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The analogy between immune systems and intrusion detection systems encourage the use of artificial immune systems for anomaly detection in computer networks. This paper describes a technique of applying artificial immune system along with genetic algorithm to develop an intrusion detection system. Far from developing primary immune response, as most of the(More)
The paper introduces particle swarm optimization as a viable strategy to find numerical solution of Diophantine equation, for which there exists no general method of finding solutions. The proposed methodology uses a population of integer particles. The candidate solutions in the feasible space are optimised to have better positions through particle best(More)
The paper introduces a connectionist network approach to find numerical solutions of Diophantine equations as an attempt to address the famous Hilbert " s tenth problem. The proposed methodology uses a three layer feed forward neural network with back propagation as sequential learning procedure to find numerical solutions of a class of Diophantine(More)
The paper proposes a perceptron based artificial neural network model for diagnosing learning disability using curriculum based test conducted by special educators in medical environment. The model comprises of a single input layer with eleven units which correspond to different sections of a conventional test and one output unit. The method is not only(More)
The paper proposes a novel idea of finding consensus of biological sequences using sequence evolution. It involves application of meta-heuristic optimization technique called Differential Evolution for the creation of a population of evolved sequences. This evolved population of sequences is used to find consensus using Position Frequency Matrix. DNA(More)
The paper proposes a methodology to find numerical solutions of Diophantine equations using steepest ascent version of Hill Climbing. It represents possible solutions of a Diophantine equation using tree and adopts a novel mechanism to generate successors. The proposed heuristic function makes the process of finding numerical solution a minimization(More)
We propose an optimized parameter set for protein secondary structure prediction using three-layer feed forward back propagation neural network. The methodology uses four parameters viz. encoding scheme, window size, number of neurons in the hidden layer and type of learning algorithm. The input layer of the network consists of neurons changing from 3 to(More)
The paper attempts to find numerical solutions of Diophantine equations, a challenging problem as there are no general methods to find solutions of such equations. It uses the metaphor of foraging habits of real ants. The ant colony optimization based procedure starts with randomly assigned locations to a fixed number of artificial ants. Depending upon the(More)
The paper proposes a methodology for predicting 3D structure of proteins using genetic algorithm. It uses genomic sequences for the experimental purpose. In order to give a complete representation of known and unknown genomic sequences of similar kind, the known collection of sequences are made to evolve. The evolved sequences are subjected to offer(More)