A systematic literature review and classification of knowledge discovery in traditional medicine
Abstract Introduction and Objective Despite the importance of machine learning methods
application in traditional medicine there is a no systematic literature review and a …
application in traditional medicine there is a no systematic literature review and a …
Machine learning based landslide susceptibility mapping models and GB-SAR based landslide deformation monitoring systems: Growth and evolution
Ongoing landslides have wreaked havoc in various regions across the globe. This article
presents a study of two forms of landslide monitoring viz; creation of Landslide Susceptibility …
presents a study of two forms of landslide monitoring viz; creation of Landslide Susceptibility …
Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing
W Zhang, Y He, L Wang, S Liu, X Meng - Geological Journal, 2023 - Wiley Online Library
Landslide susceptibility analysis can provide theoretical support for landslide risk
management. However, some susceptibility analyses are not sufficiently interpretable …
management. However, some susceptibility analyses are not sufficiently interpretable …
Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)
Landslides are a manifestation of slope instability causing different kinds of damage
affecting life and property. Therefore, high-performance-based landslide prediction models …
affecting life and property. Therefore, high-performance-based landslide prediction models …
Mapping and holistic design of natural hydraulic lime mortars
In recent years, the study of high hydraulicity natural hydraulic lime (NHL5) mortars has
been in the focus of many researchers, as it is considered a compatible, eco-friendly binding …
been in the focus of many researchers, as it is considered a compatible, eco-friendly binding …
Improvement of best first decision trees using bagging and dagging ensembles for flood probability mapping
Abstract Development of zoning and flood-forecasting models is essential for making
optimal management decisions before and after floods. The Komijan watershed of Markazi …
optimal management decisions before and after floods. The Komijan watershed of Markazi …
Soft computing ensemble models based on logistic regression for groundwater potential mapping
Groundwater potential maps are one of the most important tools for the management of
groundwater storage resources. In this study, we proposed four ensemble soft computing …
groundwater storage resources. In this study, we proposed four ensemble soft computing …
Landslide susceptibility mapping using different GIS-based bivariate models
Landslides are the most frequent phenomenon in the northern part of Iran, which cause
considerable financial and life damages every year. One of the most widely used …
considerable financial and life damages every year. One of the most widely used …
Decision tree based ensemble machine learning approaches for landslide susceptibility mapping
The concept of leveraging the predictive capacity of predisposing factors for landslide
susceptibility (LS) modeling has been continuously improved in recent work focusing on …
susceptibility (LS) modeling has been continuously improved in recent work focusing on …
Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility
W Chen, X Lei, R Chakrabortty, SC Pal… - Journal of …, 2021 - Elsevier
The objective of this study is to assess the gully head-cut erosion susceptibility and identify
gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area …
gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area …