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  本文關(guān)鍵詞：基因表達(dá)式編程在電力負(fù)荷預(yù)測中的應(yīng)用　出處：《西安建筑科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 基因表達(dá)式編程算法 遠(yuǎn)緣融合 電力負(fù)荷預(yù)測 小生境技術(shù)

【摘要】：基因表達(dá)式編程算法(Gene Expression Programming,GEP)是在繼承并發(fā)展遺傳算法和遺傳編程優(yōu)點的基礎(chǔ)上,借鑒生物遺傳的基因表達(dá)規(guī)律,所提出的搜索和知識發(fā)現(xiàn)的新技術(shù)。該算法因其更強(qiáng)的解決問題的能力、易于進(jìn)行遺傳操作以及獨特的編碼方式等優(yōu)點備受國內(nèi)外研究學(xué)者關(guān)注,現(xiàn)已廣泛應(yīng)用于函數(shù)挖掘、預(yù)測、關(guān)聯(lián)規(guī)則和分類聚類等研究領(lǐng)域中的典型應(yīng)用,如時間序列和數(shù)據(jù)流預(yù)測模型、災(zāi)情分析、多層關(guān)聯(lián)規(guī)則挖掘、特征自動提取、挖掘遞歸函數(shù)等。本文主要的研究工作是改進(jìn)了標(biāo)準(zhǔn)GEP算法,將改進(jìn)后的算法應(yīng)用于電力負(fù)荷預(yù)測領(lǐng)域,構(gòu)建了基于GEP算法的電力負(fù)荷預(yù)測模型,在此基礎(chǔ)上,設(shè)計了基于基因表達(dá)式編程的電力負(fù)荷預(yù)測的原型系統(tǒng)。本文的具體工作主要有以下幾點:(1)依據(jù)小生境思想,本文對標(biāo)準(zhǔn)GEP算法進(jìn)行改進(jìn)得到一種基于遠(yuǎn)緣融合的小生境技術(shù)的基因表達(dá)式編程算法(OFN-GEP)。(2)本文將OFN-GEP算法應(yīng)用于電力負(fù)荷預(yù)測中,對咸陽市居民用電負(fù)荷量進(jìn)行建模預(yù)測,構(gòu)建了基于OFN-GEP算法的電力負(fù)荷預(yù)測模型,將OFN-GEP算法與最新文獻(xiàn)中的類似改進(jìn)算法進(jìn)行了比較,驗證了基于OFN-GEP算法的電力負(fù)荷預(yù)測模型的優(yōu)越性和較高的預(yù)測精度。(3)本文設(shè)計了電力負(fù)荷預(yù)測原型系統(tǒng),為電廠調(diào)度人員提供科學(xué)有效的參考依據(jù)。本文所實現(xiàn)的基于基因表達(dá)式編程算法的電力負(fù)荷預(yù)測系統(tǒng)已經(jīng)在咸陽市某電廠發(fā)揮了實際作用,為電廠的調(diào)度人員提供一定的參考價值。
[Abstract]:Gene expression programming algorithm (Gene Expression Programming, GEP) is based on the inheritance and development of the advantages of genetic algorithm and genetic programming, genetic reference gene expression pattern, the proposed new technology search and knowledge discovery. This algorithm because of its stronger ability to solve problems, easy operation and unique genetic encoding the way the advantages have attracted much attention of researchers at home and abroad, it has been widely applied in function mining, prediction, typical application of association rules and classification in the field of research, such as the prediction model of time series and data flow disaster analysis, association rule mining, automatic feature extraction, mining recursive function. The main work of this paper is to improve the standard GEP algorithm, the improved algorithm is applied to the field of power load forecasting, power load prediction model is built based on the GEP algorithm, on the basis of On the design of the prototype system of electric power load forecasting based on gene expression programming. The main work of this paper are as follows: (1) based on the niche theory, the standard GEP algorithm is improved by an expression programming algorithm and niche technique of distant fusion genes based on (OFN-GEP) (2). The OFN-GEP algorithm is applied to power load forecasting, the residents of Xianyang city electric load modeling and forecasting, construction of power load forecasting model based on OFN-GEP algorithm, improved OFN-GEP algorithm will be similar with the latest literature of the algorithm were compared to verify the prediction accuracy and superiority of high power load OFN-GEP algorithm based on the prediction model. (3) the design of electric power load forecasting system, to provide a scientific reference basis for power dispatch personnel. Gene expression programming algorithm based on the realization of the The power load forecasting system of the method has played a practical role in a power plant in Xianyang and provides a certain reference value for the dispatchers of the power plant.

【學(xué)位授予單位】：西安建筑科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP18;TM715

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