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中文摘要：
为了在产品设计过程中更准确地理解顾客需求,给设计提供可靠的决策依据,设计人员不仅需要确定顾客需求当前的权重,更需要预测其未来的权重,以便掌握其动态趋势。针对当前顾客需求未来权重预测和动态趋势分析研究较少的情况,提出了基于变精度粗糙集和最小二乘支持向量机回归理论的集成方法,来预测顾客需求的未来权重。该方法首先利用变精度粗糙集的β分类精度方法计算了顾客需求权重;然后周期性地计算每项顾客需求权重以构建权重时间序列,引入最小二乘支持向量机回归理论对顾客需求权重时间序列进行处理,从而确定预测模型的具体表达式,进行权重预测,并通过历史的、当前的和预测的权重数据,构建顾客需求权重的动态趋势直方图,以便分析。以大倾角带式输送机为例,对该集成方法的可行性和有效性进行了说明。
英文摘要：
To understand the customers＇ requirements more accurate and provide reliable decision-making in product design process,the product designers needed to determine not only the current weight of customers＇ requirements but also predicted the future weight so as to master the dynamic trend of customers＇ requirements.At present,there were few studies on predicting future weight of customers＇ requirements and dynamic trend analysis.Aiming at this problem,an integrated method based on the preprocessing of Variable Precision Rough Set（VPRS）and Least Squares Support Vector Machines（LS-SVM） regression theory was presented to predict the weight of customer requirements.In this method,the weight of customers＇ requirements was calculated firstly based on β-classification accuracy method of VPRS,and then the time sequence weight was constructed by calculating each customer equariment weight periodically.The LS-SVM regression theory was introduced to process time sequence of customers＇ requirements weight so as to determine concrete representation of prediction model.According to the historical,current and future weight of customers＇ requirements,the dynamic trend column diagram of customers＇ requirements was constructed for analysis.A case study of high-angle belt conveyor was provided to prove the feasibility and effectiveness of the proposed method.
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