Leader: G Karmakar
Not offered in 2005.
Synopsis: Introduction to neural networks and their applications. Simple neural networks for pattern classification. Multilayered neural networks (backprogration and its variations for faster training and adaptive architectures). Unsupervised neural networks (Kohonen Self Organising Maps). Case studies. Introduction to evolutionary computation and its possible applications. Genetic algorithms. Modeling and simulation with genetic algorithm in economic systems. Genetic programming and design issues of evolutionary algorithms. Hands-on experience to solve real-world business and economic problems using available software tools.
Assessment: Assignments: 60% + Examination (2 hours): 40%
Contact Hours: 4 hours per week