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Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping

Research article (Geocarto International, 2021) · cited 36× · AI/ML
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Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping

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Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping is a scholarly article[1].

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  • Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping. Retrieved May 24, 2026, from https://4ort.xyz/entity/combining-logistic-regression-based-hybrid-optimized-machine-learning-algorithms-with-sensitivity-analysis-to-achieve-ro
MLA “Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/combining-logistic-regression-based-hybrid-optimized-machine-learning-algorithms-with-sensitivity-analysis-to-achieve-ro.
BibTeX @misc{4ortxyz_combining-logistic-regression-based-hybrid-optimized-machine-learning-algorithms-with-sensitivity-analysis-to-achieve-ro_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping}}, year = {2026}, url = {https://4ort.xyz/entity/combining-logistic-regression-based-hybrid-optimized-machine-learning-algorithms-with-sensitivity-analysis-to-achieve-ro}, note = {Accessed: 2026-05-24}}
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