Prediction of Digital Elevation Model Height by Multivariate Adaptive Regression Splines (Mars) Interpolation Approach

Zeena Adil Najeeb

Prediction of Digital Elevation Model Height by Multivariate Adaptive Regression Splines (Mars) Interpolation Approach

Zeena Adil Najeeb * §

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§ Al-Nahrain University

Prediction of Digital Elevation Model Height by Multivariate Adaptive Regression Splines (Mars) Interpolation Approach

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Abstract

The objective of this paper is to assess the applicability and performance of multivariate adoptive regression spline analysis (MARS) for prediction elevation height in digital elevation model. MARS is an adaptive, nonparametric regression approach. Three dimensional coordinates (X, Y, and Z) in Equal-Sized grid Cell observed and recognized vie Differential Global Positioning System (DGPS) at AL-Nahrain university site. Mathematical prediction models with their errors and analysis are established in this paper. As the same time the independent variables X,Y and the dependent predicted variable Z the height which be used in. The data were dividedrandomly into training and testing70% of the entire data set is utilized for training and the remaining30% for testing. MARS depends on two steps for computation logarithm forward and backward to get better performance MARS adopts Generalized Cross-Validation (GCV) with different statistical parameters of standard deviation, root mean square error and residuals.

References

15 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Zeena Adil Najeeb. 2017. "Prediction of Digital Elevation Model Height by Multivariate Adaptive Regression Splines (Mars) Interpolation Approach". Global Journal of Research in Engineering - E: Civil & Structural GJRE-E Volume 17 (GJRE Volume 17 Issue E3).

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GJRE Volume 17 Issue E3

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

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Classification

GJRE-E Classification FOR Code: 090599

Submission ReceivedDecember 14, 2016
Peer Review Double Blind
Handling Editor
Accepted January 1, 2017
Published December 18, 2017

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v1.2

Issue date

December 18, 2017

Language

English

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Article Matrices

Total Score: 101

Country: Iraq

Subject: Global Journal of Research in Engineering - E: Civil & Structural

Authors: Zeena Adil Najeeb (PhD/Dr. count: 0)

View Count (all-time): 455

Total Views (Real + Logic): 925

Total Downloads (simulated): 39

Publish Date: 2017 01, Sun

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