基于粗糙集和決策樹規(guī)則提取方法的研究畢業(yè)論文.doc
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基于粗糙集和決策樹規(guī)則提取方法的研究畢業(yè)論文,摘要在許多行業(yè)的故障診斷過程中，針對故障診斷信息不一致的情況，通常采用一種基于粗糙集和決策樹規(guī)則的提取方法，來提取簡單有效的診斷規(guī)則?；诖植诩蜎Q策樹規(guī)則的提取方法從定義的故障診斷決策系統(tǒng)出發(fā)，將故障診斷問題用一個具有不同簡化層次的決策網(wǎng)絡(luò)表示。在引入決策診斷規(guī)則的覆蓋度概念后，推導出每個網(wǎng)絡(luò)節(jié)點的診斷決策規(guī)則集?；?..
內(nèi)容介紹
此文檔由會員 白癡學東西 發(fā)布
摘 要
在許多行業(yè)的故障診斷過程中，針對故障診斷信息不一致的情況，通常采用一種基于粗糙集和決策樹規(guī)則的提取方法，來提取簡單有效的診斷規(guī)則?；诖植诩蜎Q策樹規(guī)則的提取方法從定義的故障診斷決策系統(tǒng)出發(fā)，將故障診斷問題用一個具有不同簡化層次的決策網(wǎng)絡(luò)表示。在引入決策診斷規(guī)則的覆蓋度概念后，推導出每個網(wǎng)絡(luò)節(jié)點的診斷決策規(guī)則集。基于粗糙集和決策樹規(guī)則的提取方法具有良好的定性分析能力，因此，如何將粗糙集與決策樹很好的融合，從而提取出有效的規(guī)則，已經(jīng)是一個非常有研究性的問題了。
本文以粗糙集和決策樹為研究多規(guī)則提取方法的基礎(chǔ)。首先，介紹了論文的研究背景，國內(nèi)外研究現(xiàn)狀以及研究的意義。其次，對粗糙集理論進行詳細研究，包括粗糙集中的一些基本的概念和粗糙集的簡化。再次，將粗糙集理論應(yīng)用到?jīng)Q策樹中，應(yīng)用準確度和覆蓋度兩個因素對提取的規(guī)則進行評價，最終提取簡潔、高效的規(guī)則。最后，舉出一個故障診斷方面的實例，將基于粗糙集和決策樹規(guī)則的提取方法應(yīng)用于實例中以解決問題，證明基于粗糙集和決策樹規(guī)則的提取方法可對新的故障狀態(tài)進行推理和決策，在故障診斷信息不完備的情況下也能得到相對滿意的診斷結(jié)論。
關(guān)鍵詞：粗糙集，決策樹，覆蓋度，故障診斷，決策規(guī)則
Abstract
In many industries the process of fault diagnosis, fault diagnostic information for inconsistencies, often using a decision tree based on rough sets and rule extraction method to extract the simple and effective diagnostic rules. Rules based on rough sets and decision tree extraction method from the definition of the starting fault diagnosis decision-making system, the fault diagnosis problem is simplified with a different level of decision-making network said. Diagnostic decision rules for the introduction of the coverage of concepts, each network node is derived diagnostic decision rules set. Rules based on rough sets and decision tree extraction method has good qualitative analysis, therefore, how to rough set and decision tree is a very good integration to extract the effective rules, has become one of the most researches of the problem.
This paper researches on rough set and decision tree based rule extraction method. First of all, introduced the research background, research status and research significance. Secondly, the detailed study of rough set theory, including some of the basic rough sets and rough sets concepts simplified. Again, the rough set theory applied to the decision tree, the application of accuracy and coverage of the two factors to eva luate the extracted rules, the final extraction of simple, efficient rules. Finally, to cite an instance of a fault diagnosis, the decision tree based on rough sets and rule extraction method is applied to solve the problem instances to prove that the rules based on rough sets and decision tree extraction method can be the fault of the new state of reasoning and decision-making in fault diagnosis case of incomplete information can be obtained relatively satisfactory diagnoses.
