本文選題：中國水產(chǎn)品　切入點：高階GM(n　出處：《大連海洋大學(xué)》2015年碩士論文

【摘要】：中國水產(chǎn)品是國民經(jīng)濟的重要組成部分,是直接關(guān)系民計民生的重要環(huán)節(jié)。中國水產(chǎn)品產(chǎn)量一直保持著平穩(wěn)較快的增長,對此數(shù)據(jù)進行實證分析具有積極的現(xiàn)實意義。中國水產(chǎn)品產(chǎn)量數(shù)據(jù)具有指數(shù)增長、階段性、隨機性等特征;又由于政治、經(jīng)濟、環(huán)境、自然等因素的影響,數(shù)據(jù)也呈現(xiàn)模糊性、微震蕩性,故采用現(xiàn)代時間序列建模方法對數(shù)據(jù)進行分析具有可行性。這一系列的數(shù)據(jù)隨時間推移既有一定的趨勢性又有隨機性特征,較為符合灰色系統(tǒng)模型的模型特點。故本文最終選用灰色系統(tǒng)模型進行數(shù)據(jù)分析。在研究過程中,首先利用傳統(tǒng)的GM(1,1)模型對中國水產(chǎn)品產(chǎn)量進行了建模分析,并利用高階灰色系統(tǒng)模型進行不同階數(shù)建模結(jié)果的分析比對,在計算精度與計算成本的綜合衡量下,選擇了GM(2,1)、GM(3,1)與GM(1,1)對中國水產(chǎn)品產(chǎn)量進行了實證比對分析,得出高階灰色系統(tǒng)GM(2,1)模型的建模結(jié)果較比傳統(tǒng)模型精度上有了較大程度的提高,但由于數(shù)據(jù)的階段性的影響,高階灰色系統(tǒng)GM(3,1)模型的建模結(jié)果則誤差較大,不宜進行實證分析。同時,在中國水產(chǎn)品產(chǎn)量所包含的海洋捕撈、遠洋漁業(yè)、海水養(yǎng)殖、淡水捕撈、淡水養(yǎng)殖產(chǎn)量數(shù)據(jù)中,為了分析各產(chǎn)量之間的潛在關(guān)系,利用灰關(guān)聯(lián)分析按序列的關(guān)聯(lián)關(guān)系將中國水產(chǎn)品產(chǎn)量分為兩組,并利用多變量灰色系統(tǒng)模型對分組后的兩組數(shù)據(jù)分別進行建模分析,誤差計算結(jié)果顯示了建模結(jié)果的有效性。通過以上實證分析可知,灰色系統(tǒng)理論中的高階灰色系統(tǒng)模型和多變量灰色系統(tǒng)模型對中國水產(chǎn)品產(chǎn)量數(shù)據(jù)進行分析能夠收到良好的效果,但仍存有數(shù)據(jù)特殊性的限制;第二,利用高階灰色系統(tǒng)模型對呈指數(shù)型增長且伴有隨機性的數(shù)據(jù)進行建模,以及利用多變量灰色系統(tǒng)模型對有內(nèi)在關(guān)聯(lián)的數(shù)據(jù)進行分組建模具有推廣意義;第三,從追求單數(shù)據(jù)的建模精度到利用多維數(shù)據(jù)關(guān)系進行建模的思路在當(dāng)今大數(shù)據(jù)的背景下,具有現(xiàn)實意義。這為相關(guān)部門決策與分析生產(chǎn)與供給、消費與需求、進出口、市場流通和價格等問題提供了數(shù)據(jù)分析基礎(chǔ),具有借鑒意義。
[Abstract]:Aquatic products is an important part of the national economy and an important link directly related to people's livelihood.The production of aquatic products in China has been increasing steadily and rapidly.China's aquatic product output data are characterized by exponential growth, stages, randomness, and so on. Due to the influence of political, economic, environmental, natural and other factors, the data also show fuzziness and micro-volatility.Therefore, it is feasible to use the modern time series modeling method to analyze the data.This series of data not only has some tendency and randomness with time, but also accords with the model characteristic of grey system model.So this paper chooses the grey system model to analyze the data.In the course of the research, the traditional GM1 / 1) model is used to model and analyze the aquatic product production in China, and the high order grey system model is used to analyze and compare the different order modeling results.In this paper, we have selected GMGM2GM1) to compare and analyze the aquatic product production in China. It is concluded that the modeling result of the high-order grey system GMGM2GM1) model is higher than that of the traditional model, but because of the influence of the stage of the data, the model is more accurate than that of the traditional model, but because of the effect of the stage of the data,High order grey system GM3 + 1) model is not suitable for empirical analysis because of its large error.At the same time, in order to analyze the potential relationship between the various yields, in the data on marine fishing, ocean fisheries, mariculture, freshwater fishing and freshwater aquaculture, which are included in China's aquatic product production,The production of aquatic products in China is divided into two groups by using the grey correlation analysis according to the correlation relation of the sequence, and the two groups of data after grouping are modeled and analyzed by using the multivariable grey system model. The result of error calculation shows the validity of the modeling results.Through the above empirical analysis, we can see that the high-order grey system model and the multi-variable grey system model in the grey system theory can achieve good results in the analysis of aquatic product production data in China, but there are still some limitations of the data particularity.Using the high-order grey system model to model the exponential growth data with randomness, and using the multi-variable grey system model to group the data with internal correlation is of great significance.From pursuing the modeling accuracy of single data to modeling by using multidimensional data relationship, it is of practical significance under the background of big data today.It provides a data analysis basis for the decision and analysis of production and supply, consumption and demand, import and export, market circulation and price.
【學(xué)位授予單位】：大連海洋大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：F326.4;N941.5

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1 付瑩,張廣立,楊汝清;基于數(shù)列變換優(yōu)化的灰色系統(tǒng)模型[J];系統(tǒng)工程與電子技術(shù);2004年04期

2 鞠淼;;灰色系統(tǒng)模型在千車故障率問題中的應(yīng)用[J];長春工業(yè)大學(xué)學(xué)報(自然科學(xué)版);2005年04期

3 李炳林;劉洪;;用灰色系統(tǒng)模型估測我國非正規(guī)經(jīng)濟規(guī)模[J];商業(yè)研究;2006年17期

4 白志剛;;基于趨勢外推模型和灰色系統(tǒng)模型的深圳保費收入總量預(yù)測[J];統(tǒng)計教育;2010年12期

5 劉豐常;用灰色系統(tǒng)模型預(yù)測地震趨勢[J];華南地震;1988年03期

6 李臨潁,陶炳炎;產(chǎn)量結(jié)構(gòu)灰色系統(tǒng)模型及其模擬[J];南京氣象學(xué)院學(xué)報;1991年04期

7 李曉立;;論灰色系統(tǒng)模型方法[J];系統(tǒng)辯證學(xué)學(xué)報;1993年03期

8 王澤e，

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