【摘要】：礦業(yè)系統(tǒng)安全態(tài)勢(shì)是衡量礦業(yè)系統(tǒng)安全管理效果和制定安全管理政策的重要依據(jù)，礦業(yè)系統(tǒng)安全態(tài)勢(shì)的預(yù)測(cè)研究是確定安全投入和制定安全對(duì)策措施的重要基礎(chǔ)之一。以我國(guó)礦業(yè)系統(tǒng)安全事故發(fā)生起數(shù)為系統(tǒng)安全態(tài)勢(shì)表征值，依其趨勢(shì)性、周期性、隨機(jī)波動(dòng)性等特征，研究建立了季節(jié)指數(shù)灰色馬爾科夫加權(quán)組合預(yù)測(cè)模型，提出了灰色預(yù)測(cè)、馬爾科夫預(yù)測(cè)串聯(lián)組合再與季節(jié)指數(shù)預(yù)測(cè)加權(quán)并聯(lián)組合的混合組合模式；以平均絕對(duì)誤差最小為判斷準(zhǔn)則，選用冪指數(shù)方程作為季節(jié)指數(shù)預(yù)測(cè)的趨勢(shì)方程，既較好地體現(xiàn)了安全態(tài)勢(shì)非線性發(fā)展規(guī)律，也可提高趨勢(shì)預(yù)測(cè)精度；依據(jù)預(yù)測(cè)平均絕對(duì)誤差值最小原則，，確定了馬爾科夫預(yù)測(cè)的狀態(tài)數(shù)為4；提出了基于觀測(cè)值與灰色預(yù)測(cè)值比值的“灰色馬爾科夫預(yù)測(cè)組合方法”；以預(yù)測(cè)誤差平方和倒數(shù)構(gòu)建目標(biāo)函數(shù)，優(yōu)化權(quán)重系數(shù)，構(gòu)建了灰色馬爾科夫預(yù)測(cè)與季節(jié)指數(shù)預(yù)測(cè)加權(quán)組合模型。加權(quán)組合模型較季節(jié)指數(shù)預(yù)測(cè)模型和灰色馬爾科夫預(yù)測(cè)模型精度分別提高了7.8%，5.6%�；赩B6.0開(kāi)發(fā)平臺(tái)，開(kāi)發(fā)了季節(jié)指數(shù)灰色馬爾科夫組合預(yù)測(cè)模型系統(tǒng)軟件，實(shí)現(xiàn)了馬爾科夫狀態(tài)數(shù)確定、季節(jié)長(zhǎng)度確定、趨勢(shì)方程選擇、單一模型預(yù)測(cè)、組合模型預(yù)測(cè)、組合精度計(jì)算、數(shù)據(jù)的動(dòng)態(tài)更新與動(dòng)態(tài)建模等功能，提高了預(yù)測(cè)工作的效率和準(zhǔn)確度。
[Abstract]:The safety situation of mining system is an important basis to measure the effect of safety management in mining system and to formulate safety management policy. The prediction and study of safety situation of mining system is one of the important bases for determining safety input and formulating safety countermeasures. According to the characteristics of trend, periodicity and random fluctuation, the grey Markov weighted combination forecasting model of seasonal index is established, and the grey forecast is put forward according to the characteristics of trend, periodicity and random fluctuation of mining system safety accidents in China. The mixed combination model of Markov prediction series combination and seasonal index forecasting weighted parallel combination is adopted as the criterion of minimum mean absolute error and power exponent equation is chosen as the trend equation of seasonal index prediction. It not only reflects the nonlinear development law of security situation, but also improves the precision of trend prediction, according to the principle of minimum average absolute error of prediction, the state number of Markov prediction is determined to be 4. Based on the ratio of observed value to grey prediction value, a combined method of grey Markov prediction is proposed, and the objective function is constructed from the sum of square of prediction error, and the weight coefficient is optimized. A weighted combination model of grey Markov prediction and seasonal index prediction is constructed. The precision of the weighted combination model is 7.856% higher than that of the seasonal index model and the grey Markov model, respectively. Based on the VB6.0 development platform, the system software of seasonal exponential grey Markov combined prediction model is developed, which realizes the determination of Markov state number, seasonal length determination, trend equation selection, single model prediction, combined model prediction, and so on. The efficiency and accuracy of prediction are improved by combining precision calculation, dynamic updating of data and dynamic modeling.
【學(xué)位授予單位】：武漢科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：X936

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