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在实际决策过程中,二元语义分析方法被广泛地应用于求解基于语言评价信息的多属性决策问题。针对二元语义分析方法中评价信息表示形式变换的过程,指出二元语义分析方法是将模糊语言标度转换1~n数字标度,该转换造成了信息提取与合成的失真;阐述了标度选择的重要性以及指数标度的优良性质,建立利用指数标度改进二元语义表示模型,实验结果表明该改进模型可以有效降低信息集结过程中的信息扭曲和损失。
In the actual decision-making process, binary semantic analysis method is widely used to solve multi-attribute decision-making problems based on language evaluation information. Aiming at the process of evaluating information representation transformation in binary semantic analysis method, it is pointed out that the binary semantic analysis method is to convert the fuzzy language scale from 1 to n digital scale, which leads to the distortion of information extraction and synthesis. The importance of the choice and the good nature of the index scale. The index scale is used to improve the binary semantic representation model. The experimental results show that the improved model can effectively reduce the information distortion and loss in the process of information aggregation.