{'fraction_non_alphanumeric': 0.012897678417884782, 'fraction_numerical': 0.0025795356835769563, 'mean_word_length': 5.887573964497041, '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}}
Fast Reconstruction and Optimization of 3D Temperature Field Based-on Kriging Interpolation

With the widespread application of the Internet of Things technology in the industrial field, the research on 3D temperature field reconstruction technology has also received widespread attention. A fast reconstruction algorithm of 3D temperature field based on Kriging interpolation is proposed. Through CFD software simulation, the three-dimensional space simulation temperature field and the temperature data of the sensor node are obtained. According to the spatial position and temperature information about the sensor node, the Kriging interpolation method is used to realize the rapid reconstruction of the three-dimensional temperature field. In order to improve the overall accuracy of the reconstructed temperature field, an improved genetic algorithm is used to optimize the parameters of the Kriging interpolation method. The results show that the three-dimensional temperature field can be quickly reconstructed based on the Kriging interpolation method, and the optimized reconstructed temperature field can accurately reflect the temperature change trend.