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Non-technical energy losses mostly arise from illegal use of energy. Energy distribution companies need to estimate the sources of these losses in order to take actions for reducing them. In this work we formulate a stratified sampling procedure as a non-linear restricted optimization problem, in which the variance of overall energy loss due to the(More)
In this paper we present a sampling approach to run the k-means algorithm in large data sets. We propose a genetic algorithm to guide sampling based on evaluating the fitness of each individual of the population through the k-means clustering algorithm. Although we want a partition with the lowest SSE, our algorithm tries to find the sample with the highest(More)
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