MK
Masoud Karbasi
University of Zanjan, University of Tehran
Research areas: Environmental Science · Environmental Engineering · Hydrological Forecasting Using AI · Hydrology and Drought Analysis · Stock Market Forecasting Methods
0000-0002-9012-8280
Employment
- 2011 - Present
Education
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University of Tehran P.H.D2003 - 2011
Projects & Funding
Projects & funding information is unavailable.
Publications (81)
- A reliable deep ensemble hybrid model for urban air quality health index forecasting in maritime Canada Save
- An intelligent weighted adaptive regression process for reliable and uncertainty aware drought forecasting Save
- Utilizing soil characteristics and hybrid machine learning for interpretable potato yield prediction: A study with satin-bowerbird optimization and deep neural network Save
- A state-of-the-art novel approach to predict potato crop coefficient (Kc) by integrating advanced machine learning tools Save
- Advancing long-term precipitation pattern forecasting in Atlantic Canada using successive variational mode decomposition, recursive LSTM, and graph-based feature selection Save
- Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms Save
- Enhanced water quality prediction model using advanced hybridized resampling alternating tree-based and deep learning algorithms Save
- Meticulous estimation of maize actual evapotranspiration: A comprehensive explainable CatBoost algorithm reinforced with Jackknife uncertainty paradigm Save
- Thermo-physical properties estimation of an oil-based hybrid nanofluid: application of a new hybrid neurocomputing approach Save
- eXplainable expert systems for potato tuber yield prediction in the Maritime provinces of Canada Save
- Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting Save
- Accurate monitoring of micronutrients in tilled potato soils of eastern Canada: Application of an eXplainable inspired-adaptive boosting framework coupled with SelectKbest Save
- Boruta extra tree-bidirectional long short-term memory model development for Pan evaporation forecasting: Investigation of arid climate condition Save
- Correction to: Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm (Scientific Reports, (2024), 14… Save
- Developing Extended and Unscented Kalman Filter-Based Neural Networks to Predict Cluster-Induced Roughness in Gravel Bed Rivers Save
- Innovative multi-temporal evapotranspiration forecasting using empirical fourier decomposition and bidirectional long short-term memory Save
- Monitoring of greenhouse gas emission drivers in Atlantic Canadian Potato production: A robust explainable intelligent glass-box Save
- 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 Save
- Multi-step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) model enhanced by Boruta-XGBoost feature selection algorithm Save
- Quantitative improvement of streamflow forecasting accuracy in the Atlantic zones of Canada based on hydro-meteorological signals: A multi-level advanced intelligent expert framework Save