Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 623-628.doi: 10.11896/jsjkx.210200021

• Interdiscipline & Application • Previous Articles     Next Articles

Research of ATC Simulator Training Values Independence Based on Pearson Correlation Coefficient and Study of Data Visualization Based on Factor Analysis

LUO Jing-jing1, TANG Wei-zhen2, DING Ji-ting3   

  1. 1 College of Air Traffic Management,Civil Aviation Flight University of China,Guanghan,Sichuan 618307,China
    2 CAAC Academy,Civil Aviation Flight University of China,Guanghan,Sichuan 618307,China
    3 East China Regional Air Traffic Management Bureau,Shanghai 200335,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:LUO Jing-jing,born in 1990,postgraduate,probationer.Her main research interests include air traffic control training data visualization and flight procedure design.
  • Supported by:
    Construction of Training System for Air Traffic Controllers in Medium and Small Airports of Civil Aviation Based on Complexity of Security(14002600100020J124) and Construction of Training Curriculum System for CAAC Supervisors(2146999).

PDF (PC)

503

Abstract: In order to solve the problem of repeated scoring on training indicators of ATC simulation,the indicators' relationship is studied based on Pearson correlation coefficient,and the significance level is used to test and the scoring algorithm is modified.This paper extracts 4 162 items from the cloud small program scoring database,taks factor analysis theory as the research me-thod,uses principal component analysis method to solve the factor load matrix,and uses orthogonal rotation method to expand the load value,reasonably explains the common factors,establishes the quality and ability model of the control students,and realizs data visualization.The results show that the score of the indicators after de-correlation show a downward trend,and the fluctuation is basically the same as that of the original evaluation score.Some indicator descriptions can be changed according to the correlation and independent values.The ability value after factor analysis can clearly reflect the ability of students through radar chart,showing the quality and ability of students,and is also convenient for scientific control of post allocation,which is an effective application of data visualization.

Key words: Air traffic control simulator training, Data visualization, Factor analysis, Pearson correlation coefficient, Retrieval

CLC Number: 

