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Akram Seifi, Soudabeh Golestani Kermani, Amir Mosavi and Fatemeh Soroush
Quantitatively analyzing models? uncertainty is essential for agricultural models due to the effect of inputs parameters and processes on increasing models? uncertainties. The main aim of the current study was to explore the influence of input parameter ...
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Rana Muhammad Adnan Ikram, Abolfazl Jaafari, Sami Ghordoyee Milan, Ozgur Kisi, Salim Heddam and Mohammad Zounemat-Kermani
Precise estimation of pan evaporation is necessary to manage available water resources. In this study, the capability of three hybridized models for modeling monthly pan evaporation (Epan) at three stations in the Dongting lake basin, China, were investi...
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Mohammad Zounemat-Kermani, Youngmin Seo, Sungwon Kim, Mohammad Ali Ghorbani, Saeed Samadianfard, Shabnam Naghshara, Nam Won Kim and Vijay P. Singh
This study evaluates standalone and hybrid soft computing models for predicting dissolved oxygen (DO) concentration by utilizing different water quality parameters. In the first stage, two standalone soft computing models, including multilayer perceptron...
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Homa Rashidizadeh-Kermani, Mostafa Vahedipour-Dahraie, Hamid Reza Najafi, Amjad Anvari-Moghaddam and Josep M. Guerrero
This paper proposes a stochastic bi-level decision-making model for an electric vehicle (EV) aggregator in a competitive environment. In this approach, the EV aggregator decides to participate in day-ahead (DA) and balancing markets, and provides energy ...
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Mohammad Zounemat-Kermani and Miklas Scholz
An adaptive neuro-fuzzy inference system (ANFIS) was developed using the subtractive clustering technique to study the air demand in low-level outlet works. The ANFIS model was employed to calculate vent air discharge in different gate openings for an em...
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Abdy Kermani and Robert Hairstans
Pág. 1806 - 1812
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Alexander Porteous and Abdy Kermani
Pág. 806 - 815
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Sherif, M R; Habib, I W; Nagshineh, M; Kermani, P
Pág. 268 - 282
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