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

机译:利用人工学习算法和模糊逻辑的房地产评估土木工程检验

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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.
机译:土木工程专家开展的建筑物的技术检验可以识别和分类房地产的物理条件;这为用户的保护和安全产生了相关信息。鉴于财产的真实条件,以及房地产估值宇宙,使用人工智能和模糊逻辑,可以获得与建筑物的物理条件相关的市场价格。该实验的目的是使用与人工智能相关的土木工程检验形式进行物业评估模型,以及模糊逻辑,并与市场价值进行比较,以验证此检查形式的适用性。因此,所用方法是基于土木工程技术检验,了根据葡萄牙使用的模型,适应拉脱维亚的现实。从该报告获取数据后应用人工智能。由此,获得了关联规则,其用于漫反射逻辑,以获得每平方米公寓的价格,并与市场价值进行比较。为此,使用了48个住宅公寓,位于拉脱维亚市的Jelgava市,从10月到2019年12月进行了检查。主要结果是9%误差度量,这表明了应用该方法的可能性提出的方法在这个实验中。因此,对于每个公寓样本咨询,它导致了保护状态和相关的市场价值。

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