A Hybrid Weight Assignment Model for Urban Underground Space Resources Evaluation Integrated with the Weight of Time Dimension
Dixu Liu, Lixin Wu, Yang Yang
Abstract
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Dixu Liu, Lixin Wu, Yang Yang
Abstract
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The utilization of urban underground space resources (UUSR) are important approaches to effectively save land resources, improve the living environment, expand the urban space, and achieve sustainable urban development. To obtain accurate UUSR evaluation results, the weight assignment of indicators plays an important role in the evaluation process and is an indispensable part of it. Reasonable weights of indicators can greatly improve the accuracy of the final UUSR evaluation results. Neither the basic characteristics of cross-section data and time series data of UUSR evaluation indicators are taken into consideration simultaneously, nor is the combination and cross application of different weighting methods in the previous weight assignment of UUSR evaluation indicators. Considering the influence of the time dimension, the weighting method of time dimension is introduced into the UUSR evaluation. Through integrating the classical entropy weight method, which is a frequently-used weighting method of indicator dimension with the weighting method of time dimension in two different approaches by time ordered weighted averaging (TOWA) operator, the hybrid weight assignment model named entropy and time weighting model (E-TW) for UUSR evaluation is proposed. The experimental calculation results show that the UUSR evaluation results using the E-TW model are significantly better than the results using the single classical entropy weight method, which means the hybrid weight assignment model is more suitable for UUSR evaluation than the single weighting method of indicator dimension.
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The utilization of urban underground space resources (UUSR) are important approaches to effectively save land resources, improve the living environment, expand the urban space, and achieve sustainable urban development. To obtain accurate UUSR evaluation results, the weight assignment of indicators plays an important role in the evaluation process and is an indispensable part of it. Reasonable weights of indicators can greatly improve the accuracy of the final UUSR evaluation results. Neither the basic characteristics of cross-section data and time series data of UUSR evaluation indicators are taken into consideration simultaneously, nor is the combination and cross application of different weighting methods in the previous weight assignment of UUSR evaluation indicators. Considering the influence of the time dimension, the weighting method of time dimension is introduced into the UUSR evaluation. Through integrating the classical entropy weight method, which is a frequently-used weighting method of indicator dimension with the weighting method of time dimension in two different approaches by time ordered weighted averaging (TOWA) operator, the hybrid weight assignment model named entropy and time weighting model (E-TW) for UUSR evaluation is proposed. The experimental calculation results show that the UUSR evaluation results using the E-TW model are significantly better than the results using the single classical entropy weight method, which means the hybrid weight assignment model is more suitable for UUSR evaluation than the single weighting method of indicator dimension.
Key concepts: Weighting, Entropy (arrow of time), Dimension (graph theory), Computer science, Evaluation methods, Mathematical optimization, Data mining, Mathematics