Civil and Environmental Science Journal
Vol 1, No 1 (2018)

Data Generation In Order To Replace Lost Flow Data Using Bootstrap Method And Regression Analysis


Susilo, Gatot Eko



Article Info

Publish Date
06 Apr 2018

Abstract

This paper aims to find method to generate data in order to replace lost flow data in the series of discharge data in Sungai Seputih River, Lampung Province. Bootstrap simulation is used to estimate the discharge data and complete the existing discharge data. Regression analysis is also used to find the pattern of data distribution. Results of the research show that both methods are able to generate new series of flow data that the distribution is similar to available field data. Results also show that the use of statistical methods is one way to tackle the problem of data limitations due to missing or unrecorded data. The weakness of data generation using a combination of Bootstrap methods and regression analysis is the disappearance of extreme values in the data series. Existing extreme values have been modified to ideal values that satisfy certain distributions. However, careful analysis is required in using statistical method, so that the results of analysis do not deviate from the field conditions.


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Original Source : http://civense.ub.ac.id/index.php/civense/article/view/7
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Journal Info

Abbrev

civense

Publisher

Subject

Civil Engineering, Building, Construction & Architecture Engineering Environmental Science

Description

Civil and Environmental Science Journal (CIVENSE) is an international journal, peer-reviewed research publication covering new concepts, theories, methods, and techniques related to science and engineering. ...