J. Shiri
Publications
121
h-index
37
Citations
3,741
Highly Influential Citations
111
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Forecasting daily lake levels using artificial intelligence approaches
Ö. Kisi, J. Shiri, Bagher Nikoofar
Computer Science
Comput. Geosci.

1 April 2012
TLDR
Three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models. Expand
125 Citations
9
River suspended sediment estimation by climatic variables implication: Comparative study among soft computing techniques
Ö. Kisi, J. Shiri
Environmental Science, Computer Science
Comput. Geosci.
1 June 2012
TLDR
Compared the accuracy of three different soft computing methods, Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference System, and Gene Expression Programming, in estimating daily suspended sediment concentration on rivers by using hydro-meteorological data, the Conjugate gradient algorithm was found to be better than the others. Expand
94 Citations
7
Prediction of long‐term monthly air temperature using geographical inputs
O. Kisi, J. Shiri
Environmental Science
2014
Air temperature as a major climatic component is important in land evaluation, water resources planning and management, irrigation scheduling and agro-hydrologic planning. In this paper, the… Expand
46 Citations
6
Daily reference evapotranspiration modeling by using genetic programming approach in the Basque Country (Northern Spain)
J. Shiri, O. Kisi, G. Landeras, J. J. López, A. Nazemi, L. Stuyt
Environmental Science
11 January 2012
Summary Evapotranspiration, as a major component of the hydrological cycle, is of importance for water resources management and development, as well as for estimating the water budget of irrigation… Expand
119 Citations
5
Suspended sediment modeling using genetic programming and soft computing techniques
O. Kisi, Ali Hosseinzadeh Dailr, M. Cimen, J. Shiri
Mathematics
11 July 2012
Summary Modeling suspended sediment load is an important factor in water resources engineering as it crucially affects the design and management of water resources structures. In this study the… Expand
130 Citations
5
Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations
J. Shiri, Ö. Kisi
Mathematics, Computer ScienceComput. Geosci.
1 October 2011
TLDR
This paper investigates the ability of genetic programming (GP) and adaptive neuro-fuzzy inference system (ANFIS) techniques for groundwater depth forecasting and found that the GP and ANFIS models could be employed successfully in forecasting water table depth fluctuations. Expand
120 Citations
5
PDF
Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model
J. Shiri, O. Kisi
Environmental Science
26 November 2010
Summary Streamflow forecasting is an important issue in hydrologic engineering, as it determines the reservoir inflow as well as the flooding events, in spite of several other applications in water… Expand
138 Citations
5
Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia
S. Karimi, Ö. Kisi, J. Shiri, O. Makarynskyy
Mathematics, Computer ScienceComput. Geosci.
1 March 2013
TLDR
Multi linear regression technique was used for selecting the optimal input combinations (lag times) of hourly sea level and results indicated that triangular membership function was optimal for predictions with the ANFIS models while adaptive learning rate and Levenberg-Marquardt were most suitable for training the ANN models.Expand
81 Citations
4
PDF
A survey of water level fluctuation predicting in Urmia Lake using support vector machine with firefly algorithm
Ö. Kisi, J. Shiri, +4 authors R. Hashim
Computer ScienceAppl. Math. Comput.
1 November 2015
TLDR
The experimental results showed that an improvement in the predictive accuracy and capability of generalization can be achieved by the SVM-FA approach in comparison to the GP and ANN in 1 day ahead lake level forecast. Expand
67 Citations
3
PDF
Precipitation Forecasting Using Wavelet-Genetic Programming and Wavelet-Neuro-Fuzzy Conjunction Models
O. Kisi, J. Shiri
Engineering
3 June 2011
Forecasting precipitation as a major component of the hydrological cycle is of primary importance in water resources engineering, planning and management as well as in scheduling irrigation… Expand
147 Citations
3
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