發(fā)布時間：2018-04-10 00:14

  本文選題：數(shù)據(jù)挖據(jù)　切入點(diǎn)：決策樹　出處：《華北電力大學(xué)》2017年碩士論文

【摘要】：隨著信息技術(shù)的日新月異,計(jì)算機(jī)技術(shù)的應(yīng)用遍布各行各業(yè),海量的信息融入人們的方方面面,現(xiàn)今人們正處在一個信息爆炸的年代。如何有效的處理海量的數(shù)據(jù)信息,從中找到有價值的數(shù)據(jù),就成了各方研究的焦點(diǎn)。在電力行業(yè),電力設(shè)備越來越多,電網(wǎng)結(jié)構(gòu)越來越復(fù)雜的情況下,如何把采集到的電網(wǎng)數(shù)據(jù)通過提取和分析,得到有價值的運(yùn)行診斷信息,數(shù)據(jù)挖據(jù)技術(shù)的出現(xiàn)給這種用于電力系統(tǒng)故障診斷中海量信息的處理分析提供了方法。本文中,我們把數(shù)據(jù)挖據(jù)技術(shù)應(yīng)用到了電力系統(tǒng)的故障診斷中,構(gòu)建了電力系統(tǒng)故障診斷的模型。此模型主要利用決策樹把知識的獲取和表示結(jié)合在一起,使兩者的處理能夠同步進(jìn)行。在電力系統(tǒng)故障診斷的模型中,我們改進(jìn)了數(shù)據(jù)挖據(jù)技術(shù)中的決策樹算法,并用它完成知識的獲取與之結(jié)合。本文系統(tǒng)由推理機(jī)、解釋器、決策樹算法模塊和圖形界面四大模塊組成。推理機(jī)的主要功能是以決策樹算法生成的規(guī)則進(jìn)行推理,解釋器主要對推理機(jī)所返回的規(guī)則和決策樹生成或者專家錄入的規(guī)則進(jìn)行翻譯,決策樹算法主要作用是構(gòu)架一個高效易用的決策樹并且生成分類準(zhǔn)確的規(guī)則供推理機(jī)使用,圖形界面負(fù)責(zé)直觀的顯示輸出結(jié)果。本實(shí)驗(yàn)系統(tǒng)利用.NET平臺構(gòu)架,系統(tǒng)還可以擴(kuò)展適用的數(shù)據(jù)樣本或者使用數(shù)據(jù)挖據(jù)中其它的算法來處理其它方面的問題。
[Abstract]:With the rapid development of information technology, the application of computer technology is spread all over the industry, massive information is integrated into all aspects of people, now people are in an era of information explosion.How to effectively deal with massive data information and find valuable data has become the focus of research.In the electric power industry, with more and more power equipment and more and more complex power network structure, how to get valuable operation diagnosis information by extracting and analyzing the collected power grid data,The emergence of data mining technology provides a method for processing and analyzing mass information in power system fault diagnosis.In this paper, we apply the data mining technology to the fault diagnosis of power system, and construct the model of power system fault diagnosis.This model mainly uses decision tree to combine knowledge acquisition and representation so that the two processes can be processed synchronously.In the power system fault diagnosis model, we improve the decision tree algorithm in data mining technology, and use it to complete the knowledge acquisition and combination.The system consists of four modules: inference machine, interpreter, decision tree algorithm module and graphical interface.The main function of the inference machine is to infer the rules generated by the decision tree algorithm. The interpreter mainly translates the rules returned by the inference machine and the rules generated by the decision tree or input by experts.The main function of the decision tree algorithm is to construct an efficient and easy to use decision tree and to generate accurate classification rules for use by the inference machine. The graphical interface is responsible for displaying the output results intuitively.This experiment system uses .NET platform framework, the system can also extend the applicable data samples or use other algorithms in data mining to deal with other problems.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP311.13;TM711

【參考文獻(xiàn)】

相關(guān)期刊論文 前8條

1 周戈;高占國;楊秀清;李力;;數(shù)據(jù)挖掘中屬性約簡算法的研究[J];電腦知識與技術(shù);2008年02期

2 王姿雅;姚建剛;江岳春;姜燕;;具有數(shù)據(jù)挖掘功能的電力遠(yuǎn)程監(jiān)測管理系統(tǒng)[J];計(jì)算機(jī)工程與設(shè)計(jì);2006年11期

3 廖志偉,葉青華,王鋼,文福拴;基于GRNN的多故障自適應(yīng)電力系統(tǒng)故障診斷[J];華南理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2005年09期

4 王治華;;數(shù)據(jù)倉庫、聯(lián)機(jī)分析處理和數(shù)據(jù)挖掘技術(shù)的應(yīng)用[J];上海電力;2005年02期

5 方培培,李永麗,楊曉軍;Petri網(wǎng)與專家系統(tǒng)結(jié)合的輸電網(wǎng)絡(luò)故障診斷方法[J];電力系統(tǒng)及其自動化學(xué)報(bào);2005年02期

6 許先鋒,龔樂年,陳星鶯;基于廣度優(yōu)先搜索和優(yōu)化算法的輸電網(wǎng)故障診斷[J];電力系統(tǒng)及其自動化學(xué)報(bào);2004年05期

7 許儀勛,陸拯,郭志忠;基于遺傳算法的電力系統(tǒng)分層信息故障診斷方法[J];繼電器;2000年10期

8 于將;配電故障統(tǒng)計(jì)分析系統(tǒng)及其管理對策[J];華北電力技術(shù);2000年06期

相關(guān)碩士學(xué)位論文 前5條

1 黃婕;基于云計(jì)算的故障檢測方法研究與實(shí)現(xiàn)[D];昆明理工大學(xué);2014年

2 李U喲，

本文編號：1728798