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Advanced Hybrid Information Processing. 5th EAI International Conference, ADHIP 2021, Virtual Event, October 22-24, 2021, Proceedings, Part II

Research Article

The Prediction Method of Regional Economic Development Potential Along Railway Based on Data Mining

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  • @INPROCEEDINGS{10.1007/978-3-030-94554-1_19,
        author={Hui-fang Guo and Qing-mei Cao},
        title={The Prediction Method of Regional Economic Development Potential Along Railway Based on Data Mining},
        proceedings={Advanced Hybrid Information Processing. 5th EAI International Conference, ADHIP 2021, Virtual Event, October 22-24, 2021, Proceedings, Part II},
        proceedings_a={ADHIP PART 2},
        year={2022},
        month={1},
        keywords={Data mining Economic development potential Data preprocessing Economic forecast},
        doi={10.1007/978-3-030-94554-1_19}
    }
    
  • Hui-fang Guo
    Qing-mei Cao
    Year: 2022
    The Prediction Method of Regional Economic Development Potential Along Railway Based on Data Mining
    ADHIP PART 2
    Springer
    DOI: 10.1007/978-3-030-94554-1_19
Hui-fang Guo1, Qing-mei Cao2
  • 1: School of Transportation and Municipal Engineering, Inner Mongolia Vocational and Technical College of Architecture
  • 2: Department of Computer Technology and Information Management, Vocational and Technical College of Inner Mongolia Agricultural University

Abstract

The prediction accuracy and efficiency of regional economic development potential along the railway line are poor when the common methods are used to predict the economic development potential along the railway. In view of this problem, a data mining based prediction method for regional economic development potential along the railway line is designed. Select the influencing factors of regional economic development along the railway, construct the regional economic development index system, collect index data, clean, cluster, sort and standardize the index data, extract the economic development characteristics in the pre-processing index data through data mining, input the economic development characteristics to the neural network, and output the predicted value of economic development potential after training and learning, Divide the economic development potential level. The experimental results show that the design method reduces the deviation of economic development potential prediction, shortens the prediction time, improves the accuracy and efficiency of prediction.

Keywords
Data mining Economic development potential Data preprocessing Economic forecast
Published
2022-01-18
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-94554-1_19
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