Research on multidimensional evaluation and prediction modelling

Yuyang Dai; Kailin Zhang; Huanhuan Lian; Zehao Li

doi:10.1117/12.3033017

5 July 2024 Research on multidimensional evaluation and prediction modelling

Yuyang Dai, Kailin Zhang, Huanhuan Lian, Zehao Li

Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 1318469 (2024) https://doi.org/10.1117/12.3033017
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia

Abstract

This research paper presents a comprehensive methodology for multidimensional evaluation and prediction modeling, integrating advanced statistical and computational techniques. It focuses on the development of a robust model that employs least squares interpolation, normalization, entropy weighting, and the coefficient of variation method for accurate data analysis and weight calculation. By analyzing data from 20 countries across 11 indicators, the study leverages TOPSIS, Random Forest Regression, and Grey Prediction Models to offer a nuanced understanding of complex systems. The findings demonstrate the model's effectiveness in providing reliable assessments and forecasts, underscoring its potential for widespread application in various fields.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuyang Dai, Kailin Zhang, Huanhuan Lian, and Zehao Li "Research on multidimensional evaluation and prediction modelling", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 1318469 (5 July 2024); https://doi.org/10.1117/12.3033017

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