Civil Engineering Inspection for Real Estate Evaluation with the Use of Artificial Learning Algorithms and Fuzzy Logic

Q4 Social Sciences
Vladimir Surgelas, I. Arhipova, V. Pukite
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引用次数: 0

Abstract

Abstract The technical inspection of a building carried out by an expert in civil engineering can identify and classify the physical conditions of the real estate; this generates relevant information for the protection and safety of users. Given the real conditions of the property, and for the real estate valuation universe, using artificial intelligence and fuzzy logic, it is possible to obtain the market price associated with the physical conditions of the building. The objective of this experiment is to develop a property evaluation model using a civil engineering inspection form associated with artificial intelligence, and fuzzy logic, and also compare with market value to verify the applicability of this inspection form. Therefore, the methodology used is based on technical inspection of civil engineering regarding the state of conservation of properties according to the model used in Portugal and adapted to the reality of Latvia. Artificial intelligence is applied after obtaining data from that report. From this, association rules are obtained, which are used in the diffuse logic to obtain the price of the apartment per square meter, and for comparison with the market value. For this purpose, 48 samples of residential apartments located in the city of Jelgava in Latvia are used, with an inspection carried out from October to December 2019. The main result is the 9% error metric, which demonstrates the possibility of applying the method proposed in this experiment. Thus, for each apartment sample consulted, it resulted in the state of conservation and a market value associated.
基于人工学习算法和模糊逻辑的土木工程房地产评估检测
土木工程专家对建筑物进行技术检验,可以对房地产的物理状况进行识别和分类;这就产生了保护用户安全的相关信息。考虑到物业的实际情况,以及房地产估值领域,使用人工智能和模糊逻辑,可以获得与建筑物物理条件相关的市场价格。本实验的目的是利用人工智能和模糊逻辑相结合的土建工程检验表,开发一个属性评估模型,并与市场价值进行对比,验证该检验表的适用性。因此,所使用的方法是根据葡萄牙使用的模型对财产保护状况进行土木工程技术检查,并适应拉脱维亚的实际情况。从该报告中获取数据后应用人工智能。由此得到关联规则,在漫射逻辑中使用关联规则来获得公寓每平方米的价格,并与市场价值进行比较。为此,使用了位于拉脱维亚耶尔加瓦市的48个住宅公寓样本,并于2019年10月至12月进行了检查。主要结果是9%的误差度量,这证明了应用本实验提出的方法的可能性。因此,对于每个公寓样本,它得出了保护状态和相关的市场价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Rural Sustainability Research
Rural Sustainability Research Social Sciences-Geography, Planning and Development
CiteScore
1.40
自引率
0.00%
发文量
0
审稿时长
9 weeks
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