TY  - JOUR
T1  - Compressive Strength Prediction Using Linear Regression Method
AU  - Tiza, Michael Toryila
AU  - Imoni, Samson
AU  - Onyebuchi, Mogbo
AU  - Akande, Ebenezer Ogırıma
AU  - Jiya, Victoria Hassana
AU  - Onuzulike, Collins
PY  - 2023
DA  - September
Y2  - 2023
JF  - Journal of International Environmental Application and Science
JO  - J. Int. Environmental Application & Science
PB  - Şükrü DURSUN
WT  - DergiPark
SN  - 1307-0428
SP  - 100
EP  - 106
VL  - 18
IS  - 3
LA  - en
AB  - This study investigates the compressive strength of cement kiln replacement mixtures using a mechanistic modeling approach. The objective is to establish a mathematical model that predicts the compressive strength based on the percentage of cement kiln replacement. The study analyzed data from various replacement percentages ranging from 10% to 35% and their corresponding compressive strength values. A linear regression model was developed to capture the relationship between the replacement percentage and compressive strength. The model exhibited a good fit to the data, with a mean squared error of approximately 0.0254. Confidence intervals were calculated to provide a range of predicted compressive strength values at different replacement percentages. The findings of this study contribute to understanding the mechanical behavior of cement kiln replacement mixtures and offer insights for optimizing mixture designs. The developed mathematical model can serve as a valuable tool for engineers and researchers in the construction industry, aiding in the estimation of compressive strength for various cement kiln replacement scenarios.
KW  - Cement kiln Replacement
KW  - Compressive Strength
KW  - Mechanistic Modeling
KW  - Mathematical model
KW  - linear regression.
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UR  - https://dergipark.org.tr/en/pub/jieas/issue//1319805
L1  - https://dergipark.org.tr/en/download/article-file/3232230
ER  -