F. Parvin

发表

Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms

Sk Ajim Ali, Q. Pham, N. T. Linh, 2022, Theoretical and Applied Climatology.

Appraisal of infrastructural amenities to analyze spatial backwardness of Murshidabad district using WSM and GIS-based kernel estimation

Sk Ajim Ali, F. Parvin, S. Najmul Islam Hashmi, 2019, GeoJournal.

An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility mapping in the Rangit River watershed, India

Duong Tran Anh, Yasin Wahid Rabby, Sk Ajim Ali, 2022, Natural Hazards.

Flood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approach

Sk Ajim Ali, Q. Pham, E. Łupikasza, 2022, Natural Hazards.

Predicting the effects of climate change on prospective Banj oak (Quercus leucotrichophora) dispersal in Kumaun region of Uttarakhand using machine learning algorithms

Sk Ajim Ali, Ateeque Ahmad, S. Shamim, 2022, Modeling Earth Systems and Environment.

Phytoremediation of Heavy Metals (Ar, Cd, Pb) Using Transgenic Rice Plants - an Overview

F. Parvin, R. Islam, M. Faris, 2015 .

Urban flood vulnerability assessment in a densely urbanized city using multi-factor analysis and machine learning algorithms

Sk Ajim Ali, Q. Pham, N. T. Linh, 2022, Theoretical and Applied Climatology.

An ensemble random forest tree with SVM, ANN, NBT, and LMT for landslide susceptibility mapping in the Rangit River watershed, India

Duong Tran Anh, Yasin Wahid Rabby, Sk Ajim Ali, 2022, Natural Hazards.

Appraisal of infrastructural amenities to analyze spatial backwardness of Murshidabad district using WSM and GIS-based kernel estimation

Sk Ajim Ali, F. Parvin, S. Najmul Islam Hashmi, 2019, GeoJournal.

A district-level vulnerability assessment of next COVID-19 variant (Omicron BA.2) in Uttarakhand using quantitative SWOT analysis

Sk Ajim Ali, Ateeque Ahmad, Mohd Mohsin, 2022, Environment, development and sustainability.

Retrieval of Land Surface Temperature from Landsat 8 OLI and TIRS: A Comparative Analysis Between Radiative Transfer Equation-Based Method and Split-Window Algorithm

Sk Ajim Ali, Ateeque Ahmad, F. Parvin, 2022, Remote Sensing in Earth Systems Sciences.

A comparison among fuzzy multi-criteria decision making, bivariate, multivariate and machine learning models in landslide susceptibility mapping

Nadhir Al-Ansari, Quoc Bao Pham, Romulus Costache, 2021, Geomatics, Natural Hazards and Risk.

GIS-based comparative assessment of flood susceptibility mapping using hybrid multi-criteria decision-making approach, naïve Bayes tree, bivariate statistics and logistic regression: A case of Topľa basin, Slovakia

Mohammad Ali Ghorbani, Nguyen Thi Thuy Linh, Quoc Bao Pham, 2020 .

Accessibility and site suitability for healthcare services using GIS-based hybrid decision-making approach: a study in Murshidabad, India

Sk Ajim Ali, F. Parvin, Aaisha Khatoon, 2020, Spatial Information Research.

Isolation of Mixed Bacterial Culture from Rajshahi Silk Industrial Zone and Their Efficiency in Azo Dye Decolorization

Md Mahmudul Islam, I. Sarkar, A. Dutta, 2015 .

Spatial implementation of frequency ratio, statistical index and index of entropy models for landslide susceptibility mapping in Al-Balouta river basin, Tartous Governorate, Syria

Sk Ajim Ali, H. Almohamad, R. Costache, 2022, Geoscience Letters.

Green HRM: pathway towards environmental sustainability using AHP and FAHP in a nascent parsimony

F. Parvin, N. Khan, Aaisha Khatoon, 2022, International Journal of Manpower.

Spatial prediction and mapping of the COVID-19 hotspot in India using geostatistical technique

Sk Ajim Ali, Ateeque Ahmad, F. Parvin, 2021, Spatial Information Research.

Examining challenges and multi-strategic approaches in waste management during the COVID-19 pandemic: A systematic review

Sk Ajim Ali, F. Parvin, 2022, Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA.

Predicting the effects of climate change on prospective Banj oak (Quercus leucotrichophora) dispersal in Kumaun region of Uttarakhand using machine learning algorithms

Sk Ajim Ali, Ateeque Ahmad, Mohd Mohsin, 2022, Modeling Earth Systems and Environment.

Sanitary landfill site selection by integrating AHP and FTOPSIS with GIS: a case study of Memari Municipality, India

Duong Tran Anh, Sk Ajim Ali, N. Al‐Ansari, 2020, Environmental Science and Pollution Research.

GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms

Mohammad Ali Ghorbani, Nguyen Thi Thuy Linh, Quoc Bao Pham, 2020, Geoscience Frontiers.

Detection of areas prone to flood-induced landslides risk using certainty factor and its hybridization with FAHP, XGBoost and deep learning neural network

Quoc Bao Pham, Romulus Costache, Duong Tran Anh, 2021 .

Examining the role of class imbalance handling strategies in predicting earthquake-induced landslide-prone regions

Sk Ajim Ali, K. Koc, Q. Pham, 2023, Appl. Soft Comput..

An integrated approach for evaluating the flash flood risk and potential erosion using the hydrologic indices and morpho-tectonic parameters

Sk Ajim Ali, Q. Pham, F. Parvin, 2021, Environmental Earth Sciences.

Mass movement susceptibility prediction and infrastructural risk assessment (IRA) using GIS-based Meta classification algorithms

Sk Ajim Ali, Q. Pham, Meriame Mohajane, 2023, Appl. Soft Comput..

Hydro-geochemical assessment of ground water for drinking and agricultural purposes and potential human health risk in Aligarh city, India

Sk Ajim Ali, M. Nafees, F. Parvin, 2023, Chemical Engineering Journal Advances.

Estimating Photosynthetically Active Euphotic Layer in Major Lakes of Kumaun Region Using Secchi Depth

Sk Ajim Ali, S. Shamim, F. Parvin, 2023, Water, Air, & Soil Pollution.

Comparing the Performance of Machine Learning Algorithms for Groundwater Mapping in Delhi

Sk Ajim Ali, S. Shamim, F. Parvin, 2023, Journal of the Indian Society of Remote Sensing.