Knowledge-Based Fis and Anfis Models Development and Comparison for Residential Real Estate Valuation

Yalpır, Şükran; Özkan, Gülgün

doi:10.3846/ijspm.2018.442

Cited by 15 publications

(8 citation statements)

References 22 publications

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“…The authors measured the absolute mean error. This revealed a high accuracy of the obtained results and indicated the possibility of using the fuzzy model in property valuations in Turkey (Yalpir, Ozkan, 2018). From this, the first method used to evaluate was the comparative method of market data using statistical inferences and the second method is fuzzy logic.…”

Section: Introductionmentioning

confidence: 65%

Improvements in the civil engineering focused on the real estate appraisal with the use of artificial intelligence and fuzzy logic

2020

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In the field of civil engineering, there are some traditional methods of property evaluation that deal with these techniques. However, there is controversy about what would bring the best performance, a greater degree of ease and clarity without presenting multicollinearity. This controversy is due to the difficulty of finding appropriate predictive variables in real estate valuation since they often do not fit the binary model, involving human subjectivity. From this, the research aims to propose improvements in the property evaluation process with the use of artificial intelligence without presenting the effects of multicollinearity and autocorrelation, to predict the value of the real estate market. The object of study is a standard 2-bedroom residential apartment with 48m-2 located in the central area of Jelgava, Latvia, in October 2019. Therefore, the methodology uses statistical inference as an initial analysis parameter and the fuzzy logic incorporates the best association rules which are originated from artificial intelligence extracted from the apriori algorithm. Finally, the results obtained by regression and fuzzy were compared with the value in euros m-2, according to the official publication of the government of Latvia, referring to the market value of a 2-bedroom residential apartment in the city of Jelgava, Latvia, in October 2019, this government publication is the reference for this study. The statistical hypotheses that allowed its validation were accepted. In the Fuzzy model, the results indicated an excellent equivalence to market prices in relation to the traditional valuation process.

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Section: Introductionmentioning

confidence: 65%

Improvements in the civil engineering focused on the real estate appraisal with the use of artificial intelligence and fuzzy logic

2020

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“…, 2008; Belniak and Wieczorek, 2017; Watkins, 1999; Arribas et al. , 2016; Wyatt, 1997; Yalpir and Ozkan, 2018; Liu et al. , 2018b; Abidoye and Chan, 2018a, b; Francke and Vos, 2004).…”

Section: Existing Studies and Challengesmentioning

confidence: 99%

BIM and real estate valuation: challenges, potentials and lessons for future directions

Jafary¹,

Shojaei

Rajabifard

et al. 2022

ECAM

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PurposeBuilding information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices.Design/methodology/approachThis paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022.FindingsFour domains of application have been identified: (1) developing machine learning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes; (2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models; (3) employing BIM for accurate estimation of components of cost approach-based valuation practices; and (4) extraction of useful visual features for real estate valuation from BIM representations instead of 2D images through deep learning and computer vision.Originality/valueThis paper contributes to research efforts on utilization of 3D modeling in real estate valuation practices. In this regard, this paper presents a broad overview of the current applications of BIM for valuation procedures and provides potential ways forward for future investigations.

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“…Adaptive neuro-fuzzy inference system (ANFIS) integrated the advantages of both neural networks and fuzzy logic systems with high self-adaptability and self learning ability to be identified as a universal estimator for responding to complex problems [16]. The ANFIS was a class of adaptive, multi-layer and feed-forward networks which was comprised of input-output varioubs and a fuzzy rule base of the Takagi-Sugeno type [21].…”

Section: Conceptionmentioning

confidence: 99%

“…In recent years, adaptive neural-fuzzy inference system (ANFIS) combined with both learning and reasoning capability of artificial neural network and fuzzy logic has been developed for solving the complex problems [16]. Akbarpour proposed an ANFIS model to predict the punching shear strength of two-way slabs based on 189 experimental results and found that the proposed model can evaluate the punching load with an acceptable error [17].…”

Section: Introductionmentioning

confidence: 99%

Compressive Strength Evaluation of Concrete Confined With Spiral Stirrups by Using Adaptive Neuro-fuzzy Inference System (ANFIS)

Chang¹,

Zheng²

2021

Preprint

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The compressive strength of concrete confined with spiral stirrups was an important parameter to evaluate the load-bearing capacity of concrete columns. The confinement provided by spiral stirrups let concrete under the triaxial compression state and improved the compressive strength of concrete. However, the relationships between concrete and stirrups were complex and the existing prediction models for evaluating the compressive strength of confined concrete were various. In this paper, an adaptive neural-fazzy inferenxe system (ANFIS) model was developed to evaluate the compressive strength of concrete confined with stirrups. A set of 231 experimental results of concrete confined with spiral stirrups were collected from the previous studies to establish a reliable database. The investigated parameters included the aspect ratio of specimens, the diameter, spacing, yield strength, and volumetric ratio of stirrups, the ratio of longitudinal reinforcement, and the compressive strength of concrete. The results showed that the ANFIS model predicted the compressive strength of confined concrete accurately. By comparing with existing models, the proposed ANFIS model had high applicable and reliability. The effects of the investigated parameters on the compressive strength of concrete were analyzed based on the proposed ANFIS model.

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Knowledge-Based Fis and Anfis Models Development and Comparison for Residential Real Estate Valuation

Cited by 15 publications

References 22 publications

Improvements in the civil engineering focused on the real estate appraisal with the use of artificial intelligence and fuzzy logic

Improvements in the civil engineering focused on the real estate appraisal with the use of artificial intelligence and fuzzy logic

BIM and real estate valuation: challenges, potentials and lessons for future directions

Compressive Strength Evaluation of Concrete Confined With Spiral Stirrups by Using Adaptive Neuro-fuzzy Inference System (ANFIS)

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