臺灣博碩士論文加值系統

排班的方式對於客運公司的開支、營收、維修等方面對造成很大的影響，所以一個好的排班系統必須被建立起來，使得客運公司在調度上可以使效益最大化。此外，一個好的派車系統的建構，必須是有經驗的調度員來建立，透過電腦系統來進行運作，最後使應變系統能快速且立即對於排車需求做出反應。
公車應變營運系統，也就是公車額外派車系統。一般來說，公車是否需要額外派車，常常是以人工作業的方式，此種作業方式必須依賴有經驗的調度人員來進行，如果調度員的經驗不足，則所預估出來的公車需求，其準確率可能就不會那太高。所以需要建立專家系統。
本研究將所得到的資料，建立歸屬函數，並建立專家模糊推論規則，利用Rough Set Theory針對專家推論規則進行簡化，還有將專家模糊推論規則進行非監督式的K-mean分群。將三種推論結果建立專家系統，並將三種推論結果進行深入探討其適應性，使其能有效簡化模糊推論的規則。

A method of bus schedule affects bus company ‘s pay、operation、maintain. A useful bus operations must be established, let bus company have the most benefit in operation. Structuring a fine bus operations that must be established by experience schedule member. Operating by computer system and reacting quickly.
Bus operations is a bus extra dispatch vehicles system. Whether dispatch vehicle or not. It is decided by human. This mission be done by experience schedule member. If schedule member is too young , then the schedule accuracy is not high. So we must establish an expert system for bus operations.
This research is establishing an expert system for bus operations. We used the expert data that collected by investigated bus schedule expert. Establish membership function and fuzzy inference rule. Then We use rough set theory for reduce the fuzzy inference rule. Use unsupervised network’s K-mean clustering the fuzzy inference rule. We establish expert system by this three inference rules. And we use scenario analysis to compare the result of inference rules.

目錄
摘要 i
表目錄 vi
圖目錄 vii
第一章 緒論 1
1.1 研究動機與目的 1
1.2研究方法與內容 1
1.3研究架構 2
第二章 文獻回顧 4
2.1客運排班相關文獻 4
2.2模糊專家系統 5
2.2.1模糊邏輯與模糊專家系統簡介 5
2.2.2模糊專家系統相關文獻 6
2.3 Rough Set Theory 7
2.3.1 Rough Set Theory介紹 7
2.3.2 Rough Set Theory相關文獻 9
第三章 研究方法 11
3.1研究步驟 11
3.2模糊專家系統 12
3.2.1.模糊化 12
3.2.2.知識庫 13
3.2.3推論機制 13
3.3.4解模糊化 14
3.3 Rough Set Theory 15
3.3.1資訊表(Information Table) 15
3.3.2不可區分關係(Indiscernibility Relation) 17
3.3.3近似集合(Approximation Set) 17
3.3.4屬性簡化 19
3.3.5規則選取 20
第四章 實証分析 21
4.1資料來源 22
4.2建立歸屬函數 23
4.3建立模糊推論規則 27
4.4建立模糊專家系統 28
4.5 K-mean分群 30
4.6以Rough Set進行規則簡化 33
4.7 RS 14情境分析 36
4.7.1情境分析說明 36
4.7.2情境分析結果 37
4.7.3 探討 44
4.8 RS19情境分析 46
4.8.1情境分析結果 46
4.8.2探討 54
第五章 結論與建議 56
5.1結論 56
5.2建議 57
參考文獻 58

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