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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

模糊期望值與模糊變異數的檢定方法 / Methods on Testing Hypotheses of Fuzzy Mean and Fuzzy Variance

張曙光, Shu-Kuang,Chang Unknown Date (has links)
在許多實際情形下,傳統的統計檢定方法是不足以應付的。故本論文提出模糊檢定方法,我們定義出模糊樣本期望值與模糊樣本變異數的計算方法,再針對不同的模糊資料,分別提出不同的檢定方法,去解決最實際需要解決的問題,其中包括推廣古典的統計檢定方法與自創的檢定方法。 關鍵字:隸屬度函數,模糊樣本取樣,模糊樣本期望值,模糊樣本變異數,人性思考,t檢定,F檢定,模糊常態分配。 / In many expositions of fuzzy methods, fuzzy techniques are described as an alternative to a more traditional statistical approach. In this paper, we present a class of fuzzy statistical decision process in which testing hypothesis can be naturally reformulated in terms of interval-valued statistics. We provide the definitions of fuzzy mean, fuzzy distance as well as investigation of their related properties. We also give some empirical examples to illustrate the techniques and to analyze fuzzy data. Empirical studies show that fuzzy hypothesis testing with soft computing for interval data are more realistic and reasonable in the social science research. Finally certain comments are suggested for the further studies. We hope that this reformation will make the corresponding fuzzy techniques more acceptable to researchers whose only experience is in using traditional statistical methods. Key words: Membership function, fuzzy sampling survey, fuzzy mean, human thought, t-test, F-test, normally distributed.
12

模糊線性迴歸之研究

趙家慶 Unknown Date (has links)
使用傳統迴歸的方式對未知事物做預測,往往不能夠精準的做出結論,縱使在相同的條件下實際去操作,也很難得到相同的結果,因此模糊數概念的建立,並運用在迴歸分析上更能有效描述預測結果的不確定性。然而模糊線性迴歸(Fuzzy Linear Regression)在利用最小平方法處理問題時,往往過於著重在模糊區間的中心與分展度上,而忽略了描述資料的模糊性,使得隸屬度函數(membership function)的功能受到相當大的限制。本文在D'Urso和Gastaldi(2000)所提出的雙重模糊線性迴歸(doubly fuzzy linear regression)模型架構下,利用Yang和Ko(1996)在LR空間下所定義模糊數間的距離公式,導出能反映隸屬度函數的最小平方估計,並引進一些傳統迴歸中常用來偵測離群值(outlier)與具影響力觀察值(influence observation)的概念與技巧,應用在模糊線性迴歸資料的偵測上。
13

模糊卡方適合度檢定 / Fuzzy Chi-square Test Statistic for goodness-of-fit

林佩君, Lin,Pei Chun Unknown Date (has links)
在資料分析上,調查者通常需要決定,不同的樣本是否可被視為來自相同的母體。一般最常使用的統計量為Pearson’s 統計量。然而,傳統的統計方法皆是利用二元邏輯觀念來呈現。如果我們想要用模糊邏輯的概念來做樣本調查,此時,使用傳統 檢定來分析這些模糊樣本資料是否仍然適當?透過這樣的觀念,我們使用傳統統計方法,找出一個能處理這些模糊樣本資料的公式,稱之為模糊 。結果顯示,此公式可用來檢定,模糊樣本資料在不同母體下機率的一致性。 / In the analysis of research data, the investigator often needs to decide whether several independent samples may be regarded as having come from the same population. The most commonly used statistic is Pearson’s statistic. However, traditional statistics reflect the result from a two-valued logic concept. If we want to survey sampling with fuzzy logic concept, is it still appropriate to use the traditional -test for analysing those fuzzy sample data? Through this concept, we try to use a traditional statistic method to find out a formula, called fuzzy , that enables us to deal with those fuzzy sample data. The result shows that we can use the formula to test hypotheses about probabilities of various outcomes in fuzzy sample data.
14

