【摘要】：猶豫模糊語(yǔ)言術(shù)語(yǔ)集能夠靈活、全面地反映決策者的定性決策信息,在供應(yīng)鏈管理、模式識(shí)別和醫(yī)療診斷等領(lǐng)域具有廣泛的應(yīng)用前景,已成為模糊集理論研究中的熱點(diǎn).熵是用來衡量模糊信息的不確定性,是模糊集理論中一個(gè)重要研究?jī)?nèi)容.本論文研究猶豫模糊語(yǔ)言術(shù)語(yǔ)集和帶概率的猶豫模糊語(yǔ)言術(shù)語(yǔ)集的熵,并提出一種基于熵測(cè)度和離平均方案(平均解)距離(EDAS)的猶豫模糊語(yǔ)言多屬性決策方法.本文一共分為三章.第一章,介紹猶豫模糊語(yǔ)言術(shù)語(yǔ)集和帶概率的猶豫模糊語(yǔ)言術(shù)語(yǔ)集及其熵理論的研究背景、發(fā)展現(xiàn)狀及相關(guān)的預(yù)備知識(shí).第二章,研究猶豫模糊語(yǔ)言術(shù)語(yǔ)集的熵和基于熵的EDAS決策方法.首先定義猶豫模糊語(yǔ)言術(shù)語(yǔ)集的模糊性指標(biāo)和猶豫性指標(biāo),并在此基礎(chǔ)上給出猶豫模糊語(yǔ)言術(shù)語(yǔ)集的二元熵(包含模糊熵和猶豫熵)的公理化定義,給出構(gòu)建模糊熵和猶豫熵的一般方法和具體的熵公式.之后,提出一個(gè)綜合熵公式,該公式能夠綜合反映猶豫模糊語(yǔ)言術(shù)語(yǔ)集的模糊性和猶豫性特征.對(duì)提出的熵公式,結(jié)合具體的數(shù)據(jù)與現(xiàn)有的熵公式進(jìn)行了比較,說明其合理性與優(yōu)越性.最后,提出一種基于熵和EDAS的決策方法,用以解決屬性權(quán)重未知的猶豫模糊語(yǔ)言多屬性決策問題.第三章,研究帶概率的猶豫模糊語(yǔ)言術(shù)語(yǔ)集的熵.提出帶概率的猶豫模糊語(yǔ)言術(shù)語(yǔ)集的熵的公理化定義,并給出熵公式的構(gòu)造方法和具體的熵公式.提出的熵公式既能反映帶概率的猶豫模糊語(yǔ)言術(shù)語(yǔ)集的模糊性,又能反映其猶豫性,因此能全面地刻畫其不確定性.最后,用具體的多屬性決策實(shí)例說明所提出的熵公式在多屬性群決策中的應(yīng)用.
[Abstract]:The term set of hesitating fuzzy language can flexibly reflect the qualitative decision information of decision makers. It has wide application prospects in the fields of supply chain management, pattern recognition and medical diagnosis, and has become a hot spot in the research of fuzzy set theory. Entropy is used to measure the uncertainty of fuzzy information and is an important research content in fuzzy set theory. In this paper, we study the entropy of the hesitancy fuzzy language terminology set and the hesitant fuzzy language terminology set with probability, and propose a multi-attribute decision making method based on entropy measure and distance from the average solution (EDAS). This paper is divided into three chapters. In the first chapter, we introduce the background, the present situation and the related preparatory knowledge of the hesitant fuzzy language terminology set and the probabilistic hesitant fuzzy language terminology set and its entropy theory. In chapter 2, the entropy of hesitant fuzzy terminology set and the EDAS decision method based on entropy are studied. Firstly, the fuzziness index and hesitancy index of hesitating fuzzy language terminology set are defined, and then the axiomatic definition of binary entropy (including fuzzy entropy and hesitating entropy) of hesitant fuzzy language terminology set is given. The general method of constructing fuzzy entropy and hesitating entropy and the specific entropy formula are given. After that, a comprehensive entropy formula is proposed, which can reflect the fuzziness and hesitancy characteristics of the hesitant fuzzy language terminology set. The proposed entropy formula is compared with the existing entropy formula in combination with the specific data, which shows its rationality and superiority. Finally, a decision method based on entropy and EDAS is proposed to solve the problem of uncertain fuzzy language multi-attribute decision making with unknown attribute weight. In chapter 3, we study the entropy of the hesitant fuzzy language terminology set with probability. The axiomatic definition of entropy in the set of hesitant fuzzy terms with probability is proposed, and the method of constructing entropy formula and the specific entropy formula are given. The proposed entropy formula can not only reflect the fuzziness of the set of hesitant fuzzy terms with probability, but also reflect its hesitancy, so it can describe its uncertainty comprehensively. Finally, an example of multi-attribute decision making is given to illustrate the application of the proposed entropy formula in multi-attribute group decision making.
【學(xué)位授予單位】：揚(yáng)州大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：O159;O225

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