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解读贝叶斯优化深度学习模型，加强水土流失易发性预测和管理：印度东部案例研究

IF 3.3 4区 地球科学 Q2 ENVIRONMENTAL SCIENCES
Geocarto International Pub Date : 2024-06-19 DOI:10.1080/10106049.2024.2367611
Meshel Alkahtani, Javed Mallick, Saeed Alqadhi, Md Nawaj Sarif, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo
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引用次数: 0

摘要

水土流失对可持续土地管理和农业生产力构成重大威胁。要解决这一问题，需要先进的预测模型，以准确识别水土流失区域。
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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Interpretation of Bayesian-optimized deep learning models for enhancing soil erosion susceptibility prediction and management: a case study of Eastern India
Soil erosion poses a significant threat to sustainable land management and agricultural productivity. Addressing this issue requires advanced predictive models that can accurately identify areas at...
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来源期刊
Geocarto International
Geocarto International ENVIRONMENTAL SCIENCES-GEOSCIENCES, MULTIDISCIPLINARY
CiteScore
6.30
自引率
13.20%
发文量
407
审稿时长
>12 weeks
期刊介绍： Geocarto International is a professional academic journal serving the world-wide scientific and user community in the fields of remote sensing, GIS, geoscience and environmental sciences. The journal is designed: to promote multidisciplinary research in and application of remote sensing and GIS in geosciences and environmental sciences; to enhance international exchange of information on new developments and applications in the field of remote sensing and GIS and related disciplines; to foster interest in and understanding of science and applications on remote sensing and GIS technologies; and to encourage the publication of timely papers and research results on remote sensing and GIS applications in geosciences and environmental sciences from the world-wide science community. The journal welcomes contributions on the following: precise, illustrated papers on new developments, technologies and applications of remote sensing; research results in remote sensing, GISciences and related disciplines; Reports on new and innovative applications and projects in these areas; and assessment and evaluation of new remote sensing and GIS equipment, software and hardware.
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