Predicting Food Distribution with Underlying Factors for a Hunger Relief Organization

被引：0

作者：

Odubela, Kehinde ^{[1
]}

Ivuawuogu, Henry ^{[1
]}

Jiang, Steven ^{[1
]}

Davis, Lauren ^{[1
]}

机构：

[1] North Carolina A&T State Univ, Dept Ind & Syst Engn, Greensboro, NC USA

来源：

JOURNAL OF HUNGER & ENVIRONMENTAL NUTRITION | 2025年 / 20卷 / 01期

关键词：

Food distribution; forecasting; underlying factors; visual analytics; hunger relief; TIME-SERIES; INSECURITY; DEMAND; DETERMINANTS;

D O I：

10.1080/19320248.2024.2328353

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

Hunger relief organizations often estimate food demand using food distribution data. Leveraging Visual Analytics (VA) and historical data, we examine how underlying factors like unemployment, poverty rate, and median household income affect forecasts for aid recipients' food demand. Our study reveals that incorporating these factors enhances forecast accuracy. Visual Analytics empowers decision-makers to integrate field knowledge with computational insights, enabling more informed decisions. This innovative approach presents a valuable tool for charitable organizations to strategically improve forecasting precision in the dynamic landscape of hunger relief.

引用

页码：43 / 59

页数：17

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