The Opportunities, Limitations, and Challenges in Using Machine Learning Technologies for Humanitarian Work and Development

IF 0.7 4区数学 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Advances in Complex Systems Pub Date : 2024-03-21 DOI:10.1142/s0219525924400022

V. Sekara, Márton Karsai, Esteban Moro, Dohyung Kim, Enrique Delamonica, Manuel Cebrian, Miguel Luengo-Oroz, Rebeca Moreno Jimenez, M. García-Herranz

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将机器学习技术用于人道主义工作和发展的机遇、局限和挑战

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advances in Complex Systems 综合性期刊-数学跨学科应用

CiteScore

1.40

自引率

0.00%

发文量

121

审稿时长

6-12 weeks

期刊介绍： Advances in Complex Systems aims to provide a unique medium of communication for multidisciplinary approaches, either empirical or theoretical, to the study of complex systems. The latter are seen as systems comprised of multiple interacting components, or agents. Nonlinear feedback processes, stochastic influences, specific conditions for the supply of energy, matter, or information may lead to the emergence of new system qualities on the macroscopic scale that cannot be reduced to the dynamics of the agents. Quantitative approaches to the dynamics of complex systems have to consider a broad range of concepts, from analytical tools, statistical methods and computer simulations to distributed problem solving, learning and adaptation. This is an interdisciplinary enterprise.