Procedia Engineering· 2012
Modelling using Polynomial Regression
- 777citations
- 2012year
Short summary
This paper applies polynomial regression to model the curvilinear relationship between strains and drilling depth, estimating parameters with a least squares method.
AI-generated from the title and abstract; the full text is not read.
Key points
- Polynomial regression is useful for curvilinear relationships between variables.
- The model was applied to characterize the relationship between strains and drilling depth.
- Parameters were estimated using the least squares method.
- Model accuracy was evaluated using common regression indicators.
- MATLAB was used for data analysis and calculations.
AI-generated from the title and abstract; the full text is not read.
Abstract
This paper is concentrated on the polynomial regression model, which is useful when there is reason to believe that relationship between two variables is curvilinear. The polynomial regression model has been applied using the characterisation of the relationship between strains and drilling depth. Parameters of the model were estimated using a least square method. After fitting, the model was evaluated using some of the common indicators used to evaluate accuracy of regression model. The data were analyzed using computer program MATLAB that performs these calculations.
The authors' abstract, as published at the source. Procedia Engineering, 2012 · DOI ↗
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Field: Discrete Mathematics and Combinatorics
Discrete Mathematics and CombinatoricsMathematics