Research On Intelligent Algorithm For Low Visibility Prediction And Airport Delay Mode

In the process of the generation and development of the air transport industry,the safety and punctuality of flights have always been the focus of attention of airlines,airports,and control units.Therefore,both domestic and foreign experts and scholars as well as relevant technical personnel in the industry are very concerned about the relevant content.With the vigorous development of China’s aviation industry and the catch-up of foreign related industries,the pressure of flights safety and on-time rates are also growing.Low visibility weather phenomena as an important factor affecting flight safety and punctuality rates has always been Considered very much.Therefore,it is an important research topic and direction to make accurate predictions on the future visibility of the airport and to give the transition rules of the airport’s potential operation mode according to the change of visibility.The main goal of this paper is to use historical data,combined with the relevant intelligent technology of data mining to complete the two aspects of visibility prediction and airport flight delay mode analysis under low visibility.hoping to make a certain contribution to the safety and efficiency of the civil aviation industry and to save the public resources of the society.A detailed overview of the analysis of visibility and airport delay patterns is as follows:In terms of visibility prediction,the classification of the operational rules of the airport was first made based on the operational standards of specific airports and related research at home and abroad.Then,through the correlation test,the meteorological elements most closely related to the change of visibility are found.Based on the collection and collation of a large number of historical METAR messages at a specific airport,a meteorological element history database was established.Based on this,the classical algorithm of data mining was used to build a visibilityForecast model which construct with significant correlation meteorological elements as input variables and visibility levels as output variables.Finally,the actual historical visibility and meteorological data of Shuangliu Airport were used to verify the model,and a model to achieve the expected accuracy and its related parameters were obtained.Achieve the Accurate prediction of visibility levels.In the analysis of airport flight delay mode,the definitions and statistical methods of flight delay related terms are compared,the characteristic distribution of flight delays at specific airports is given,and the special law of airport operation under low visibility conditions is analyzed.The most important thing is to use the same data mining algorithm based on the collection and collation of a large number of historical data of specific airports to establish the airport flight data flow database.The prediction method of airport flight delay time is given,and the complete method is established by MATLAB software.The model passed the analysis and verification of accuracy.The research in this paper avoids the traditional way of predicting visibility and making flight delay correlation by establishing mathematical formulas and solving complex functions.The related algorithms of historical data mining are more convenient to achieve related purposes.This paper presents an application example of meteorological prediction and airport historical data analysis,and proves the feasibility and applicability of the data mining method in related fields.Use the model in this paper to predict changes in visibility at specific airports and trends in flight delay duration before making a flight plan or conducting civil aviation-related activities.It has made practical and practical contributions to the development of plans,safety,efficiency,and efficiency for airlines,air traffic control units,airports,etc.