LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios

Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts

(2020) Mumtaz Ali et al.   JOURNAL OF HYDROLOGY

Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach

(2020) Mumtaz Ali et al.   HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES

Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cites of queensland Australia

(2019) Sujan Ghimire et al.   JOURNAL OF CLEANER PRODUCTION

Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach

(2019) Ramendra Prasad et al.   CATENA

Research on soil moisture prediction model based on deep learning

(2019) Yu Cai et al.   PLoS One

Application of Long Short-Term Memory (LSTM) Neural Network for Flood Forecasting

(2019) Le et al.   Water

Application of a Parallel Particle Swarm Optimization-Long Short Term Memory Model to Improve Water Quality Data

(2019) Jianzhuo Yan et al.   Water

Research on Short-Term Load Prediction Based on Seq2seq Model

(2019) Gangjun Gong et al.   Energies

Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction

(2019) Ghimire et al.   Energies

Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms

(2019) Mumtaz Ali et al.   JOURNAL OF HYDROLOGY

Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms

(2019) Sujan Ghimire et al.   APPLIED ENERGY

Short-term electricity demand forecasting using machine learning methods enriched with ground-based climate and ECMWF Reanalysis atmospheric predictors in southeast Queensland, Australia

(2019) Mohanad S. AL-Musaylh et al.   RENEWABLE & SUSTAINABLE ENERGY REVIEWS

Temperature Prediction Using the Missing Data Refinement Model Based on a Long Short-Term Memory Neural Network

(2019) Park et al.   Atmosphere

A hybrid air quality early-warning framework: An hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms

(2019) Ekta Sharma et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting

(2018) Mumtaz Ali et al.   ATMOSPHERIC RESEARCH

Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches †

(2018) Salah Bouktif et al.   Energies

Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition

(2018) Ramendra Prasad et al.   GEODERMA

Developing a Long Short-Term Memory (LSTM) based model for predicting water table depth in agricultural areas

(2018) Jianfeng Zhang et al.   JOURNAL OF HYDROLOGY

Comparison of GCM Precipitation Predictions with Their RMSEs and Pattern Correlation Coefficients

(2018) et al.   Water

Estimation of daily global solar radiation using deep learning model

(2018) Kazım Kaba et al.   ENERGY

Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia

(2018) Bin Wang et al.   INTERNATIONAL JOURNAL OF CLIMATOLOGY

Application of multivariate recursive nesting bias correction, multiscale wavelet entropy and AI-based models to improve future precipitation projection in upstream of the Heihe River, Northwest China

(2018) Linshan Yang et al.   THEORETICAL AND APPLIED CLIMATOLOGY

The socioeconomic future of deltas in a changing environment

(2018) Iñaki Arto et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Dynamic Neural Network Modelling of Soil Moisture Content for Predictive Irrigation Scheduling

(2018) Olutobi Adeyemi et al.   SENSORS

Deep Learning with a Long Short-Term Memory Networks Approach for Rainfall-Runoff Simulation

(2018) Caihong Hu et al.   Water

Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks

(2018) Ata Akbari Asanjan et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Short-Term Load Forecasting Using EMD-LSTM Neural Networks with a Xgboost Algorithm for Feature Importance Evaluation

(2017) Huiting Zheng et al.   Energies

A combined model based on CEEMDAN and modified flower pollination algorithm for wind speed forecasting

(2017) Wenyu Zhang et al.   ENERGY CONVERSION AND MANAGEMENT

Performance of CMIP3 and CMIP5 GCMs to Simulate Observed Rainfall Characteristics over the Western Himalayan Region

(2017) Jitendra Kumar Meher et al.   JOURNAL OF CLIMATE

A new approach for simulating and forecasting the rainfall-runoff process within the next two months

(2017) Mohamad Javad Alizadeh et al.   JOURNAL OF HYDROLOGY

A Variable Impacts Measurement in Random Forest for Mobile Cloud Computing

(2017) Jae-Hee Hur et al.   WIRELESS COMMUNICATIONS & MOBILE COMPUTING

Improving PM2.5 Air Quality Model Forecasts in China Using a Bias-Correction Framework

