發(fā)布時(shí)間：2018-04-18 11:19

  本文選題：綜合評(píng)價(jià)問題 + 服務(wù)滿意度��； 參考：《中國(guó)衛(wèi)生統(tǒng)計(jì)》2017年04期

【摘要】：正醫(yī)療衛(wèi)生領(lǐng)域常見多屬性決策或多指標(biāo)評(píng)價(jià)問題~([1]),傳統(tǒng)模型適用于客觀屬性或指標(biāo)情況,以精確實(shí)數(shù)為測(cè)度信息設(shè)計(jì)建模方案~([2-3]),主觀屬性或指標(biāo)測(cè)度適于模糊數(shù)描述,而傳統(tǒng)模型不適于這類模糊信息計(jì)算。Zadeh提出模糊集合(Fuzzy集),基于此的模糊綜合評(píng)判模型~([4-5])用于單隸屬度邏輯運(yùn)算簡(jiǎn)單而粗糙。Gau和Buehrer對(duì)其改進(jìn)并提出Vague集,兼顧隸屬度、非隸屬度和猶豫度,對(duì)模糊信息描述更為全
[Abstract]:The traditional model is suitable for the objective attribute or index case, the accurate real number is used as the measure information to design the modeling scheme ([2-3]), the subjective attribute or the index measure is suitable for the fuzzy number description, the traditional model is suitable for the objective attribute or the index evaluation problem ([2-3]), the subjective attribute or the index measure is suitable for the fuzzy number description.The traditional model is not suitable for this kind of fuzzy information calculation. Zadeh puts forward the fuzzy set of fuzzy sets. The fuzzy comprehensive evaluation model based on this model ([4-5]) is used for the simple logic operation of single membership degree and the improvement of rough. Gau and Buehrer for its Vague set, which takes into account the membership degree.Non-membership degree and hesitation degree, more complete description of fuzzy information
【作者單位】： 濰坊醫(yī)學(xué)院公共衛(wèi)生與管理學(xué)院;"健康山東"重大社會(huì)風(fēng)險(xiǎn)預(yù)測(cè)與治理協(xié)同創(chuàng)新中心;
【基金】：教育部人文社科基金(15YJCZH087) 濰坊醫(yī)學(xué)院公派教師訪學(xué)項(xiàng)目(2016-25) 山東自然科學(xué)基金(ZR2015HL101) 中華醫(yī)學(xué)會(huì)醫(yī)學(xué)教育項(xiàng)目(2016A-RW007)
【分類號(hào)】：O159;R197.1

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