本文選題：黑龍江　切入點(diǎn)：煙草企業(yè)　出處：《哈爾濱理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：中國(guó)煙草業(yè)多年來(lái)全面推進(jìn)“以客戶訂單為基準(zhǔn)的組織貨源”工作,這也正迎合了當(dāng)今社會(huì)“以銷定產(chǎn)”的思想,因此如何準(zhǔn)確的預(yù)測(cè)銷量,準(zhǔn)確及時(shí)地反應(yīng)煙草市場(chǎng)走勢(shì),為參與市場(chǎng)的生產(chǎn)者、營(yíng)銷方提供準(zhǔn)確有效的決策參考依據(jù),已成為市場(chǎng)各方最為急迫的要求。本文,首先介紹了黑龍江卷煙在國(guó)內(nèi)的銷售現(xiàn)狀,分析了影響黑龍江省煙草有限責(zé)任公司(后文簡(jiǎn)稱為龍江煙草公司)銷量的具體因素,在模型的選擇上介紹了灰色系統(tǒng)和馬爾可夫模型的基本理論,說(shuō)明了灰色預(yù)測(cè)模型和馬爾可夫預(yù)測(cè)模型的概念和研究方法。在灰色系統(tǒng)理論基礎(chǔ)上建立的灰色系統(tǒng)預(yù)測(cè)模型使用數(shù)據(jù)少,方便運(yùn)算,預(yù)測(cè)準(zhǔn)確度高。而馬爾可夫鏈理論的研究適用于隨機(jī)狀態(tài)的動(dòng)態(tài)系統(tǒng),更加適合預(yù)測(cè)隨機(jī)波動(dòng)幅度比較大以及樣本數(shù)據(jù)多的隨機(jī)過(guò)程。但其不足之處是不僅要求預(yù)測(cè)對(duì)象具有馬氏性,同時(shí),預(yù)測(cè)數(shù)據(jù)序列要服從典型分布,但當(dāng)系統(tǒng)信息較少時(shí)較難確定數(shù)據(jù)序列服從何種分布。所以,本文在分別使用灰色系統(tǒng)和馬爾可夫模型對(duì)卷煙銷量進(jìn)行預(yù)測(cè),得到結(jié)果分析各自模型的特點(diǎn)及優(yōu)劣后,又將灰色預(yù)測(cè)模型和馬爾可夫預(yù)測(cè)模型有機(jī)地結(jié)合起來(lái),利用各自的模型優(yōu)勢(shì),用灰色預(yù)測(cè)模型來(lái)預(yù)測(cè)卷煙銷量的時(shí)間走勢(shì),隨后對(duì)灰色產(chǎn)生的殘差走勢(shì)建立馬爾可夫模型進(jìn)行修正,從而使兩者相結(jié)合建立更為精確的灰色馬爾可夫預(yù)測(cè)模型,對(duì)各自模型取長(zhǎng)補(bǔ)短,進(jìn)行優(yōu)化。本文對(duì)龍江煙草公司目前銷售情況進(jìn)行了研究,對(duì)2012-2015年共四年來(lái)每月的銷量數(shù)據(jù)進(jìn)行分析測(cè)算,使用灰色模型和馬爾可夫模型及兩個(gè)模型相結(jié)合建立的灰色馬爾可夫模型,通過(guò)灰色模型及其相應(yīng)的建模軟件,對(duì)年銷量樣本數(shù)據(jù)進(jìn)行分析、預(yù)測(cè);對(duì)月銷量樣本數(shù)據(jù)應(yīng)用馬爾可夫模型結(jié)果進(jìn)行對(duì)比,發(fā)現(xiàn)誤差較大;最后通過(guò)將灰色模型的誤差作為馬爾可夫模型的區(qū)間劃分依據(jù),從而建立灰色馬爾可夫模型,對(duì)季度的卷煙品類銷量進(jìn)行預(yù)測(cè),取得了更為精確的預(yù)測(cè)結(jié)果。
[Abstract]:Over the years, the Chinese tobacco industry has comprehensively promoted the work of "organizing and supplying goods based on customer orders," which is also catering to the idea of "producing by sales" in today's society. Therefore, how to accurately predict the sales volume and accurately and timely reflect the trend of the tobacco market, For the producers participating in the market, the marketer provides the accurate and effective reference basis for decision-making, which has become the most urgent requirement of all parties in the market. This paper first introduces the current situation of Heilongjiang cigarette sales in China. This paper analyzes the specific factors influencing the sales volume of Heilongjiang Tobacco Co., Ltd. (hereinafter referred to as Longjiang Tobacco Company), and introduces the basic theories of grey system and Markov model in the selection of models. The concept and research method of grey prediction model and Markov prediction model are explained. The grey system prediction model established on the basis of grey system theory uses less data and is convenient for calculation. The Markov chain theory is suitable for dynamic systems with random states. It is more suitable to predict random processes with large amplitude of random fluctuation and large sample data. However, its shortcoming is that it not only requires the prediction object to have Markov property, but also the prediction data series should be distributed from a typical model. But when the system information is less, it is difficult to determine the distribution of the data sequence clothing. Therefore, the gray system and Markov model are used to predict the cigarette sales volume, and the results of the analysis of the characteristics, advantages and disadvantages of the respective models. Combining the grey forecasting model with the Markov forecasting model organically, using their respective model advantages, using the grey forecast model to predict the time trend of cigarette sales. Then, the Markov model is established to correct the residual trend of grey, so as to establish a more accurate grey Markov prediction model, which can make up for the weakness of each model. In this paper, the current sales situation of Longjiang Tobacco Company is studied, and the monthly sales data of 2012-2015 are analyzed and calculated. Using the grey model and Markov model and the grey Markov model established by the combination of the two models, through the grey model and its corresponding modeling software, the sample data of annual sales volume are analyzed and forecasted. By comparing the data of monthly sales volume with the results of Markov model, it is found that the error of grey model is large. Finally, the error of grey model is taken as the basis of interval division of Markov model, and then the grey Markov model is established. Forecast the quarterly cigarette sales and obtain more accurate forecast results.
【學(xué)位授予單位】：哈爾濱理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：F426.8;F274

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