(2017) Baolei Lyu et al.   Atmosphere

Evaluation of ACCESS climate model ocean diagnostics in CMIP5 simulations

(2017) S Marsland et al.   Australian Meteorological and Oceanographic Journal

Seasonal cycle of precipitation over major river basins in South and Southeast Asia: A review of the CMIP5 climate models data for present climate and future climate projections

(2016) Shabeh ul Hasson et al.   ATMOSPHERIC RESEARCH

On practical challenges of decomposition-based hybrid forecasting algorithms for wind speed and solar irradiation

(2016) Yamin Wang et al.   ENERGY

An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland

(2016) Ravinesh C Deo et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Using extreme learning machines for short-term urban water demand forecasting

(2016) Soukayna Mouatadid et al.   Urban Water Journal

Selecting Optimal Random Forest Predictive Models: A Case Study on Predicting the Spatial Distribution of Seabed Hardness

(2016) Jin Li et al.   PLoS One

Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

(2015) Ravinesh C. Deo et al.   ATMOSPHERIC RESEARCH

A Comparative Study of Empirical Mode Decomposition-Based Short-Term Wind Speed Forecasting Methods

(2015) Ye Ren et al.   IEEE Transactions on Sustainable Energy

Comparative analysis of CMIP3 and CMIP5 global climate models for simulating the daily mean, maximum, and minimum temperatures and daily precipitation over China

(2015) Qiaohong Sun et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

Feature Selection with theBorutaPackage

(2015) Miron B. Kursa et al.   Journal of Statistical Software

Assessing reliability of regional climate projections: the case of Indian monsoon

(2014) K. V. Ramesh et al.   Scientific Reports

Determination of Input for Artificial Neural Networks for Flood Forecasting Using the Copula Entropy Method

(2013) Lu Chen et al.   JOURNAL OF HYDROLOGIC ENGINEERING

The Millennium Drought in southeast Australia (2001-2009): Natural and human causes and implications for water resources, ecosystems, economy, and society

(2013) Albert I. J. M. van Dijk et al.   WATER RESOURCES RESEARCH

Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate

(2013) J. Sillmann et al.   JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES

A refined index of model performance: a rejoinder

(2012) David R. Legates et al.   INTERNATIONAL JOURNAL OF CLIMATOLOGY

Modelling Forest α-Diversity and Floristic Composition — On the Added Value of LiDAR plus Hyperspectral Remote Sensing

(2012) Benjamin F. Leutner et al.   Remote Sensing

An Overview of CMIP5 and the Experiment Design

(2011) Karl E. Taylor et al.   BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

A refined index of model performance

(2011) Cort J. Willmott et al.   INTERNATIONAL JOURNAL OF CLIMATOLOGY

An Improved Particle Swarm Optimization for Feature Selection

(2011) Yuanning Liu et al.   Journal of Bionic Engineering

Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada

(2011) Jan Adamowski et al.   WATER RESOURCES RESEARCH

Raising the bar? – The challenges of evaluating the outcomes of environmental modelling and software

(2010) K.B. Matthews et al.   ENVIRONMENTAL MODELLING & SOFTWARE

A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer

(2010) Heesung Yoon et al.   JOURNAL OF HYDROLOGY

Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling

(2009) Hoshin V. Gupta et al.   JOURNAL OF HYDROLOGY

Projected changes in temperature and precipitation extremes over the Yangtze River Basin of China in the 21st century

(2009) Ying Xu et al.   QUATERNARY INTERNATIONAL

Conditional Variable Importance for Random Forests

(2008) Carolin Strobl et al.   BMC BIOINFORMATICS

On the need for bias correction of regional climate change projections of temperature and precipitation

(2008) Jens H. Christensen et al.   GEOPHYSICAL RESEARCH LETTERS