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.