Journal Papers

Ahmed AAM, Deo RC, Ghahramani A, Feng Q, Raj N, Yin Z, et al. New double decomposition deep learning methods for river water level forecasting. Science of the Total Environment; 20 July 2022, 154722

Ahmed AAM, Deo RC, Raj N, Ghahramani A, Feng Q, Yin Z, et al. Deep learning hybrid model with Boruta-Random Forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity. Journal of Hydrology 2021; 599: 126 [Q1; Impact Factor: 5.72 and SNIP: 1.87; 95th percentile, 1ST IN HYDROLOGY DISCIPLINE]

Ahmed, AAM, Deo, RC, Feng, Q. et al. Hybrid deep learning method for a week-ahead evapotranspiration forecasting. Stochastic Environ Research Risk Assessment (2021) [Q1; Impact Factor: 3.38 and SNIP: 1.15; 86th percentile].

Ahmed AAM, Deo RC, Raj N. et al. Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations, and Synoptic-Scale Climate Index Data. Remote Sensing 2021; 13:554 [Q1; Impact Factor: 4.85 and SNIP: 1.71; 90th percentile].

Ahmed AAM, Deo RC, Ghahramani A. et al. LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios. Stochastic Environmental Research and Risk Assessment 2021: 1-31[Q1; Impact Factor: 3.38 and SNIP: 1.15; 86th percentile].

Ahmed AAM, Sharma E, Jui SJJ, Deo RC. at al. Kernel Ridge Regression hybrid method for wheat yield prediction using satellite-derived predictors, Remote Sensing. 2022; 14(5): 1136. [Q1; Impact Factor: 4.85 & SNIP: 1.71; 90th percentile]

Jui SJJ, Ahmed AAM, Bose A. et al. Spatio-temporal Hybrid Random Forest Model for Tea Yield Prediction using Satellite Derived Hydro-meteorological Variables Coupled with Dragonfly Algorithm and Support Vector Regression, Remote Sens. 2022, 14, 805 [Q1; Impact Factor: 4.85 and SNIP: 1.71] .

Raj N, Gharineiat Z, Ahmed AAM, Stepanyants Y, Assessment and Prediction of Sea Level Trend in the South Pacific Region, Remote Sensing 2022; 14(4):986. [Q1; Impact Factor: 4.85 and SNIP: 1.71; 90th percentile].

Ahmed AAM, Hafez Ahmed, Ahmed O, Optimisation algorithms as training approach with deep learning methods to develop ultraviolet index forecasting model in Australia. Stoch Environ Res Risk Assess (2021) [Q1; Impact Factor: 3.38 and SNIP: 1.15; 86th percentile]

Ahmed AAM, Shah SMA (2017) Application of artificial neural networks to predict peak flow of Surma River in Sylhet zone of Bangladesh, International Journal of Water, 11(4), DOI: 10.1504/IJW.2017.088046

Ahmed AAM, Shah SMA (2017) Application of adaptive neuro-fuzzy inference system (ANFIS) to predict the biochemical oxygen demand (BOD) of Surma River in the Journal of King Saud Uni - Engineering Sci. 29(3): 237-243.

Ahmed AAM (2017) Prediction of dissolved oxygen in Surma River influenced by biochemical oxygen demand and chemical oxygen demand using the artificial neural networks, Journal of King Saud Uni- Engg Sci. 29(2): 151-158

Alam JB, Ahmed AAM, Ahmed B, MJH Khan (2011) Evaluation of possible environmental impacts for Barapukuria thermal power plant and coal mine in the Journal of Soil Sci&Environ. Management (ISSN 2141-2391) 2(5):126-131.

Alam JB, Ahmed AAM, Munna GM, Ahmed AAM (2010) Environmental Impact Assessment of the oil and gas sector-a case study of Magurchara gas field, Journal of Soil Sci., and Environ. Management (ISSN 2141-2391) 1(5): 86-91.