring Phenotypic Structural Complexity of Artificial Cellular Organisms.- Fuzzy Rules and SVM Approach to the Estimation of Use Case Parameters.