Analysis on the Evolution of Ecological Transformation of Consumption Patterns to Help Realize the Evolution of Realize Low-Carbon City Construction Taking into Account Similarity Knowledge Recognition and Matching Algorithms

Xudong Li, Lan Tao, Xiaoqian Zhou and Xiantao Jiang

Mathematical Problems in Engineering, 2022, vol. 2022, 1-10

Abstract: For the purpose of addressing or eliminating the influence of low-carbon city construction effectively, it is crucial to carry out qualitative analysis on the evolutionary process in the construction of the low-carbon city based on the similarity knowledge identification matching algorithm. The ecological transformation of consumption patterns is implemented to facilitate the distribution of resources in the evolution analysis of the low-carbon city construction. The regularity and innovation during the process of building low-carbon cities is effectively summarized. On the premises of fully grasping the principles of low-carbon city development and related policy protection, a suitable low-carbon city development model is found. In accordance with the features of separate transmission, the model is recovered by using the characteristics in the total deviation observed, and the constrained nonoptimizable case is replaced with the computation case of constrained separate line segment with the relaxation factor. Finally, the results of the practical case analysis suggest that the image processing method supported by the ecological transformation of consumption patterns applied in this paper uses the relatively advanced computer network technology and 3D visualization model construction based on the establishment of a low-carbon city construction model according to the effective analysis of geological surveys and data, which can provide theoretical support for the subsequent construction of low-carbon cities.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:9914086

DOI: 10.1155/2022/9914086

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