Ravinesh C. Deo

According to our database, Ravinesh C. Deo authored at least 9 papers between 2015 and 2020.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2020

Global Solar Radiation Estimation and Climatic Variability Analysis Using Extreme Learning Machine Based Predictive Model.

Tao Hai, Ahmad Sharafati, Achite Mohammed, Sinan Q. Salih, Ravinesh C. Deo, Nadhir Al-Ansari, Zaher Mundher Yaseen

IEEE Access, 2020

2019

Sleep EEG signal analysis based on correlation graph similarity coupled with an ensemble extreme machine learning algorithm.

Shahab A. Abdulla, Mohammed Diykh, Raid Luaibi Laft, Khalid Saleh, Ravinesh C. Deo

Expert Syst. Appl., 2019

Fractal dimension undirected correlation graph-based support vector machine model for identification of focal and non-focal electroencephalography signals.

Mohammed Diykh, Shahab A. Abdulla, Khalid Saleh, Ravinesh C. Deo

Biomed. Signal Proc. and Control, 2019

2018

Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors.

Hadi Sanikhani, Ravinesh C. Deo, Pijush Samui, Özgür Kisi, Cihan Mert, Rasoul Mirabbasi, Siavash Gavili, Zaher Mundher Yaseen

Computers and Electronics in Agriculture, 2018

Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties.

Louis Kouadio, Ravinesh C. Deo, Vivekananda Byrareddy, Jan F. Adamowski, Shahbaz Mushtaq, Van Phuong Nguyen

Computers and Electronics in Agriculture, 2018

Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting.

Mumtaz Ali, Ravinesh C. Deo, Nathan J. Downs, Tek Maraseni

Computers and Electronics in Agriculture, 2018

Predicting compressive strength of lightweight foamed concrete using extreme learning machine model.

Zaher Mundher Yaseen, Ravinesh C. Deo, Ameer Hilal, Abbas M. Abd, Laura Cornejo-Bueno, Sancho Salcedo-Sanz, Moncef L. Nehdi

Advances in Engineering Software, 2018

Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia.

Mohanad S. Al-Musaylh, Ravinesh C. Deo, Jan F. Adamowski, Yan Li

Advanced Engineering Informatics, 2018

2015

Prediction of SPEI Using MLR and ANN: A Case Study for Wilsons Promontory Station in Victoria.

Soukayna Mouatadid, Ravinesh C. Deo, Jan F. Adamowski

Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015