{'fraction_non_alphanumeric': 0.013605442176870748, 'fraction_numerical': 0.0, 'mean_word_length': 4.815789473684211, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Fault Locating of Grounding Grids Based on Ant colony Optimizing Elman Neural Network

In order to improve the accuracy and efficiency of the fault location of grounding grids, a new method combing ant colony algorithm (ACA) with Elman neural network is proposed. The method contrasts the voltages of the test points when the grounding grids is normal or not. The simulation results showes that the method can save time and improve accuracy.