{'fraction_non_alphanumeric': 0.01661631419939577, 'fraction_numerical': 0.011329305135951661, 'mean_word_length': 4.915178571428571, '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}}
Maximum entropy for comprehensive evaluation of region agriculture drought

Comprehensive evaluation is an important part of systems engineering but its evaluation results remains uncertainty. The chief aim of this paper is to develop a novel model which could be used to obtain the drought degree reasonably and accurately. It requires a great deal of further research effort in the systems evaluation because of the uncertainty which is regarded in terms of information entropy. A maximum entropy evaluation model based on projection pursuit (MEPP for short) is mentioned and accelerating genetic algorithm (AGA) is applied for the optimization of the projection index function and the projection - drought degree curve respectively. Case study results show that the absolute error of the model is reached to 83.33% in the range of [0, 0.2]. The drought index weight distribution is in agreement with the views expressed by analytic hierarchy process method. There is reason therefore to consider the index weights and drought degree evaluation model as quite reliable. The drought degree is 4.596 which have a good behavior to the variable fuzzy set methods 4.302. The result of MEPP model indicates that the case study region has a badly drought and MEPP model is of great importance for the drought disaster management.