This project focus on the problem of data clustering, where the similarity between instances are measured by Euclidean distance metric. Here we include the case where the data dimension, the number of clusters and the size of data set could be very large. Genetic algorithm is used due to its capability to capture the global optimality, leading to a promising empirical performance in the given e...

no unique method has been so far specified for determining the number of neurons in hidden layers of multi-layer perceptron (mlp) neural networks used for prediction. the present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. the data used in the present research for prediction are consumption data of water...