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Probabilistic Linguistic Linear Least Absolute Regression for Fashion Trend Forecasting

机译:时尚趋势预测的概率语言线性最不绝对消退

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摘要

Fashion trend is an important aspect in costume designing given that the correct fashion trend prediction can help productions to occupy markets in short time. In the methods of forecast, fuzzy linear least absolute regression is a useful model. Meanwhile, most descriptions about the fashion trend are in nature words which are difficult to be used directly in present models. To deal with this problem, the probabilistic linguistic term set, a powerful tool in expressing and computing nature language, is introduced in this paper. First, operations on probabilistic linguistic term sets are modified to be more logical in the solution procedure of regression. Then a novel model which combines fuzzy linear least absolute regression and probabilistic linguistic term set is developed. Finally, an illustration about the forecast of clothing fashion trend is given to show the applicability of our method in costume designing evaluation.
机译:时尚趋势是服装设计的一个重要方面,因为正确的时尚潮流预测可以帮助在短时间内占据市场的制作。在预测方法中,模糊线性最不绝对回归是一个有用的模型。与此同时,大多数关于时尚趋势的描述都处于自然词语中,难以直接在现有模型中使用。为了解决这个问题,本文介绍了概率语言术语集,表达和计算自然语言的强大工具。首先,在回归解决过程中,修改了关于概率语言术语集的操作。然后,开发了一种结合模糊线性最小绝对回归和概率语言术语集的新型模型。最后,给出了关于服装时尚趋势预测的插图,以表明我们在服装设计评估中的方法的适用性。

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