S. Motamedi
Publications
59
h-index
17
Citations
828
Highly Influential Citations
22
Claim Author Page
Author pages are created from data sourced from our academic publisher partnerships and public sources.
Publications
Influence
Soft computing approaches for forecasting reference evapotranspiration
M. Gocić, S. Motamedi, +4 authors Muhammad Arif
Engineering, Computer Science
Comput. Electron. Agric.
1 April 2015
TLDR
SVM-Wavelet model was found to perform better than the GP, SVM-FFA and ANN models. Expand
94
5
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
SVM coupled with FA was used to forecast lake level.Results demonstrate the SVM-FA superiority.Expand
66
3
PDF
Extreme learning machine based prediction of daily dew point temperature
Kasra Mohammadi, Shahaboddin Shamshirband, S. Motamedi, D. Petkovic, R. Hashim, M. Gocić
Engineering, Computer Science
Comput. Electron. Agric.
1 September 2015
TLDR
An ELM-based model is proposed to predict daily dew point temperature with much greater predictions capability than SVM and ANN. Expand
67
3
PDF
Evaluating the compression index of fibrous peat treated with different binders
A. Dehghanbanadaki, A. Arefnia, Azin Keshtkarbanaeemoghadam, K. Ahmad, S. Motamedi, R. Hashim
Materials Science
Bulletin of Engineering Geology and the…
1 May 2017
Fibrous peats feature high compressibility and correspondingly very low strength. In this study, an investigation into the compressibility of untreated and stabilized fibrous peat with different… Expand
10
2
Determination of the most influential weather parameters on reference evapotranspiration by adaptive neuro-fuzzy methodology
D. Petkovic, M. Gocić, +4 authors H. Bonakdari
Mathematics, Computer Science
Comput. Electron. Agric.
1 June 2015
TLDR
The adaptive neuro-fuzzy inference system is applied for selection of the most influential reference evapotranspiration (ET0) parameters.Expand
53
1
PDF
An appraisal of wind turbine wake models by adaptive neuro-fuzzy methodology
Shahaboddin Shamshirband, D. Petkovic, R. Hashim, S. Motamedi, N. B. Anuar
Engineering
1 December 2014
Abstract Production losses and increased turbine loadings are observed in wind farms, when wind turbines interact with each other. If a wind turbine is located in the wake of another one, its… Expand
35
1
Extreme learning machine approach for sensorless wind speed estimation
V. Nikolic, S. Motamedi, Shahaboddin Shamshirband, D. Petkovic, Sudheer Ch, M. Arif
Engineering
1 March 2016
Precise predictions of wind speed play important role in determining the feasibility of harnessing wind energy. In fact, reliable wind predictions offer secure and minimal economic risk situation to… Expand
43
1
A hybrid SVM-FFA method for prediction of monthly mean global solar radiation
Shahaboddin Shamshirband, Kasra Mohammadi, C. Tong, M. Zamani, S. Motamedi, Sudheer Ch
MathematicsTheoretical and Applied Climatology
10 May 2015
In this study, a hybrid support vector machine–firefly optimization algorithm (SVM-FFA) model is proposed to estimate monthly mean horizontal global solar radiation (HGSR). The merit of SVM-FFA is… Expand
37
1
PDF
Long-Term Assessment of an Innovative Mangrove Rehabilitation Project: Case Study on Carey Island, Malaysia
S. Motamedi, R. Hashim, R. Zakaria, K. Song, B. Sofawi
Environmental Science, Medicine
TheScientificWorldJournal
3 July 2014
Wave energy and storm surges threaten coastal ecology and nearshore infrastructures. Although coastal structures are conventionally constructed to dampen the wave energy, they introduce tremendous… Expand
17
1
PDF
Evaluation of Morphodynamic Changes in the Vicinity of Low-Crested Breakwater on Cohesive Shore of Carey Island, Malaysia
Arniza Fitri, R. Hashim, K. Song, S. Motamedi
Geology
1 December 2015
There is no adequate research available on the responses of coastal morphodynamic to low-crested breakwaters along the cohesive shore. Since the shore responses to coastal structures vary widely… Expand
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