組合預(yù)測(cè)算法在時(shí)間序列預(yù)測(cè)中的研究和應(yīng)用.doc
約25頁DOC格式手機(jī)打開展開
組合預(yù)測(cè)算法在時(shí)間序列預(yù)測(cè)中的研究和應(yīng)用,摘 要 本文是對(duì)在混沌算法對(duì)電力負(fù)荷預(yù)測(cè)為背景下的提出一種新的相似度的定義和實(shí)現(xiàn),著重討論了各種相識(shí)度的度量的優(yōu)缺點(diǎn)和我們新的定義的由來,并將其應(yīng)用到chen’s 系統(tǒng)中,通過matlab仿真實(shí)驗(yàn)結(jié)果來證明本文的方法的可行性和能用性,為當(dāng)今的電力負(fù)荷預(yù)測(cè)提供了新的更加好的算法...
內(nèi)容介紹
此文檔由會(huì)員 違規(guī)15 發(fā)布
組合預(yù)測(cè)算法在時(shí)間序列預(yù)測(cè)中的研究和應(yīng)用
摘 要
本文是對(duì)在混沌算法對(duì)電力負(fù)荷預(yù)測(cè)為背景下的提出一種新的相似度的定義和實(shí)現(xiàn),著重討論了各種相識(shí)度的度量的優(yōu)缺點(diǎn)和我們新的定義的由來,并將其應(yīng)用到Chen’s 系統(tǒng)中,通過matlab仿真實(shí)驗(yàn)結(jié)果來證明本文的方法的可行性和能用性,為當(dāng)今的電力負(fù)荷預(yù)測(cè)提供了新的更加好的算法。
第一章是概述,主要講相似度的研究背景意義、目前的主要研究方法以及選題背景的介紹;第二章從相識(shí)度度量的類別上我們分別分條敘述,分別從基于形狀的相似度、基于特征的相似度、基于模型的相似度、基于壓縮的相似度展開討論,并分別就各種相似度的度量方法的優(yōu)缺點(diǎn)比較,并基于此提出了一種新的相似度的定義,然后我們利用電力系統(tǒng)的混沌預(yù)測(cè)為背景,將我們的方法應(yīng)用其中,我們做了詳細(xì)的算法推導(dǎo)過程;第四章是我們仿真的具體結(jié)果展示和仿真結(jié)果的分析和討論;第五章總結(jié),主要對(duì)忙于畢業(yè)設(shè)計(jì)這幾個(gè)月來的工作進(jìn)展和設(shè)計(jì)的研究成果以及心得體會(huì)做一下介紹。第七章為致謝;第八章是參考文獻(xiàn);最后是附錄。
關(guān)鍵詞: 相似度 電力負(fù)荷 混沌算法 Chen’s系統(tǒng)
Define and implement a new type of signal similarity
Abstract
The This article is in the chaos algorithm to the power load forecasting is put forward against the background of the definition and implementation of a new similarity, emphatically discusses the met various degrees of advantages and disadvantages of metrics and we define a new origin, and apply it to Mr Chen 's system, through the matlab simulation results prove the method is feasible and can be used for the current power load forecasting provides a new algorithm is more good.
The first chapter is an overview of the main research background significance of the similarity, the present main research methods and the introduction of topic selection background; Chapter 2 we points, respectively, from the acquaintance degree measurement category of narration, respectively from the similarity based on shape, based on the characteristics of similarity, similarity based on the model, based on the similarity of compression, and then the advantages and disadvantages of various similarity measurement method respectively, and puts forward a new kind of based on this similarity is defined first, then we use chaotic forecasting of power system as the background, the application of the method of we, our algorithm deducing process in detail; The fourth chapter is the concrete result of our simulation display and simulation results analysis and discussion; Fifth chapter summary, mainly for busy this a few months of graduation design research and design of work achievement and comments do the introduction. Chapter 7, thanks; The eighth chapter is reference; Finally, the appendix.
Keywords: similarity, Power load, chaos algorithm,Chen’s System.
