Predicting building wall temperature in composite climate using regression models: A comparative study

Yadav, Manisha; Berwal, Anil K.

doi:10.1016/j.matpr.2021.01.567

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…DOE-2 used to measure the energy savings due to building retrofits. In the recent time Building information modeling (BIM) [19] is also used to analyze the energy evaluation of retrofit technologies used by making models of existing buildings, proposing substitutes, correlating, and analyzing building performance for these substitutes and modeling improvements [20], [21].…”

Section: ) Building Performance Assessmentmentioning

confidence: 99%

Retrofit Strategy in Existing Building for Implementing Energy Conservation Building Code in India

Berwal

Yadav

2021

EJERS

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The expanding commercial building sector and urbanization in India leads to an increase in demand of energy many folds. Consequently, it is the need of the current scenario to define some regulatory regime or policy to harness the enormous potential of energy savings. Under the Energy Conservation Act 2001, the Government of India under the Bureau of Energy Efficiency launched the Energy Conservation Building Code (ECBC) on a voluntary basis. ECBC sets the standards of minimum energy performance for “large commercial buildings. These norms were for both new and existing buildings. Retrofitting of existing buildings offers noteworthy opportunities for reducing global energy consumption and greenhouse gas emissions. This paper provides a systematic approach to review the application of energy conservation building codes in existing buildings and identification of the best retrofit strategies to stimulate the implementation of ECBC in the country.

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Section: ) Building Performance Assessmentmentioning

confidence: 99%

Retrofit Strategy in Existing Building for Implementing Energy Conservation Building Code in India

Berwal

Yadav

2021

EJERS

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“…The impact of wind speed on the absorption of heat flow; on the outer surfaces of the structure was investigated. The outcomes recommend that wind speed significantly impacts the absorption of heat transition on the outside phase of the building (Yadav and Berwal 2021). The thermal performance of the exterior is also influenced by the wall's orientation (Coley and Kershaw 2010).…”

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confidence: 96%

A comparative study on regression model and artificial neural network for the prediction of wall temperature in a building

Aishwarya¹,

Balasubramanian

2022

JER is an international, peer-reviewed journal that publishes f

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This paper demonstrates the validation and prediction of the wall temperature of a building exposed to a composite climate. Two artificial intelligence models, such as multiple linear regression and artificial neural networks, have been used to predict. The wall temperature has been predicted mainly based on the parameters like ambient temperature, wind speed and relative humidity in all four directions of the buildings. Three statistical analyses were used to validate the model's outcome: R-Squared, Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). In terms of train and control data, the two models yield comparable findings. The artificial neural network model has more adaptability since it was able to adjust to unexpected changes in the input data, according to a comparison of the applied mathematics of each model. The regression model was used for this investigation because it gives constant estimate values for the factors, though the neural model isn't numerically characterized. The review infers that the neural model must be utilized as an additional way to predict the wall temperature. This study can plan and adapt buildings for future work, considering the most critical climatic conditions. It also assists architects and engineers in determining the appropriate insulation for the building envelope, which improves its thermal performance.

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Exploring the effect of longwave radiation exchange on the energy balance of building façades in subtropical regions

Zhao

Zhang

2023

Building and Environment

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Predicting building wall temperature in composite climate using regression models: A comparative study

Cited by 4 publications

References 32 publications

Retrofit Strategy in Existing Building for Implementing Energy Conservation Building Code in India

Retrofit Strategy in Existing Building for Implementing Energy Conservation Building Code in India

A comparative study on regression model and artificial neural network for the prediction of wall temperature in a building

Exploring the effect of longwave radiation exchange on the energy balance of building façades in subtropical regions

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