  • V335
[1] BELLO S A,OYEDELE L O,AKINADE O O,et al.Cloud computing in construction industry:Use cases benefits and challenges[J].Automation in Construction,2021,122:103441.
[2] LI X G.The development of designated driving application based on Android platform and Ali cloud sever[C]//2016 2nd Workshop on Advanced Research and Technology in Industry Applications.2016:633-636.
[3] KUMAR N,KUMAR G,KUMAR S R.Big data analytics application for sustainable manufacturing operations:analysis of strategic factors[J].Clean Technologies and Environmental Policy,2021(23):1-25.
[4] CHOI D,LEE H,BOK K,et al.Design and implementation of an academic expert system through big data analysis[J].The Journal of Supercomputing,2021(78):1-25.
[5] LIANG J Y,FENG C J,SONG P.A Survey on Correlation Analysis of Big Data[J].Chinese JournaL of Computers,2016,39(1):1-18.
[6] JIN L,LI Y.Discrimination of Several Correlation Coefficients and Their Implementation in R Software[J].Statistics & Information Forum,2019,34(4):3-11.
[7] SHI S,LIU W Y.Factor Analysis Method Research of Evaluation Index Connection[J].Mathematics in Economics,2010,27(2):23-27.
[8] XU W P.Design and Implementation of Data Visualization System Architecture[D].Beijing:Beijing Jiaotong University,2015.
[9] LEE A,KIM S E,SUH K D.Estimation of Stability Number of Rock Armor Using Artificial Neural Network Combined with Principal Component Analysis[J].Procedia Engineering,2015,116:149-154.
[10] LIU Y,YANG Q W,YAO Y H,et al.Current Situation and Existing Problems of Factor Analysis Method[J].Journal of Finance and Accounting,2019,7(6):192-199.
[11] WANG Y,DENG X D.Empirical Study on the PerformanceEvaluation of Agricultural Products Supply Chain Based on Factor Analysis[J].China Business and Market,2015,3:10-16.
[12] MOSLEM I,DIANAT I,OLFAT I,et al.Selection of elite F3 lines in cucumber using factor analysis method[J].International Journal of Vegetable Science,2020,26(5):498-505.
[13] WANG M M.Research on PTC Cable Materials Based on Principal Component Analysis and Quantitative Correspondence Factor Analysis Method in Big Data Technology[C]//IOP Conference Series:Materials Science and Engineering,2019,493(1):012048.
[14] WEN R Y,WANG H Y.Evaluation of Air Traffic Complexity Based on Factor Analysis and K-means Clustering[J].Journal of Taiyuan University of Technology,2016,47(3):384-388.
[15] WEIDE A C.A Beauducel.Varimax Rotation Based on Gradient Projection is a Feasible Alternative to SPSS[J].Frontiers in Psychology,2019,00645.
[16] ALAVI S M,EBRAHIMI A,POURMOURDININ E,et al.Identifying and Classifying the FactorsAffecting Fast Food Store SelectionUsing Factor Analysis Method[J].Journal of Business Management,2018,9(4):827-854.
[17] YE Y.Study on the Evaluation Index System of Guangdong's All-for-One Tourism Destination Competitiveness Based on Factor and Cluster Analysis[J].Open Journal of Social sciences,2019,7(3):418-428.
[1] NIE Xiu-shan, PAN Jia-nan, TAN Zhi-fang, LIU Xin-fang, GUO Jie, YIN Yi-long. Overview of Natural Language Video Localization [J]. Computer Science, 2022, 49(9): 111-122.
[2] ZHU Cheng-zhang, HUANG Jia-er, XIAO Ya-long, WANG Han, ZOU Bei-ji. Deep Hash Retrieval Algorithm for Medical Images Based on Attention Mechanism [J]. Computer Science, 2022, 49(8): 113-119.
[3] CHEN Hui-pin, WANG Kun, YANG Heng, ZHENG Zhi-jie. Visual Analysis of Multiple Probability Features of Bluetongue Virus Genome Sequence [J]. Computer Science, 2022, 49(6A): 27-31.
[4] YU Jia-qi, KANG Xiao-dong, BAI Cheng-cheng, LIU Han-qing. New Text Retrieval Model of Chinese Electronic Medical Records [J]. Computer Science, 2022, 49(6A): 32-38.
[5] HAN Hong-qi, RAN Ya-xin, ZHANG Yun-liang, GUI Jie, GAO Xiong, YI Meng-lin. Study on Cross-media Information Retrieval Based on Common Subspace Classification Learning [J]. Computer Science, 2022, 49(5): 33-42.
[6] ZHANG Xin-feng, SONG Bo. A Person Re-identification Method Based on Improved Triple Loss and Feature Fusion [J]. Computer Science, 2021, 48(9): 146-152.
[7] LIU Li-bo, GOU Ting-ting. Cross-modal Retrieval Combining Deep Canonical Correlation Analysis and Adversarial Learning [J]. Computer Science, 2021, 48(9): 200-207.
[8] FENG Xia, HU Zhi-yi, LIU Cai-hua. Survey of Research Progress on Cross-modal Retrieval [J]. Computer Science, 2021, 48(8): 13-23.
[9] YANG Hui-min, MA Ting-huai. Compound Conversation Model Combining Retrieval and Generation [J]. Computer Science, 2021, 48(8): 234-239.
[10] WANG Chun-jing, LIU Li, TAN Yan-yan, ZHANG Hua-xiang. Image Retrieval Method Based on Fuzzy Color Features and Fuzzy Smiliarity [J]. Computer Science, 2021, 48(8): 191-199.
[11] SUN Sheng-zi, GUO Bing-hui , YANG Xiao-bo. Embedding Consensus Autoencoder for Cross-modal Semantic Analysis [J]. Computer Science, 2021, 48(7): 93-98.
[12] FENG Jiao, LU Chang-yu. Cross Media Retrieval Method Based on Residual Attention Network [J]. Computer Science, 2021, 48(6A): 122-126.
[13] YU Sheng, LI Bin, SUN Xiao-bing, BO Li-li, ZHOU Cheng. Approach for Knowledge-driven Similar Bug Report Recommendation [J]. Computer Science, 2021, 48(5): 91-98.
[14] E Hai-hong, ZHANG Tian-yu, SONG Mei-na. Web-based Data Visualization Chart Rendering Optimization Method [J]. Computer Science, 2021, 48(3): 119-123.
[15] WANG Xiao-fei, ZHOU Chao, LIU Li-gang. Lightweight Image Retrieval System Based on Feature Clustering [J]. Computer Science, 2021, 48(2): 148-152.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.