Analysis reveals predicted growth in global pet food demand using multi-step combined model, indicating robust market trends.
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%.
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Yuan et al. (2025) studied this question.
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