我國礦業(yè)系統(tǒng)安全態(tài)勢預測研究
發(fā)布時間：2018-10-05 06:31
【摘要】：礦業(yè)系統(tǒng)安全態(tài)勢是衡量礦業(yè)系統(tǒng)安全管理效果和制定安全管理政策的重要依據，礦業(yè)系統(tǒng)安全態(tài)勢的預測研究是確定安全投入和制定安全對策措施的重要基礎之一。以我國礦業(yè)系統(tǒng)安全事故發(fā)生起數為系統(tǒng)安全態(tài)勢表征值，依其趨勢性、周期性、隨機波動性等特征，研究建立了季節(jié)指數灰色馬爾科夫加權組合預測模型，提出了灰色預測、馬爾科夫預測串聯組合再與季節(jié)指數預測加權并聯組合的混合組合模式；以平均絕對誤差最小為判斷準則，選用冪指數方程作為季節(jié)指數預測的趨勢方程，既較好地體現了安全態(tài)勢非線性發(fā)展規(guī)律，也可提高趨勢預測精度；依據預測平均絕對誤差值最小原則，，確定了馬爾科夫預測的狀態(tài)數為4；提出了基于觀測值與灰色預測值比值的“灰色馬爾科夫預測組合方法”；以預測誤差平方和倒數構建目標函數，優(yōu)化權重系數，構建了灰色馬爾科夫預測與季節(jié)指數預測加權組合模型。加權組合模型較季節(jié)指數預測模型和灰色馬爾科夫預測模型精度分別提高了7.8%，5.6%�；赩B6.0開發(fā)平臺，開發(fā)了季節(jié)指數灰色馬爾科夫組合預測模型系統(tǒng)軟件，實現了馬爾科夫狀態(tài)數確定、季節(jié)長度確定、趨勢方程選擇、單一模型預測、組合模型預測、組合精度計算、數據的動態(tài)更新與動態(tài)建模等功能，提高了預測工作的效率和準確度。
[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.
【學位授予單位】：武漢科技大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：X936
本文編號：2252368
[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.
【學位授予單位】：武漢科技大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：X936
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