目 錄
摘 要 I
Abstract II
1 緒論 1
1.1 研究背景及意義 1
1.2 國(guó)內(nèi)外研究現(xiàn)狀 1
1.3 仿真軟件MATLAB的簡(jiǎn)介 1
2信號(hào)相似度定義的方法比較以及新方法的提出 3
2.1基于形狀相似度的研究 3
2.1.1 歐氏距離 3
2.1.2 曼哈頓距離 4
2.1.3 切比雪夫距離 5
2.1.4 閔可夫斯基距離 6
2.1.5 標(biāo)準(zhǔn)化歐氏距離 6
2.1.6 馬氏距離 6
2.1.7 夾角余弦 7
2.1.7 漢明距離 7
2.2各種相似度的度量方法的優(yōu)缺點(diǎn)比較 8
2.3新的相似度方法的定義 8
2.4算法推導(dǎo) 9
2.4.1 加權(quán)一階局域法一步預(yù)報(bào)模型[5] 9
2.4.2 加權(quán)一階局域法多步預(yù)報(bào)模型 10
2.4.3 RBFNN局域法預(yù)報(bào)模型 12
3新信號(hào)相似度度量的算例仿真 13
3.1 Chen’s混沌序列 13
3.2結(jié)果分析 13
參考文獻(xiàn) 18
附 錄A某發(fā)電廠的電力負(fù)荷數(shù)據(jù)(部分) 19
致 謝 20
摘 要
本文是對(duì)在混沌算法對(duì)電力負(fù)荷預(yù)測(cè)為背景下的提出一種新的相似度的定義和實(shí)現(xiàn),著重討論了各種相識(shí)度的度量的優(yōu)缺點(diǎn)和我們新的定義的由來,并將其應(yīng)用到Chen’s 系統(tǒng)中,通過matlab仿真實(shí)驗(yàn)結(jié)果來證明本文的方法的可行性和能用性,為當(dāng)今的電力負(fù)荷預(yù)測(cè)提供了新的更加好的算法。
第一章是概述,主要講相似度的研究背景意義、目前的主要研究方法以及選題背景的介紹;第二章從相識(shí)度度量的類別上我們分別分條敘述,分別從基于形狀的相似度、基于特征的相似度、基于模型的相似度、基于壓縮的相似度展開討論,并分別就各種相似度的度量方法的優(yōu)缺點(diǎn)比較,并基于此提出了一種新的相似度的定義,然后我們利用電力系統(tǒng)的混沌預(yù)測(cè)為背景,將我們的方法應(yīng)用其中,我們做了詳細(xì)的算法推導(dǎo)過程;第四章是我們仿真的具體結(jié)果展示和仿真結(jié)果的分析和討論;第五章總結(jié),主要對(duì)忙于畢業(yè)設(shè)計(jì)這幾個(gè)月來的工作進(jìn)展和設(shè)計(jì)的研究成果以及心得體會(huì)做一下介紹。第七章為致謝;第八章是參考文獻(xiàn);最后是附錄。
關(guān)鍵詞: 相似度 電力負(fù)荷 混沌算法 Chen’s系統(tǒng)
Define and implement a new type of signal similarity
Abstract
The This article is in the chaos algorithm to the power load forecasting is put forward against the background of the definition and implementation of a new similarity, emphatically discusses the met various degrees of advantages and disadvantages of metrics and we define a new origin, and apply it to Mr Chen 's system, through the matlab simulation results prove the method is feasible and can be used for the current power load forecasting provides a new algorithm is more good.
The first chapter is an overview of the main research background significance of the similarity, the present main research methods and the introduction of topic selection background; Chapter 2 we points, respectively, from the acquaintance degree measurement category of narration, respectively from the similarity based on shape, based on the characteristics of similarity, similarity based on the model, based on the similarity of compression, and then the advantages and disadvantages of various similarity measurement method respectively, and puts forward a new kind of based on this similarity is defined first, then we use chaotic forecasting of power system as the background, the application of the method of we, our algorithm deducing process in detail; The fourth chapter is the concrete result of our simulation display and simulation results analysis and discussion; Fifth chapter summary, mainly for busy this a few months of graduation design research and design of work achievement and comments do the introduction. Chapter 7, thanks; The eighth chapter is reference; Finally, the appendix.
Keywords: similarity, Power load, chaos algorithm,Chen’s System.
目 錄
摘 要 I
Abstract II
1 緒論 1
1.1 研究背景及意義 1
1.2 國(guó)內(nèi)外研究現(xiàn)狀 1
1.3 仿真軟件MATLAB的簡(jiǎn)介 1
2信號(hào)相似度定義的方法比較以及新方法的提出 3
2.1基于形狀相似度的研究 3
2.1.1 歐氏距離 3
2.1.2 曼哈頓距離 4
2.1.3 切比雪夫距離 5
2.1.4 閔可夫斯基距離 6
2.1.5 標(biāo)準(zhǔn)化歐氏距離 6
2.1.6 馬氏距離 6
2.1.7 夾角余弦 7
2.1.7 漢明距離 7
2.2各種相似度的度量方法的優(yōu)缺點(diǎn)比較 8
2.3新的相似度方法的定義 8
2.4算法推導(dǎo) 9
2.4.1 加權(quán)一階局域法一步預(yù)報(bào)模型[5] 9
2.4.2 加權(quán)一階局域法多步預(yù)報(bào)模型 10
2.4.3 RBFNN局域法預(yù)報(bào)模型 12
3新信號(hào)相似度度量的算例仿真 13
3.1 Chen’s混沌序列 13
3.2結(jié)果分析 13
參考文獻(xiàn) 18
附 錄A某發(fā)電廠的電力負(fù)荷數(shù)據(jù)(部分) 19
致 謝 20