{'fraction_non_alphanumeric': 0.016556291390728478, 'fraction_numerical': 0.0033112582781456954, 'mean_word_length': 5.302083333333333, '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}}
Load Forecasting for Electrical Power System Based on BP Neural Network

Load forecasting model which synthetically considers every kind of impact factor is created in this paper. The input load data and temperature are normalized, and weather condition variable is quantitatively transacted. The applications of the BP (Back-Propagation Network) neural network algorithm and the neural network toolbox in MATLAB 7.0 software achieve load forecasting. The experimental result shows that the prediction of neural network model is good, and the error can meet the basic requirement of the practical system.