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Fuzzy subtractive clustering based prediction model for brand association analysis

机译:基于模糊减法聚类的品牌关联分析预测模型

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The brand is one of the crucial elements that determine the success of a product. Consumers in determining the choice of a product will always consider product attributes (such as features, shape, and color), however consumers are also considering the brand. Brand will guide someone to associate a product with specific attributes and qualities. This study was designed to identify the product attributes and predict brand performance with those attributes. A survey was run to obtain the attributes affecting the brand. Subtractive Fuzzy Clustering was used to classify and predict product brand association based aspects of the product under investigation. The result indicates that the five attributes namely shape, ease, image, quality and price can be used to classify and predict the brand. Training step gives best FSC model with radii (ra) = 0.1. It develops 70 clusters/rules with MSE (Training) is 9.7093e-016. By using 14 data testing, the model can predict brand very well (close to the target) with MSE is 0.6005 and its’ accuracy rate is 71%.
机译:品牌是决定产品成功的关键要素之一。消费者在确定产品选择时将始终考虑产品属性(例如功能,形状和颜色),但消费者也在考虑品牌。品牌会引导某人将产品与特定的属性和品质相关联。这项研究旨在识别产品属性并通过这些属性预测品牌表现。进行了一项调查以获得影响品牌的属性。减法模糊聚类用于对所调查产品的基于产品品牌关联的方面进行分类和预测。结果表明,形状,易用性,形象,质量和价格这五个属性可以用来对品牌进行分类和预测。训练步骤可提供半径(ra)= 0.1的最佳FSC模型。它开发了70个群集/规则,MSE(培训)为9.7093e-016。通过14次数据测试,该模型可以很好地预测品牌(接近目标),MSE为0.6005,准确率为71%。

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