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Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models
Research article (Applied Sciences, 2020) · cited 116× · AI/ML
Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models
Summary
Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models is a scholarly article[1].
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Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models. Retrieved May 24, 2026, from https://4ort.xyz/entity/groundwater-spring-potential-mapping-using-artificial-intelligence-approach-based-on-kernel-logistic-regression-random-f
MLA“Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/groundwater-spring-potential-mapping-using-artificial-intelligence-approach-based-on-kernel-logistic-regression-random-f.
BibTeX@misc{4ortxyz_groundwater-spring-potential-mapping-using-artificial-intelligence-approach-based-on-kernel-logistic-regression-random-f_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models}}, year = {2026}, url = {https://4ort.xyz/entity/groundwater-spring-potential-mapping-using-artificial-intelligence-approach-based-on-kernel-logistic-regression-random-f}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models — https://4ort.xyz/entity/groundwater-spring-potential-mapping-using-artificial-intelligence-approach-based-on-kernel-logistic-regression-random-f (retrieved 2026-05-24)
