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An Extended Version of the Fuzzy-Euclidean Intelligent Fitness Model (FEIFM) Implementation for Selecting Personal Vehicle

机译:选择个人车辆的模糊欧氏智能健身模型(FEIFM)实现的扩展版本

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摘要

Indeed, intelligent model is a sub-domain in computer science that its purposes utilized in numerous pieces of reality. Particularly in case of automotive industry, to select the most appropriate personal vehicle is challenging for the customers. The challenge was taken as a main problem of this study. In this research, the reasonableness is characterized by the customer parameters which portray the customer's identity. By utilizing the mix technique for fuzzy-logic and Euclidean distance calculation, the customer's identities are fitted into the personal-vehicle parameters. At long last, the constructed model for choosing personal vehicle plays several customer's parameters; e.g., age, gender, education, income and job. The model designed thru utilizing the object-oriented methodology. The result of simulation of 66 purchasers and 44 conceivable vehicles are able to propose the most reasonable vehicle for every purchaser. As an extended version, the model successfully delivers the completed scheme due to added parameters and method. It is a truthful contribution provided by this research.
机译:确实,智能模型是计算机科学的一个子领域,其目的已在众多现实中得到利用。特别是在汽车工业中,选择最合适的个人车辆对客户来说是一项挑战。挑战被视为这项研究的主要问题。在这项研究中,合理性的特征在于刻画客户身份的客户参数。通过将混合技术用于模糊逻辑和欧几里德距离计算,将客户的身份拟合到个人车辆参数中。最终,用于选择个人车辆的构建模型具有多个客户的参数。例如年龄,性别,教育程度,收入和工作。该模型通过使用面向对象的方法进行设计。 66个购买者和44个可以想象的车辆的仿真结果能够为每个购买者提供最合理的车辆。作为扩展版本,由于添加了参数和方法,该模型成功交付了完整的方案。这是这项研究提供的真实的贡献。

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