Regression Models

Alkarkhi, Abbas F.M.; Alqaraghuli, Wasin A.A.

doi:10.1016/b978-0-12-814262-2.00007-8

Cited by 2 publications

(1 citation statement)

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“…Multiple linear regression is a statistical mathematical approach that fits a data set into a linear equation to represent the connection between one dependent variable and two or more independent variables. This technique is used for the data that is further simplified into the analytical solution [26]- [29]. The generalized form of the multiple linear regression equation is given as 𝑌 = 𝛼 1 * 𝑥 1 + 𝛼 2 * 𝑥 2 +.…”

Section: Multiple Linear Regression Modelmentioning

confidence: 99%

An Introductory Study on The Performance Prediction of Membrane-Based Energy Recovery Ventilators

Asif¹,

Ashraf²,

Sultan³

et al. 2021

Proceedings of International Exchange and Innovation Conference on Engineering &Amp; Sciences (IEICES)

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Indoor air quality can be improved by mechanical ventilation to achieve desired thermal and pleasure comfort. Ventilation and air-conditioning of air via traditional methods is not cost-effective and triggers tremendous energy loss. On a commercial scale, the exhaust air carries a considerable amount of energy from the conditioned space. Membrane-based energy recovery (MERV) ventilators recover some proportion of the exhaust energy (both latent and sensible) from the exhaust air stream using membrane technology. It can effectively reduce the excessive energy loss resulting from the exhaust air stream. The present study focuses on the development of performance prediction of MERV using multiple linear regression using published experimental data. Furthermore, this developed model is used for the ambient condition of Multan, Pakistan. The results show that the model is quite validated, and it can be used for the potential application of human thermal comfort/ air-conditioning. The developed model lies well within the acceptable range of error and provides acceptable results as compared to the published experimental MERV data under the climatic conditions of Multan, Pakistan.

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Section: Multiple Linear Regression Modelmentioning

confidence: 99%