1. Onyari, E. and B.D. Ikotun, 2018. Prediction of compressive and flexural strengths of a modified zeolite additive mortar using artificial neural network. Constr. Build. Mater., 187: 1232-1241.
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2. Onyari, E. and A. Taigbenu, 2017. Inverse green element evaluation of source strength and concentration in groundwater transport, J. Hydroinf., 19: 81-96.
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3. Onyari, E.K. and F.M. Ilunga, 2013. Application of MLP neural network and M5P model tree in predicting streamflow: A case study of luvuvhu catchment, South Africa. Int. J. Innovation, Manage. Technol., 4: 11-15.
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4. Masego, I. and E. Onyari, 2011. Application of Hierarchical Process (AHP) for ANN model selection in streamflow prediction. World Multiconference on Syst. Cybern. Inf. Orlando, USA, 3: 215-219.
5. Popescu, I., A. Jonoski, S.J.V. Andel, E. Onyari, Quiroga and V.G. Moya, 2010. Integrated modelling for flood risk mitigation in Romania: Case study of the Timis-Bega river basin. Int. J. River Basin Manage., 8: 269-280.
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6. Onyari E. and F. Ilunga, 2010. Application of MLP-ANN and M5P-MT in streamflow estimation: A case study of luvuvhu catchment, South Africa. Int. Conf. Inf. Multimedia Technol., Hong Kong, China, 3: 156-160.
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