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研究生:林政翰
研究生(外文):Cheng-Han Lin
論文名稱:遺傳規劃法於模糊建模與負載排程之應用
論文名稱(外文):Application of Genetic Programming to Fuzzy Modeling and the Schedule of Direct Load Control
指導教授:姚立德姚立德引用關係
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:電機工程系研究所
學門:工程學門
學類:電資工程學類
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:121
中文關鍵詞:遺傳規劃法模糊類神經網路模糊建模負載排程
外文關鍵詞:Genetic ProgrammingFuzzy Neural NetworkFuzzy ModelingDirect Load Control
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遺傳規劃法能被設計在搜尋結構解的應用上,主要是遺傳規劃法擁有著強大得搜尋能力,且其透過樹狀結構的交配演化而得到更好的結構解,故在本研究中將利用遺傳規劃法來解決兩個最佳化組合的問題。
(1).遺傳規劃法於模糊建模之應用:本篇論文中是談論有關以普遍的方法去發展模糊建模,而模糊建模與數值建模最大的不同在於,模糊建模能在一個模糊集合中透露一些訊息給我們,且這個觀點也提醒著我們,在建模的同時,除了其精確度的問題外,尚須考慮到一個模糊建模的透明度的問題。

(2).遺傳規劃法於負載排程之應用:其主要是利用遺傳規劃法搜尋結構的特性,在尖峰負載時找出合適的空調來受控,而此受控情形即對空調負載作短暫的停機動作,由於部分空調系統受控,故能有效的抑制尖峰負載。
Based on a good searching ability of structure, Genetic Programming is designed to search the structural solution and to utilize crossover mechanism of tree structure to get the better structure. In this thesis, we will use the performance of Genetic Programming to solve two optimal questions.
(1).Application of Genetic Programming to fuzzy modeling: This study is concerned with a general methodology of identification of fuzzy models. Unlike other numeric models, fuzzy models operate at a level of information granules (fuzzy sets), and this aspect brings up an important requirement of design on about the transparency of the model.

(2).Application of Genetic Programming to the schedule of direct load control: Based on the searching ability of Genetic Programming, we can find an optimal control strategy to reduce the peak load.
中文摘要 i
ABSTRACT ii
誌謝 iii
目 錄 iv
表目錄 vi
圖目錄 viii
第一章 緒論 1
1.1 前言 1
1.2 研究動機與目的 1
1.3 文獻探討 2
1.4 內容大綱 5
第二章 遺傳規劃法之架構與設計 6
2.1 遺傳規劃法的架構 6
2.1.1 遺傳規劃法的特性 7
2.2 基因型遺傳規劃法架構 9
第三章 遺傳規劃法於模糊建模之應用 13
3.1 模糊建模 13
3.2 建模內容 15
3.3 遺傳規劃法之應用 16
3.3.1 遺傳規劃法之適應值 17
3.3.2 遺傳規劃法之交配情形 18
3.3.3 遺傳規劃法之突變 19
3.3.4 移民滅種 21
3.3.5 限制條件 21
3.4 Mamdani模糊模型 22
3.4.1 Mamdani運算之分析 23
3.4.2 梯度法於Mamdani模型參數之微調 25
3.4.3 遺傳規劃法表示Mamdani模糊模型之流程圖 28
3.5 TSK模糊模型 29
3.5.1 梯度法於TSK模型參數之微調 29
3.5.2 TSK模糊模型方法一 31
3.5.3 TSK模糊模型方法二 32
3.6 實驗與模擬 33
第四章 遺傳規劃法於負載排程之應用 93
4.1 負載排程簡介 93
4.2 問題描述 93
4.3 最佳化排程 96
4.3.1 初始化 96
4.3.2 多時段排程預測策略 98
4.3.3多時段排程預測策略之簡化 102
4.3.4 遺傳規劃法於負載排程之上限依據 105
4.4 最佳化與受控公平性探討 105
4.5 實驗與模擬 106
第五章 結論與未來展望 115
參考文獻 116
作者簡介 121
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