模糊時間數列的階次認定、模式建構及預測 / The Order Identification of Fuzzy Time Series, Models Construction and Forecasting

廖敏治 Unknown Date (has links)
本文將模糊理論的觀念,應用到時間數列分析上。研究重點包括模糊自相似度的定義與度量,模糊自迴歸係數的分析,模糊相似度辨識與自迴歸階次認定、模糊時間數列模式建構與預測等。我們首先給定模糊時間數列模式的概念與一些重要性質。接著提出模糊相似度的定義與度量,以及模式建構的流程。經由系統性的模擬與分析,我們建立階次認定的演算法則與認定程序。藉著詳細的演算比較這些類型的模糊時間數列。並以模糊關係方程式推導,提出合適的模糊時間數列模式建構方法。並利用提出的方法對台灣的景氣對策信號,及台灣結婚率建立模糊時間數列模式。最後,使用所建構的模糊時間數列模式對未來進行預測,以驗證所建構模糊時間數列模式的效率性與實用性。 / In modeling a time series the accuracy of various model constructions and forecasting techniques, certain rules and models are adhered to. Traditional methods on the model construction for a time series are based on the researchers' experience by choosing a "good" model, which will satisfactorily explain its dynamic behavior, from a model-base. But a fundamental question that often arises is: does the data exhibit the real case honestly? In this research we show how fuzzy time series construction be applied for this purpose. An order detection process for fuzzy time series is presented. Simulation has been used extensively to explore general properties of statistical procedures, and the approach is particularly useful in fuzzy time series construction. Statistical strategies typically consist of sequences of rules used repeatedly on the same data set. This paper is organized as follows: In Chapter 2 we will discuss about the definition of fuzzy time series as well as certain important properties. In Chapter 3, We use the similarity comparison process to decide the order of a fuzzy time series. Simulations and analysis with the results about various types of autocorrelation are experienced in Chapter 4. Finally, we apply our methods to three empirical examples, Taiwan business cycle index, marriage rate and numbers of students enrollment in Chapter 5. Chapter 6 is the conclusion and the discussion of future researches.
15

所得不均度之模糊測量-以台灣所得分配為例

吳鎮安, Wu Chen Un Unknown Date (has links)
傳統的不均度指標對於不均度的排序皆是精確而不含糊的,在Lorenz曲線相交的情況下,無法使用Lorenz準則判別不均度優劣,若使用不均度指標則可能產生不一致的排序結果,為了解決此一困境,本研究沿用Basu(1987)與Ok(1995,1996)的研究架構,修改其所得不均度的模糊測量方法,並力求將相關的模糊理論研究方法應用在所得不均度的議題上。 本文實證部分主要使用1980年至2002年中華民國行政院主計處「家庭收支調查報告」的資料,計算出家戶與個人資料的所得不均度指標值。結果發現,若考慮個人對於不均度感受上的模糊性,在家戶所得方面,80年代至90年代以後不均度顯著惡化,而個人所得分配則無明顯差異。而迴歸分析結果顯示,妻子勞動參與率上升、戶內就業人數比例增加,社福支出增加均有助於改善家戶所得不均的情況,而就業者平均教育程度上升與失業率的增加會加深家戶所得不均度。考慮不同的不均度指標間存在著模糊性,亦即將不均度指標視為模糊數(fuzzy number),而將傳統迴歸分析延伸至模糊迴歸分析,所預測的結果不再是一個精確的點,而是一個模糊區間,如此更切合實際所得分配狀況。最後,對於1993年至1997年不均度的模糊比較結果,討論了語意表示與信賴區間兩種不同的解模糊方法。而不同機制(隸屬度函數與不均度指標的不同)下的模糊排序結果可能產生不一致,本文也引用了文獻上的方法加以解決。值得注意的是,利用各種模糊關係的總和排序,與主計處每年根據家戶總可支配所得五等分位資料所計算的Gini係數排序略有出入,顯示出更客觀的排序結果。

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