基于情绪感知的语言多属性决策方法

情绪对于决策有着重要影响,由于缺乏有效的决策者情绪状态获取方法,当前考虑情绪状态的语言多属性决策方法研究偏少.随着物联网技术的发展,通过可穿戴传感器能够便捷地获取决策者脑电信号,进而可感知其情绪状态.为此,研究基于情绪感知的语言多属性决策方法.首先,提出基于SVM概率输出模型的情绪感知方法,根据决策者脑电信号,实时、准确感知决策者情绪状态的概率分布;其次,提出基于云模型的语言评价定量化方法,一方面考虑语言评价的模糊性与随机性,另一方面考虑决策者情绪状态因素,定量化语言评价;然后,提出基于前景理论的方案排序方法,在情绪泛化假设下,根据综合前景值将各方案排序;最后,通过实例验证该决策方法的可行性和有效性.

Linguistic multi-criteria decision-making method based on emotion perception

Emotions have an important influence on decision-making. However, due to the limitation of acquisition methods for emotional state, there is little research currently about the linguistic multi-criteria decision-making method considering the influence of emotion state. With the development of Internet of things technology, wearable sensors can easily acquire decision makers'' electroencephalogram(EEG) signals and then perceive their emotion states. Therefore, a linguistic multi-attribute decision-making method based on emotion perception is studied. Firstly, an emotion perception method based on the SVM probability output model is proposed. According to the EEG signals of decision makers, the emotional state probability distribution can be obtained accurately in real time. On this basis, a quantitative method of linguistic assessment based on a cloud model is proposed. Considering the fuzziness and randomness of linguistic assessment as well as emotional factors, the linguistic assessment is quantified. Then, the scheme sorting method based on the prospect theory is proposed. On the basis of affective generalization hypothesis, the comprehensive prospect values are calculated and the schemes are sorted. Finally, the feasibility and effectiveness of the proposed method are illustrated by examples.