COMPARISON OF NEURO-FUZZY, GENETIC ALGORITHM, ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION FOR PREDICTION OF SOIL SALINITY (CASE STUDY: ARDAKAN CITY)

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TAGHIZADEH MEHRJARDI RUHOLLAH; SARMADIAN FEREYDOON; SAVAGHEBI GHOLEM REZA; OMID MAHMOUD; TOOMANIAN NOURAYER; ROUSTA MOHAMMAD JAVAD; RAHIMIYAN MOHAMMAD HASAN

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Journal: Journal of Range and Watershed Managment Year:2013 | Volume:66 | Issue:2 Page(s): 207-222

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Title

COMPARISON OF NEURO-FUZZY, GENETIC ALGORITHM, ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION FOR PREDICTION OF SOIL SALINITY (CASE STUDY: ARDAKAN CITY)

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Keywords

ANFISQ2

SOIL SALINITYQ2

GAQ2

ANNQ2

MLRQ2

Abstract

In recent years, alternative methods have been used for estimation of SOIL SALINITY. Therefore, at present research, 600 soil samples collected from Ardakan in central Iran. Then EM38 and terrain parameters such as wetness index, land index and curvature as readily measured properties and SOIL SALINITY (0-30 and 0-100) as predicted variables were measured. After that, the data set was divided into two subsets for calibration (80%) and testing (20%) of the models. For predicting of mentioned parameters, ANFIS, GA, ANNs and MLR were applied. In order to evaluate models, some evaluation parameters such as root mean square, average error, average standard error and coefficient of determination were used. Results showed that the ANFIS model gives better estimation than the other techniques for all characteristics whereas this model increased accuracy of predictions about 17 and 11% for EC30 and EC100 respectability. After ANFIS model, GA and ANN had better accuracy than multivariate regression.

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APA: Copy

TAGHIZADEH MEHRJARDI, RUHOLLAH, SARMADIAN, FEREYDOON, SAVAGHEBI, GHOLEM REZA, OMID, MAHMOUD, TOOMANIAN, NOURAYER, ROUSTA, MOHAMMAD JAVAD, & RAHIMIYAN, MOHAMMAD HASAN. (2013). COMPARISON OF NEURO-FUZZY, GENETIC ALGORITHM, ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION FOR PREDICTION OF SOIL SALINITY (CASE STUDY: ARDAKAN CITY). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), 66(2), 207-222. SID. https://sid.ir/paper/162684/en

Vancouver: Copy

TAGHIZADEH MEHRJARDI RUHOLLAH, SARMADIAN FEREYDOON, SAVAGHEBI GHOLEM REZA, OMID MAHMOUD, TOOMANIAN NOURAYER, ROUSTA MOHAMMAD JAVAD, RAHIMIYAN MOHAMMAD HASAN. COMPARISON OF NEURO-FUZZY, GENETIC ALGORITHM, ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION FOR PREDICTION OF SOIL SALINITY (CASE STUDY: ARDAKAN CITY). JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES)[Internet]. 2013;66(2):207-222. Available from: https://sid.ir/paper/162684/en

IEEE: Copy

RUHOLLAH TAGHIZADEH MEHRJARDI, FEREYDOON SARMADIAN, GHOLEM REZA SAVAGHEBI, MAHMOUD OMID, NOURAYER TOOMANIAN, MOHAMMAD JAVAD ROUSTA, and MOHAMMAD HASAN RAHIMIYAN, “COMPARISON OF NEURO-FUZZY, GENETIC ALGORITHM, ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION FOR PREDICTION OF SOIL SALINITY (CASE STUDY: ARDAKAN CITY),” JOURNAL OF RANGE AND WATERSHED MANAGEMENT (IRANIAN JOURNAL OF NATURAL RESOURCES), vol. 66, no. 2, pp. 207–222, 2013, [Online]. Available: https://sid.ir/paper/162684/en

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