edited by Satchidananda Dehuri (Fakir Mohan University, India), Susmita Ghosh (Jadavpur University, India), & Sung-Bae Cho (Yonsei University, South Korea)

This book provides a new forum for the dissemination of knowledge in both theoretical and applied research on swarm intelligence (SI) and artificial neural network (ANN). It accelerates interaction between the two bodies of knowledge and fosters a unified development in the next generation of computational model for machine learning.

To the best of our knowledge, the integration of SI and ANN is the first attempt to integrate various aspects of both the independent research area into a single volume.

• Swarm Intelligence and Neural Networks (S Dehuri, S-B Cho & S Ghosh)
• Neural Network and Swarm Intelligence for Data Mining (S N Omkar & J Senthilnath)
• Multi-Objective Ant Colony Optimization: A Toxonomy and Review of Approaches (G Leguizamón & C A Coello Coello)
• Recurrent Neural Networks with Discountinous Activation Functions for Convex Optimization (Q Liu & J Wang)
• Automated Power Quality Disturbance Classification Using Evolvable Neural Network (B K Panigrahi, A Mohapatra, P Ray & S Das)
• Condition Monitoring and Fault Diagnosis Using Intelligent Techniques (S K Yadav, V Singh & P K Kalra)
• Hue-Preserving Color Image Enhancement Using Particle Swarm Optimzation (A Ghosh & A Gorai)
• Efficient Classifier Design with Hybrid Polynomial Neural Network (B B Misra, P K Dash & G Panda)
• Efficient Predicition of Retail Sales Using Differential Evolution Based Adaptive Model (R Majhi, B Majhi & G Panda)
• Some Studies on Particle Swarm Optimization for Single and Multi-Objective Problems (M Das & S Dehuri)
• Coherent Biclusters of Microarray Data by Imitating the Ecosystem: An Ant Colony Algorithmic Approach (D Mishra, A K Rath & M Acharya)