Mumtaz Ali

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University of Southern Queensland

Australia

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Recent Grants

Grant: Close

Probabilistic and Deep Learning Modelling of Drought Predictions and Their Impacts on Crops

Open Date: 2022-01-01

Close Date: 2024-01-01

Grant: Close

Research Support Grant

Open Date: 2021-01-01

Close Date: 2024-01-01

Grant: Close

Big Data Analytics in Agricultural and Environmental Science

Open Date: 2019-04-01

Close Date: 2022-01-01

Articles (26)

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Collaborators (6)

Adeyemi Olusola

Assistant Professor

York University

CANADA

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Yong Xiang

Deakin University

AUSTRALIA

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Miklas Scholz

University of Salford

UNITED KINGDOM

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Shahab Abdulla

Senior Lecturer

University of Southern Queensland

AUSTRALIA

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Zaher Mundher Yaseen

SAUDI ARABIA

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Aitazaz A. Farooque

CANADA

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Mumtaz Ali

Research Interests

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Recent Grants

Articles (26)

Uncertainty assessment based on data decomposition and Boruta-driven extreme gradient boosting to predict spatiotemporal urban air dust heavy metal index

SPI-Informed Drought Forecasts Integrating Advanced Signal Decomposition and Machine Learning Models

Leveraging Advanced Data-Driven Approaches to Forecast Daily Floods Based on Rainfall for Proactive Prevention Strategies in Saudi Arabia

Designing empirical fourier decomposition reinforced with multiscale increment entropy and deep learning to forecast dry bulb air temperature

An explainable predictive approach for investigation of greenhouse gas emissions in maritime canada's potato agriculture

Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory

Multi-step ahead significant wave height forecasting using global and local view graph representation based on GRU model

Multi-step solar ultraviolet index prediction: integrating convolutional neural networks with long short-term memory for a representative case study in Queensland, Australia

Monthly sodium adsorption ratio forecasting in rivers using a dual interpretable glass-box complementary intelligent system: Hybridization of ensemble TVF-EMD-VMD, Boruta-SHAP, and eXplainable GPR

Enhancing groundwater level prediction accuracy using interpolation techniques in deep learning models

Adaptive Regularization and Resilient Estimation in Federated Learning

Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting

Application of an explainable glass-box machine learning approach for prognostic analysis of a biogas-powered small agriculture engine

Short-term wave power forecasting with hybrid multivariate variational mode decomposition model integrated with cascaded feedforward neural networks

Forecasting River Water Temperature Using Explainable Artificial Intelligence and Hybrid Machine Learning: Case Studies in Menindee Region in Australia

A designed predictive modelling strategy based on data decomposition and machine learning to forecast solar radiation

Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation

Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm

Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach

An intelligent model involving multi-channels spectrum patterns based features for automatic sleep stage classification

Ensemble robust local mean decomposition integrated with random forest for short-term significant wave height forecasting

Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting

Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting

Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study

A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach

Development of an enhanced bidirectional recurrent neural network combined with time-varying filter-based empirical mode decomposition to forecast weekly reference evapotranspiration

Collaborators (6)

Adeyemi Olusola

Yong Xiang

Miklas Scholz

Shahab Abdulla

Zaher Mundher Yaseen

Aitazaz A. Farooque

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