Simplified Characterization of Building Thermal Response Rates

Dong, Ziqian; Zhu, Pai; Bobker, Michael; Ascazubi, Marco

doi:10.1016/j.egypro.2015.11.098

Cited by 7 publications

(3 citation statements)

References 7 publications

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“…Resulting signs of partial tolerances can be different and effects of changes may be compensated to a certain extent (Dong et al, 2015). The worst scenario occurs when all partial tolerances of the same signs are added.…”

Section: Sensitivity Analysis In Research Of Construction Of Agricultmentioning

confidence: 99%

Sensitivity Analysis in Research of Construction of Agricultural Buildings Focused on Poultry Farming

Malinovský

2019

AOL

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Both heat comfort and energy saving represent important parameters of agriculture buildings environment. Selecting material composition for perimeter walls (in course of both new building construction and reconstruction of existing ones) can aid to eliminate heat load of interior environment. Non-stationary processes taking place in building constructions in connection with building interaction with exterior environment and installed ventilating and heating systems are affected by a number of factors that can be well modelled by help of simulation methods and verified by experimental measuring. This work deals with analysing building construction from viewpoint of material used materials and changing their different physical parameters in order to achieve an optimal perimeter construction composition for agriculture building with regard to poultry farms.

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Section: Sensitivity Analysis In Research Of Construction Of Agricultmentioning

confidence: 99%

Sensitivity Analysis in Research of Construction of Agricultural Buildings Focused on Poultry Farming

Malinovský

2019

AOL

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“…Many software products have been developed based on physical models, including EnergyPlus, DOE-2, TRNSYS, and eQUEST [9]. However, physical models present some deficiencies such as professional knowledge requirements, and the high costs of data collection and computation [10]. For green buildings with many energysaving technologies, many systems are involved.…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Study on Integrating Clustering with Regression for Short-Term Forecasting of Building Energy Consumption: Case Study of a Green Building

Ding

Wang

Hu³

et al. 2022

Buildings

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Integrating clustering with regression has gained great popularity due to its excellent performance for building energy prediction tasks. However, there is a lack of studies on finding suitable regression models for integrating clustering and the combination of clustering and regression models that can achieve the best performance. Moreover, there is also a lack of studies on the optimal cluster number in the task of short-term forecasting of building energy consumption. In this paper, a comprehensive study is conducted on the integration of clustering and regression, which includes three types of clustering algorithms (K-means, K-medians, and Hierarchical clustering) and four types of representative regression models (Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Regression (SVR), Artificial Neural Network (ANN), and extreme gradient boosting (XGBoost)). A novel performance evaluation index (PI) dedicated to comparing the performance of two prediction models is proposed, which can comprehensively consider different performance indexes. A larger PI means a larger performance improvement. The results indicate that by integrating clustering, the largest PI for SVR, LASSO, XGBoost, and ANN is 2.41, 1.97, 1.57, and 1.12, respectively. On the other hand, the performance of regression models integrated with clustering algorithms from high to low is XGBoost, SVR, ANN, and LASSO. The results also show that the optimal cluster number determined by clustering evaluation metrics may not be the optimal number for the ensemble model (integration of clustering and regression model).

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“…For easy computer algorhitmizing, characteristics of the time heat responses are "harmonized" by use of the Fourier transformation (Bracewell, 1999). The model environment is described by help of the finite element method with composed parameters (thermal conductivity, thermal capacity, temperature controlled heat flow sources) and elements with spread parameters (where geometric dimensions do not allow to consider insulation resistance and thermal capacity as separate parameters) (Dong et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

System Macromodel of Agricultural Building with Aim to Energy Consumption Minimization

Malinovský

2018

AOL

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Economizing on energy intended for heating of agricultural buildings is correlative with their convenient construction from the viewpoint of both thermal and mechanical properties. Therefore, knowledge of temperature time characteristics enables building construction optimizing. This paper deals with process of recognizing elements and parameters of some particular building object, assembling its system macromodel, and analysing temperature time characteristics on its base using appropriate mathematic tools (Laplace and Fourier transformation, matrix characterizing of model parameters) and special software (ANATH). Finally, the resulting temperature time characteristics can be used for an optimal design of some planned agricultural object or for reconstruction of some existing one. KeywordsEconomy of agricultural engineering, heating energy economy, system analysis, temperature time characteristics, expenses optimizing, ambient temperature well-being.

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Simplified Characterization of Building Thermal Response Rates

Cited by 7 publications

References 7 publications

Sensitivity Analysis in Research of Construction of Agricultural Buildings Focused on Poultry Farming

Sensitivity Analysis in Research of Construction of Agricultural Buildings Focused on Poultry Farming

A Comprehensive Study on Integrating Clustering with Regression for Short-Term Forecasting of Building Energy Consumption: Case Study of a Green Building

System Macromodel of Agricultural Building with Aim to Energy Consumption Minimization

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