چکیده مقاله
the electrical power network is the biggest system made by human in the world With increasing the demand for this type of energy, several problems have been emerged in electrical power network In this condition the new and complicated problems have been emerged in these large networks One the most important problems in these networks are the occurred faults in underground cables This study investigates the efficient approach for detecting these faults with high accuracy In this study we consider four different states in cables that are normal condition, one phase fault, two phase fault and three phase fault This study proposes the application of multilayer Perceptron MLP neural networks as a classifier MLP neural networks are powerful and efficient classifiers among other classifiers In the MLP, the parameters of number of hidden layer and number of neurons have high effect on its performance These parameters must be selected by accuracy Thus this paper proposes the application of imperialist competitive algorithm ICA for finding the optimum value of these parameters Simulation results show that the proposed intelligent method has very good performance and accuracy
کلیدواژهها
نویسندگان
Shima Sherafat1
Electrical Endangering Department, Kerman Branch, Islamic Azad University, Kerman, Iran
شیوه ارجاع
Sherafat1, Shima,1395,Optimized Artificial Neural Network Method for Underground Cables Fault Classification,3rd National Congress of Electrical and Computer Engineering of Iran,Tehran
ارائهشده در
مجموعه مقالات سومین کنفرانس سراسری نوآوری های اخیر در مهندسی برق و کامپیوتر19 شهریور 1395 · تهران