Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Amir Khakpour"'
Publikováno v:
آب و فاضلاب, Vol 29, Iss 1, Pp 70-80 (2018)
The effluent from copper industries is important in terms of production volume, environmental pollution and cost of treatment and disposal. In addition to its economic reasons, the effluent recovery also reduces the pollutant load. Such cases therefo
Externí odkaz:
https://doaj.org/article/7dd78489799a495fbcb48d7381edf2a5
Publikováno v:
آب و فاضلاب, Vol 22, Iss 1, Pp 118-123 (2011)
The main goal of this research is to evaluate the role of input selection by Principal Component Analysis (PCA) on Support Vector Machine (SVM) performance for monthly stream flow prediction. For this purpose, SVM is used to predict monthly flow as a
Externí odkaz:
https://doaj.org/article/c59f0ebc083045e8bc63ad6859606abf
Publikováno v:
آب و فاضلاب, Vol 21, Iss 3, Pp 99-107 (2010)
Accurate prediction of longitudinal dispersion coefficient (LDC) can be useful for the determination of pollutants concentration distribution in natural rivers. However, the uncertainty associated with the results obtained from forecasting models has
Externí odkaz:
https://doaj.org/article/bd44800f428048f69740d0386f47e9ad
Autor:
Amir Khakpour, Mohammadreza Vesali-Naseh, Abdulreza Karbassi, Mohammadreza Shahbazbegian, Roohollah Noori, Hassan Mohammadi Khalf Badam
Publikováno v:
Environmental Modeling & Assessment. 17:411-420
Canonical correlation analysis (CCA), principal component analysis (PCA), and principal factor analysis (PFA) have been adopted to provide ease of understanding: interpretation of a large complex data set in the Gorganrud River monitoring networks, e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::10129ca65ef819e93498cb0380aa65ee
https://doi.org/10.1007/s10666-011-9302-2
https://doi.org/10.1007/s10666-011-9302-2
Publikováno v:
Expert Systems with Applications. 37:5856-5862
Predicting the stream flow is one of the most important steps in the water resources management. Artificial neural network (ANN) has been suggested and applied for this purpose by many of researchers. In such studies for verification and comparison o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbb11308ffbd8d05b6a1b43386d83a55
https://doi.org/10.1016/j.eswa.2010.02.020
https://doi.org/10.1016/j.eswa.2010.02.020
Publikováno v:
Analytical Methods. 4:1996
A direct, inexpensive and solventless method based on headspace extraction coupled to gas chromatography-flame ionization detection (GC-FID) was developed for determination of benzene, toluene, ethylbenzene and xylenes (BTEX). In this method, volatil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83c772cff8925ea108de393aef076048
https://doi.org/10.1039/c2ay05839a
https://doi.org/10.1039/c2ay05839a