Arpit Bhardwaj

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The concept of “bloat” in Genetic Programming is a well established phenomenon characterized by variable-length genomes gradually increasing in size during evolution. Bloat is basically a problem that occurs during crossover and mutation. In this paper we are proposing a special type of crossover operation named as Fitness, Elitism, Depth(More)
During the evolution of solutions using genetic programming (GP) there is generally an increase in average tree size without a corresponding increase in fitness—a phenomenon commonly referred to as bloat. The conception of " bloat " in Genetic Programming is a well naturalized phenomenon characterized by variable-length genomes gradually maturating in size(More)
In this paper, we present a new method for classification of electroencephalogram (EEG) signals using Genetic Programming (GP). The Empirical Mode Decomposition (EMD) is used to extract the features of EEG signals which served as an input for the GP. In this paper, new constructive crossover and mutation operations are also produced to improve GP. In these(More)
The human brain is a delicate mix of neurons (brain cells), electrical impulses and chemicals, known as neurotransmitters. Any damage has the potential to disrupt the workings of the brain and cause seizures. These epileptic seizures are the manifestations of epilepsy. The electroencephalograph (EEG) signals register average neuronal activity from the(More)
In this paper, we propose a new, Genetically Optimized Neural Network (GONN) algorithm, for solving classification problems. We evolve a neural network genetically to optimize its structure for classification. We introduce new crossover and mutation operations which differ from a normal Genetic programming life-cycle to reduce the destructive nature of(More)
(GP) there is generally an increase in average tree size without a corresponding increase in fit-ness—a phenomenon commonly referred to as bloat. Bloating increases time to find the best solution. Sometimes, best solution can never be obtained. We are proposing a modified crossover and point mutation operation in GP algorithm in order to reduce the problem(More)