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Updated: Jun 9, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

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使用元启发算法优化SVR和CatBoost模型,以评估山体滑坡易感性

Rajendran Shobha Ajin1, Samuele Segoni2, Riccardo Fanti2

  • 1Department of Earth Sciences (DST), University of Florence (UNIFI), 50121, Florence, Italy. rajendranshobha.ajin@unifi.it.

Scientific reports
|October 22, 2024
PubMed
概括

这项研究使用机器学习回归算法优化了灰色狼和粒子群算法来增强滑坡易感性映射. 优化的CatBoost模型,特别是GWO,在预测容易发生山体滑坡的地区方面表现出卓越的性能.

关键词:
喀拉拉邦 喀拉拉邦 喀拉拉邦容易发生山体滑坡的易感性机器学习 机器学习超启发式算法 (Metaheuristic Algorithms) 是一种算法,可以通过回归是一种回归.西方高地是西方高地的一座山脉.

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