Developing a machine learning-based building repair time estimation model considering weight assigning methods

Kwon, Nahyun; Ahn, Yonghan; Son, Bo-Sik; Moon, Hyosoo

doi:10.1016/j.jobe.2021.102627

Cited by 9 publications

(4 citation statements)

References 45 publications

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“…After double logarithm: Y0 = 3,0000; Y1 = 1,5000; Y2 = 0,7725; Y3 = 0,0057; Y4 = -0,4759. Substituting the corresponding values into expression (9), we obtain a system of equations: {𝑎𝑎 0 + 𝑎𝑎 1 • 𝑌𝑌 н 𝑚𝑚𝑎𝑎𝑥𝑥 = 1, 5000, 𝑎𝑎 0 + 𝑎𝑎 1 • 𝑌𝑌 н 𝑚𝑚𝑖𝑖𝑛𝑛 = 0, 0057. Solving the system of equations, substituting instead of the maximum value of 𝑌𝑌 н 𝑚𝑚𝑎𝑎𝑥𝑥 the points obtained during the survey (9,5), instead of the minimum value (3,2), we 𝑌𝑌 н 𝑚𝑚𝑖𝑖𝑛𝑛 obtain a formula for converting natural parameters into particular desirability: ) ) ( )…”

Section: Practical Application Of the Results Obtained To Assess The ...mentioning

confidence: 99%

“…[6] A review of foreign sources on the issue of capital repairs of apartment buildings as the main direction of research revealed the topic of energy efficiency of the activities carried out [7]. There are works devoted to multi-criteria evaluation of contractors [8], as well as the development of models for estimating the time of building repairs based on machine learning [9].…”

Section: Introductionmentioning

confidence: 99%

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Methodological approaches to the assessment of public opinion during the overhaul of apartment buildings

Kornilova,

Ermakov,

Baulin

2023

E3S Web Conf.

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In the article, using the example of a survey of residents of apartment houses (AH) on the quality of capital repairs, methodological approaches to assessing public opinion are considered. Processing the results of the survey showed that the definition of the coefficient of concordance is insufficient. It is shown that in order to assess the reliability of surveys conducted by the Delphi method, one should focus on achieving a greater confidence probability, and not on the value of the concordance coefficient. The survey showed that the priority factor for residents of apartment buildings of all ages and genders when assessing major repairs is the use of quality materials. For women of all ages, the issue of the cost of repairs was very important. Its importance for this group of respondents turned out to be almost at the level of the importance of the quality of materials. For the practical application of the results obtained, the weight coefficients of each studied factor were calculated for the total sample of respondents, which made it possible to create a methodology for express assessment of the quality of ongoing overhauls based on Harrington's verbal-numerical scales.

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Section: Practical Application Of the Results Obtained To Assess The ...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Methodological approaches to the assessment of public opinion during the overhaul of apartment buildings

Kornilova,

Ermakov,

Baulin

2023

E3S Web Conf.

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“…Numerous studies have proved the predictive power of regression models. Building repair time estimation is also representing high importance considering the increase in deteriorating buildings [9]. Sajjad et al [10] proposed three buildings energy consumption prediction by a unique multioutput (MO) sequential learning model predicting heating and cooling loads also.…”

Section: Related Workmentioning

confidence: 99%

Applicability of Multivariate Linear Regression in Building Energy Demand Estimation

Storcz¹,

Kistelegdi²,

Horváth³

et al. 2022

MMEP

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The vision of the research project is to find an energy optimal building configuration, suitable for specified requirements and restrictions. The first step on this way is to create a measure to compare building configurations, faster than explicit energetic simulations. The current study examines the applicability of multivariate linear regression to support the solution of building optimization problems. During the study, multivariate linear regression models were created to estimate the expected annual heating energy demand of building configurations and examined their accuracy Between examinations, the models were modified so that the complexity was increased only to such an extent that the approximation was still sufficiently accurate. The result was a multivariate linear model that estimated the expected output for unknown descriptive variables with a 0% relative error and a 1.6% standard deviation. The R2 point of the estimates was 0.9884. Based on these, the model was considered applicable in the search space defined by the training patterns.

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“…Park et al [38] proposed a case-based reasoning-based model to estimate the time at which the first repair was needed after the completion of construction, even in phases in which maintenance-related information was scarce. Kwon et al [39] developed a model for the prediction of the repair time for the building type based on the application of a genetic algorithm, multiple linear regression analysis, feature counting method, and fuzzy analytical hierarchy process to case-based reasoning. However, these studies only targeted specific building components or had limitations associated with various uncertainties during the building maintenance phase.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of the Repair Time of Finishing Works Using a Probabilistic Approach for Efficient Residential Buildings Maintenance Strategies

Cho

Lee

et al. 2021

Sustainability

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In general, the long-term maintenance planning of residential buildings is performed based on uniform repair times. However, in fact, various factors, such as the quality and user patterns, affect the performance of residential building components in the Operation and Maintenance (O&M) phase. Hence, various residential building components are repaired at uncertain times, acting as a risk for the residential building maintenance plan. Therefore, an efficient maintenance plan should be established considering maintenance uncertainty. In this regard, this study aims to analyze the uncertainty of repair times for various finishing works in residential buildings based on a probabilistic methodology and outline the implications for the establishment of efficient maintenance strategies in these buildings. Hence, 47,344 repair data for 63 buildings in 12 public residential building complexes completed between 1991 and 2001 in the Republic of Korea were used for analysis. Before the analysis, a repair time matrix was constructed by classifying the finishing works in 25 types and setting service life times to 6–26 years. The repair time distribution for each finishing work was then derived. Results confirmed that basic repair time setting can be performed and various information for reasonable maintenance decision making regarding each finishing work can be provided through a probabilistic approach. The probabilistic approach can be used as a critical decision-making method because there is uncertainty associated with the repair time of each finishing work owing to the performance degradations of various finishing works due to complex causes. Although this study focused on repair time owing to data collection limitations, maintenance strategies with strategic flexibility can be established by developing probabilistic methods that simultaneously consider frequency and cost by securing additional high-quality cost data.

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Developing a machine learning-based building repair time estimation model considering weight assigning methods

Cited by 9 publications

References 45 publications

Methodological approaches to the assessment of public opinion during the overhaul of apartment buildings

Methodological approaches to the assessment of public opinion during the overhaul of apartment buildings

Applicability of Multivariate Linear Regression in Building Energy Demand Estimation

Analysis of the Repair Time of Finishing Works Using a Probabilistic Approach for Efficient Residential Buildings Maintenance Strategies

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