{'fraction_non_alphanumeric': 0.016423357664233577, 'fraction_numerical': 0.0, 'mean_word_length': 5.491124260355029, '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}}
Big Data Platform of Air Traffic Management

in recent years, air traffic management bureaus have successively built air traffic control systems, airport surface monitoring system, electronic flight data system, digital clearance system, collaborative decision-making system, traffic management system, etc. These systems have accumulated a huge amount of air traffic control data that has potential value. Analyzing the data of air traffic control by using machine learning algorithms can provide a guarantee for safe production and enable the air traffic control system to provide services more safely and efficiently. Therefore, the establishment of aviation big data storage and analysis platform has become an important task of air traffic management. This paper design a big data platform which stores the data output by each system used by the air traffic management system. This paper introduces the connection of data sources and the structure of the big data platform. The platform provides decision making including flight delay analysis, operational efficiency, and experience routes.