GIS based hybrid computational approaches for flash flood susceptibility assessment
Flash floods are one of the most devastating natural hazards; they occur within a catchment
(region) where the response time of the drainage basin is short. Identification of probable …
(region) where the response time of the drainage basin is short. Identification of probable …
[HTML][HTML] A comparison of performance of SWAT and machine learning models for predicting sediment load in a forested Basin, Northern Spain
In water bodies, sediment transport is a potential source of numerous negative effects on
water resource projects and can damage environmental services. Two machine learning …
water resource projects and can damage environmental services. Two machine learning …
Combination of data-driven models and best subset regression for predicting the standardized precipitation index (SPI) at the Upper Godavari Basin in India
Standardized precipitation index prediction and monitoring are essential to mitigating the
effect of drought actions on precision farming, environments, climate-smart agriculture, and …
effect of drought actions on precision farming, environments, climate-smart agriculture, and …
Daily water level prediction of Zrebar Lake (Iran): a comparison between M5P, random forest, random tree and reduced error pruning trees algorithms
Zrebar Lake is one of the largest freshwater lakes in Iran and it plays an important role in the
ecosystem of the environment, while its desiccation has a negative impact on the …
ecosystem of the environment, while its desiccation has a negative impact on the …
A comprehensive study of various regressions and deep learning approaches for the prediction of friction factor in mobile bed channels
A fundamental issue in the hydraulics of movable bed channels is the measurement of
friction factor (λ), which represents the head loss because of hydraulic resistance. The …
friction factor (λ), which represents the head loss because of hydraulic resistance. The …
Combining logistic regression-based hybrid optimized machine learning algorithms with sensitivity analysis to achieve robust landslide susceptibility mapping
Landslides and other catastrophic environmental disasters pose a significant danger to
environmental, infrastructure, and people's lives. This research aimed to construct four …
environmental, infrastructure, and people's lives. This research aimed to construct four …
Proposing receiver operating characteristic-based sensitivity analysis with introducing swarm optimized ensemble learning algorithms for groundwater potentiality …
Groundwater scarcity is one of the most concerning issues in arid and semi-arid regions. In
this study, we develop and validate a novel artificial intelligence that is a coupling of five …
this study, we develop and validate a novel artificial intelligence that is a coupling of five …
Predicting total sediment load transport in rivers using regression techniques, extreme learning and deep learning models
Total sediment load exerts control over the river channel morphology. Due to the non-linear
and multi-dimensional behavior of the variables impacting total sediment load, the prediction …
and multi-dimensional behavior of the variables impacting total sediment load, the prediction …
Drought forecasting using new advanced ensemble-based models of reduced error pruning tree
M Shahdad, B Saber - Acta Geophysica, 2022 - Springer
The present study investigates the prediction accuracy of standalone Reduced Error Pruning
Tree model and its integration with Bagging (BA), Dagging (DA), Additive Regression (AR) …
Tree model and its integration with Bagging (BA), Dagging (DA), Additive Regression (AR) …
Assessment of groundwater potential and determination of influencing factors using remote sensing and machine learning algorithms: A study of Nainital district of …
Exponential increase in population, rapid urbanization and industrialization have increased
the demand of water globally. Groundwater is an important resource in hilly and …
the demand of water globally. Groundwater is an important resource in hilly and …