Key words: Rough sets, decision tree, coverage, fault diagnosis, decision rules
目 錄
第1章 緒 論 1
1.1 論文研究的背景 1
1.1.1 粗糙集理論 1
1.1.2 決策樹技術(shù) 2
1.2 國內(nèi)外研究現(xiàn)狀 2
1.3 研究的意義 3
1.4 本文的研究工作及結(jié)構(gòu)組織 4
第2章 粗糙集理論的研究 5
2.1 引 言 5
2.2 粗糙集理論的基本概念 5
2.2.1 知識和知識庫 5
2.2.2 信息系統(tǒng)和決策表 6
2.2.3 不可分辨關(guān)系 8
2.2.4 上、下近似集 9
2.2.5 依賴度和重要度 12
2.2.6 分明矩陣 13
第3章 基于粗糙集和決策樹規(guī)則提取方法的研究 15
3.1 粗糙集的簡化 15
3.1.1 數(shù)據(jù)離散化 15
3.1.2 屬性簡約與核 18
3.1.3 決策規(guī)則 20
3.2 決策樹技術(shù)簡介 21
3.3 基于粗糙集的決策樹構(gòu)造算法 23
3.3.1 普通的決策樹算法簡介 23
3.3.2 優(yōu)化的決策樹構(gòu)造算法 26
3.4 決策規(guī)則提取及篩選 28
3.4.1 覆蓋度 28
3.4.2 決策規(guī)則的提取及預(yù)測 30
3.4.3 故障診斷決策網(wǎng)絡(luò)的推理 32
第4章 故障診斷實例研究 33
結(jié) 論 36
致 謝 37
參考文獻 38
在許多行業(yè)的故障診斷過程中，針對故障診斷信息不一致的情況，通常采用一種基于粗糙集和決策樹規(guī)則的提取方法，來提取簡單有效的診斷規(guī)則?；诖植诩蜎Q策樹規(guī)則的提取方法從定義的故障診斷決策系統(tǒng)出發(fā)，將故障診斷問題用一個具有不同簡化層次的決策網(wǎng)絡(luò)表示。在引入決策診斷規(guī)則的覆蓋度概念后，推導出每個網(wǎng)絡(luò)節(jié)點的診斷決策規(guī)則集。基于粗糙集和決策樹規(guī)則的提取方法具有良好的定性分析能力，因此，如何將粗糙集與決策樹很好的融合，從而提取出有效的規(guī)則，已經(jīng)是一個非常有研究性的問題了。
本文以粗糙集和決策樹為研究多規(guī)則提取方法的基礎(chǔ)。首先，介紹了論文的研究背景，國內(nèi)外研究現(xiàn)狀以及研究的意義。其次，對粗糙集理論進行詳細研究，包括粗糙集中的一些基本的概念和粗糙集的簡化。再次，將粗糙集理論應(yīng)用到?jīng)Q策樹中，應(yīng)用準確度和覆蓋度兩個因素對提取的規(guī)則進行評價，最終提取簡潔、高效的規(guī)則。最后，舉出一個故障診斷方面的實例，將基于粗糙集和決策樹規(guī)則的提取方法應(yīng)用于實例中以解決問題，證明基于粗糙集和決策樹規(guī)則的提取方法可對新的故障狀態(tài)進行推理和決策，在故障診斷信息不完備的情況下也能得到相對滿意的診斷結(jié)論。
關(guān)鍵詞：粗糙集，決策樹，覆蓋度，故障診斷，決策規(guī)則
Abstract
In many industries the process of fault diagnosis, fault diagnostic information for inconsistencies, often using a decision tree based on rough sets and rule extraction method to extract the simple and effective diagnostic rules. Rules based on rough sets and decision tree extraction method from the definition of the starting fault diagnosis decision-making system, the fault diagnosis problem is simplified with a different level of decision-making network said. Diagnostic decision rules for the introduction of the coverage of concepts, each network node is derived diagnostic decision rules set. Rules based on rough sets and decision tree extraction method has good qualitative analysis, therefore, how to rough set and decision tree is a very good integration to extract the effective rules, has become one of the most researches of the problem.
This paper researches on rough set and decision tree based rule extraction method. First of all, introduced the research background, research status and research significance. Secondly, the detailed study of rough set theory, including some of the basic rough sets and rough sets concepts simplified. Again, the rough set theory applied to the decision tree, the application of accuracy and coverage of the two factors to eva luate the extracted rules, the final extraction of simple, efficient rules. Finally, to cite an instance of a fault diagnosis, the decision tree based on rough sets and rule extraction method is applied to solve the problem instances to prove that the rules based on rough sets and decision tree extraction method can be the fault of the new state of reasoning and decision-making in fault diagnosis case of incomplete information can be obtained relatively satisfactory diagnoses.
Key words: Rough sets, decision tree, coverage, fault diagnosis, decision rules
目 錄
第1章 緒 論 1
1.1 論文研究的背景 1
1.1.1 粗糙集理論 1
1.1.2 決策樹技術(shù) 2
1.2 國內(nèi)外研究現(xiàn)狀 2
1.3 研究的意義 3
1.4 本文的研究工作及結(jié)構(gòu)組織 4
第2章 粗糙集理論的研究 5
2.1 引 言 5
2.2 粗糙集理論的基本概念 5
2.2.1 知識和知識庫 5
2.2.2 信息系統(tǒng)和決策表 6
2.2.3 不可分辨關(guān)系 8
2.2.4 上、下近似集 9
2.2.5 依賴度和重要度 12
2.2.6 分明矩陣 13
第3章 基于粗糙集和決策樹規(guī)則提取方法的研究 15
3.1 粗糙集的簡化 15
3.1.1 數(shù)據(jù)離散化 15
3.1.2 屬性簡約與核 18
3.1.3 決策規(guī)則 20
3.2 決策樹技術(shù)簡介 21
3.3 基于粗糙集的決策樹構(gòu)造算法 23
3.3.1 普通的決策樹算法簡介 23
3.3.2 優(yōu)化的決策樹構(gòu)造算法 26
3.4 決策規(guī)則提取及篩選 28
3.4.1 覆蓋度 28
3.4.2 決策規(guī)則的提取及預(yù)測 30
3.4.3 故障診斷決策網(wǎng)絡(luò)的推理 32
第4章 故障診斷實例研究 33
結(jié) 論 36
致 謝 37
參考文獻 38
