PREDICTION OF TABRIZ FAULT'S EARTHQUAKES MAGNITUDE USING POLYNOMIAL REGRESSION

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KHEIRI ALI; BALAFAR MOHAMMAD ALI; ZAMANI BEHZAD

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Journal: EMERGENCY MANAGEMENT Year:2016 | Volume:5 | Issue:10 Page(s): 77-81

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Information Journal Paper

Title

PREDICTION OF TABRIZ FAULT'S EARTHQUAKES MAGNITUDE USING POLYNOMIAL REGRESSION

Author(s)

KHEIRI ALI | BALAFAR MOHAMMAD ALI | ZAMANI BEHZAD | Issue Writer Certificate

Keywords

DATA MININGQ2

POLYNOMIAL REGRESSIONQ1

SEISMIC DATAQ1

FAULTQ1

PREDICTIONQ2

Abstract

Tabriz FAULT is one of the active and dangerous FAULTs in the North West of Iran. The FAULT crosses the north through the city and put crossing towns at risk. The majority of marginal inhabitants within the city are settled there. Their buildings do not resist the slightest shake. Analysis of SEISMIC DATA using POLYNOMIAL REGRESSION for predicting future earthquake's magnitude and risks can be helpful to reduce disaster results. First of all, input data are extracted and normalized. At the second step, model is obtained. In the third step, the magnitude of earthquake for the test data is predicated. In the fourth step, the performance of predicting earthquake magnitude is evaluated.Finally, to estimate the magnitude of earthquakes using other attributes a formula is obtained that can be used to estimate the coefficients of each of the independent variables.

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APA: Copy

KHEIRI, ALI, BALAFAR, MOHAMMAD ALI, & ZAMANI, BEHZAD. (2016). PREDICTION OF TABRIZ FAULT'S EARTHQUAKES MAGNITUDE USING POLYNOMIAL REGRESSION. EMERGENCY MANAGEMENT, 5(10), 77-81. SID. https://sid.ir/paper/225989/en

Vancouver: Copy

KHEIRI ALI, BALAFAR MOHAMMAD ALI, ZAMANI BEHZAD. PREDICTION OF TABRIZ FAULT'S EARTHQUAKES MAGNITUDE USING POLYNOMIAL REGRESSION. EMERGENCY MANAGEMENT[Internet]. 2016;5(10):77-81. Available from: https://sid.ir/paper/225989/en

IEEE: Copy

ALI KHEIRI, MOHAMMAD ALI BALAFAR, and BEHZAD ZAMANI, “PREDICTION OF TABRIZ FAULT'S EARTHQUAKES MAGNITUDE USING POLYNOMIAL REGRESSION,” EMERGENCY MANAGEMENT, vol. 5, no. 10, pp. 77–81, 2016, [Online]. Available: https://sid.ir/paper/225989/en

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