{'fraction_non_alphanumeric': 0.015495867768595042, 'fraction_numerical': 0.0, 'mean_word_length': 5.09433962264151, '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}}
Improvement of relational two-stage DEA model under fuzzy chance constraints

Two-stage chain system widely exists in the production and management processes. It is has a great research meaning of its efficiency evaluation. This paper improves the relational two-stage DEA model by fuzzy chance constraints, constructs a relational two-stage DEA model that can deal with the fuzzy uncertainty and suit to small samples, and transforms the model into a certainty equivalent linear model to simplify the programming solving. The results of this study can be applied to many chain system efficiency evaluation researches to deal with the fuzziness of the complex economic system. Besides, the mistaken of efficiency overestimated because of the insufficiency of sample data can be fixed by the improved model. Thereby, the accuracy and precision of efficiency evaluation can be enhanced and improved. An example of commercial banks is given to show the model application.