Engineering Evolutionary Intelligent Systems

- Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews

- Genetically Optimized Hybrid Fuzzy Neural Networks: Analysis and Design of Rule-based Multi-layer Perceptron Architectures

- Genetically Optimized Self-organizing Neural Networks Based on Polynomial and Fuzzy Polynomial Neurons: Analysis and Design

- Evolution of Inductive Self-organizing Networks

- Recursive Pattern based Hybrid Supervised Training

- Enhancing Recursive Supervised Learning Using Clustering and Combinatorial Optimization (RSL-CC)

- Evolutionary Approaches to Rule Extraction from Neural Networks

- Cluster-wise Design of Takagi and Sugeno Approach of Fuzzy Logic Controller

- Evolutionary Fuzzy Modelling for Drug Resistant HIV-1 Treatment Optimization

- A New Genetic Approach for Neural Network Design

- A Grammatical Genetic Programming Representation for Radial Basis Function Networks

- A Neural-Genetic Technique for Coastal Engineering: Determining Wave-induced Seabed Liquefaction Depth

- On the Design of Large-scale Cellular Mobile Networks Using Multi-population Memetic Algorithms

- A Hybrid Cellular Genetic Algorithm for the Capacitated Vehicle Routing Problem

- Particle Swarm Optimization with Mutation for High Dimensional Problems

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).

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