31 hasil untuk "Alireza Arabameri"
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Artikel Jurnal
Modeling groundwater potential using novel GIS-based machine-learning ensemble techniques
Study region: The present study has been carried out in the Tabriz River basin (5397 km2) in north-western Iran. Elevations vary from 1274 to 3678 m above sea level, and slope angles range from 0 to 150.9 %. The average annual minimum and maximum temperatures are 2 °C and 12 °C, respectively. The…
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Novel Ensemble Approaches of Machine Learning Techniques in Modeling the Gully Erosion Susceptibility
Gully erosion has become one of the major environmental issues, due to the severity of its impact in many parts of the world. Gully erosion directly and indirectly affects agriculture and infrastructural development. The Golestan Dam basin, where soil erosion and degradation are very severe…
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Ensemble of Machine-Learning Methods for Predicting Gully Erosion Susceptibility
Gully formation through water-induced soil erosion and related to devastating land degradation is often a quasi-normal threat to human life, as it is responsible for huge loss of surface soil. Therefore, gully erosion susceptibility (GES) mapping is necessary in order to reduce the adverse effect…
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Novel Ensemble of Multivariate Adaptive Regression Spline with Spatial Logistic Regression and Boosted Regression Tree for Gully Erosion Susceptibility
The extreme form of land degradation through different forms of erosion is one of the major problems in sub-tropical monsoon dominated region. The formation and development of gullies is the dominant form or active process of erosion in this region. So, identification of erosion prone regions is…
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Novel Machine Learning Approaches for Modelling the Gully Erosion Susceptibility
The extreme form of land degradation caused by the formation of gullies is a major challenge for the sustainability of land resources. This problem is more vulnerable in the arid and semi-arid environment and associated damage to agriculture and allied economic activities. Appropriate modeling of…
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Artikel Jurnal
Prediction of gully erosion susceptibility mapping using novel ensemble machine learning algorithms
Spatial modelling of gully erosion at regional level is very relevant for local authorities to establish successful counter-measures and to change land-use planning. This work is exploring and researching the potential of a genetic algorithm-extreme gradient boosting (GE-XGBoost) hybrid computer…
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Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors
There is an evident increase in the importance that remote sensing sensors play in the monitoring and evaluation of natural hazards susceptibility and risk. The present study aims to assess the flash-flood potential values, in a small catchment from Romania, using information provided remote…
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Artikel Jurnal Teks lengkap
Correction: Costache et al. Flash-Flood Potential Mapping Using Deep Learning, Alternating Decision Trees and Data Provided by Remote Sensing Sensors. Sensors 2021, 21, 280
Following publication, concerns were raised regarding the relevance of a few references in this publication [...]
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Artikel Jurnal
Performance Evaluation of GIS-Based Novel Ensemble Approaches for Land Subsidence Susceptibility Mapping
The optimal prediction of land subsidence (LS) is very much difficult because of limitations in proper monitoring techniques, field-base surveys and knowledge related to functioning and behavior of LS. Thus, due to the lack of LS susceptibility maps it is almost impossible to identify LS prone…
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Artikel Jurnal
Soil erosion and sediment yield estimation in a tropical monsoon dominated river basin using GIS-based models
The increasing soil erosion (SE) and the associated problems for society, economy, and environment sparked a lot of interest in estimating and mapping SE at different basin scales. The estimation of SE exhibits that SE ranges from 10 to 50 t ha−1 yr−1, with a mean SE of 20 t ha−1 yr−1. The very…
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Artikel Jurnal
Flood Susceptibility Modeling in a Subtropical Humid Low-Relief Alluvial Plain Environment: Application of Novel Ensemble Machine Learning Approach
This study has developed a new ensemble model and tested another ensemble model for flood susceptibility mapping in the Middle Ganga Plain (MGP). The results of these two models have been quantitatively compared for performance analysis in zoning flood susceptible areas of low altitudinal range…