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Analysis on the Development of the Pet Industry Based on Multi-Step Combined Model

Year: 2025

Type: article

Abstract: The multi-step combined model integrates multiple sub-models in sequential steps based on the internal correlations among factors. This paper formulates sub-problems for relevant issues, establishes corresponding sub-models, and ultimately solves them through integration. Through multiple linear regression, equations were derived for each outcome variables. A multi-order differential regression equation was applied to historical total scores. Combining predictions from direct, first-order difference, second-order difference regression, a weighted average (0.6,0.3,0.1) was calculated. The global pet food demand scores were predicted to be 33445.32, 33445.32, and 34157.15, with annual growth rates of 0.757%, 0.941%, and 1.176%.

Source: Mathematical Modeling and Algorithm Application

DOI: 10.54097/tnzzh231

Authors: Junpeng Yuan, Jiaqi Zhang, Yuexin Sun, Lin Zhang, Dang Gan

Institution: Guangzhou University

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Zero hunger

Open Access status: hybrid

OpenAlex ID: W4415004710

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