臺灣博碩士論文加值系統

本文提出了一種新的婚姻介紹所適婚年齡男女的婚姻匹配方法;即“使用模糊推理系統解決適婚年齡(FISMM)男女的婚姻匹配問題”。本FISMM方法在軟計算中利用模糊推理系統（FIS）來實現適婚年齡男女的婚姻匹配問題。首先; 每位適婚年齡男女分別提出四個特徵：身高、學歷、收入和性格; 以便在數據庫中尋找理想的交往對象。隨後、利用這四個特徵建立了一個FIS系統; 它可以在數據庫D中尋找一個查詢的適婚年齡男女與幾個候選的適婚年齡女男之間的婚姻匹配。最後; 實驗結果顯示FISMM方法可以達到令人滿意的婚姻匹配。

A novel method for marriage match in a marriage agent, called “Using a Fuzzy Inference System to solve Marriage Match (FISMM) for physically mature people”, is presented in this thesis. The FISMM method makes use of a Fuzzy Inference System (FIS) in soft computing to realize marriage match for physically mature people. First, each physically mature person provides four conditions: height, education degree, income, and personality, respectively, in order to obtain his/her ideal candidates. Subsequently, these four features are utilized to build an FIS, which can search for the marriage match between a query physically mature person and several sampling candidates in the database D. Finally, experimental results demonstrate that the FISMM method can reach a satisfying performance for marriage match of physically mature people under considerations here.

Table of Contents
Acknowledgments.....................................................I
摘要................................................................II
Abstract...........................................................III
Table of Contents...................................................IV
List of Tables......................................................VI
List of Figures....................................................VII
Chapter 1 Introduction...............................................1
1.1 Objective and motivation.........................................3
1.2 Organization.....................................................4
1.3 About marriage...................................................5
Chapter 2 Literature review..........................................7
2.1 Fuzzy logic......................................................7
2.2 Fuzzy set........................................................8
2.3 Membership function..............................................9
2.4 Logical operation of fuzzy sets and fuzzy rules.................14
2.4.1 Single rule and single variable...............................18
2.4.2 Multiple rules and multiple variables.........................20
2.5 Fuzzy inference system..........................................23
Chapter 3 The FISMM method..........................................28
3.1 Marriage match features of exploration..........................30
3.2 The composition of the FIS......................................30
3.3 The composition of training and testing sets....................34
Chapter 4 Result and discussion.....................................35
4.1 The database D of marriage match................................35
4.2 The fuzzified input and output variables........................40
4.3 Fuzzy rules.....................................................44
4.4 Fuzzy inference engine..........................................45
4.5 Defuzzification.................................................48
4.6 The quantitative index for the recognition performance..........49
4.7 Experimental results............................................51
Chapter 5 Conclusion and future work................................55
References..........................................................56

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