Abu Reza Md. Towfiqul Islam
Global and Planetary Change · 2020–2021
A researcher in the Science corpus: 3 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Global and Planetary Change — 28 citations into it
- Atmospheric Science — 7 citations into it
- Environmental Engineering — 6 citations into it
Whom Abu Reza Md. Towfiqul Islam trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Zekâi Sen (in Global and Planetary Change)
- C. Onyutha (in Global and Planetary Change)
Papers from Abu Reza Md. Towfiqul Islam's perspective
Ordered by how strongly the researchers Abu Reza Md. Towfiqul Islam trusts endorse each paper. Same corpus, a different order for every researcher.
- Trend Identification Simulation and Application
- Estimates of the Regression Coefficient Based on Kendall's Tau
- Identification of sub-trends from hydro-meteorological series (Stochastic environmental research and risk assessment (Print))
- The impacts of climate change on water resources and agriculture in China (Nature)
- Increasing Trend of Extreme Rain Events Over India in a Warming Environment (Science)
- Innovative Trend Analysis of Annual and Seasonal Rainfall Variability in Amhara Regional State, Ethiopia (Atmosphere)
- Applicability of prewhitening to eliminate the influence of serial correlation on the Mann‐Kendall test
- The meaning and use of the area under a receiver operating characteristic (ROC) curve.
- Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran (Proceedings of the Indian Academy of Sciences, Earth and Planetary Sciences)
- Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression (Landslides)
Their papers
- Modeling fragmentation probability of land-use and land-cover using the bagging, random forest and random subspace in the Teesta River Basin, Bangladesh (2021) — 129 citations
- Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches (2020) — 346 citations
- Flood susceptibility modelling using advanced ensemble machine learning models (2020) — 483 citations