In order to improve the accuracy of line losses calculation, a novel calculation method based on the Quantum Genetic Algorithm and BP neural network has been proposed for line losses in this paper. BP neural network has been used as regression model in this paper, and the Quantum Genetic Algorithm has been used to search the weights matrix and thresholds of BP neural network. BP neural network could make prediction accurately for test lines, while fitting accurately the known results. The weaknesses of BP neural network, such as easy to trap in local minimum, low precision computing and poor generalization ability, could be overcome through the Quantum Genetic Algorithm searches the parameters of BP neural network. Finally the experiment results shows that compared with traditional methods, the calculation method based on the Quantum Genetic Algorithm and BP neural network has better performance in reducing the calculation errors.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.