基于改进型灰色神经网络组合模型的空气质量预测

基于空气质量数据不足及波动较大的情况,将灰色GM（1,1）模型与人工神经网络模型组合并改进,建立改进型灰色神经网络组合模型。利用天津市2001—2008年PM10、SO2和NO2年均值作为原始数据预测2009—2010年PM10、SO2和NO2的浓度以进行模型精度检验,最后利用该模型预测2011—2015年天津市空气质量状况。结果表明,与灰色GM（1,1）模型、传统灰色神经网络组合模型相比,所建立的改进型灰色神经网络组合模型相对模拟误差小,预测结果更为可靠,可以用于空气质量预测。     

煤体电荷感应信号评价冲击危险性试验研究

为完善冲击地压矿井的冲击危险性评价方法,提高冲击危险性预测的准确率,应用自主研制的煤岩电荷监测系统,选择典型冲击地压矿井的煤样,开展了煤体单轴压缩冲击危险性测试与电荷感应监测试验研究。基于冲击地压扰动响应失稳理论,将应变软化阶段产生的电荷信号变化作为预测冲击地压发生的前兆信息,得到了煤体冲击危险性指标的临界软化系数Kρ、临界应力系数Kp及其冲击危险的等级分类标准,分析了煤体电荷感应信号的电荷事件数CSJ和电荷事件的平均幅值CFZ参量与冲击危险性指标Kρ和Kp之间的量化关系。结果表明:煤样破裂应力峰后,冲击倾向性K与电荷事件数CSJ呈指数递减关系,与CFZ呈指数递增关系;随着Kρ或Kp的增大,煤样应力峰后CSJ呈幂函数关系递增,应力峰后电荷平均幅值CFZ呈一次函数关系递减,以此可预测煤体的冲击危险程度,最后得到了河南某矿煤层冲击危险性的应力峰后冲击危险等级的CSJ和CFZ判据与划分标准。煤体冲击危险性电荷感应信号评价方法为冲击地压矿井冲击危险性评价提供了一种新的方向,对现场煤层冲击危险性评价具有指导作用,但也还需要开展大量现场试验对其进行不断修正和完善。     

基于GF-LSTM和GAN网络的小样本集人工水体溶解氧浓度预测

采用推流方式改善人工水体溶解氧分布不均衡以防止富营养化时,需要对其分布进行预测来提高推流效率,为此构建了基于生成式对抗网络(GAN,Generative Adversarial Networks)和长短期记忆神经网络(LSTM,Long-Short Term Memory Network)的溶解氧浓度预测模型。以广西大学镜湖35 m2的一片水体区域为研究对象,采用不同电压直流水泵推流,用无人船搭载在线检测仪在一段时间内定时定点采集水体溶解氧浓度数据作为原始数据样本,并采用GAN扩充数据样本。利用遗传算法和改进的一阶滤波算法进行溶解氧的噪声数据处理,结合LSTM网络构建溶解氧浓度预测模型GF-LSTM(Genetic And Filtering Algorithm-Long Short Term Memory Network)。结果表明:相比常用的BP网络,GF-LSTM网络预测的平均误差降低了62%,均方误差降低了75%;相比传统的LSTM网络,GF-LSTM网络预测的平均误差降低了22%,均方误差降低了50%。     

Experimental study on unconfined methane explosion: Explosion characteristics and overpressure prediction method

Explosion accidents have become the main threat for the high-efficiency use of cleaner gas energy sources, such as natural gas. During an explosion, obstacle causing flame acceleration is the main reason for the increase of the explosion overpressure, which still remains to be fully understood. In this research, field experiments were conducted in a 1 m³ cubic frame apparatus to investigate the effect of built-in obstacles on unconfined methane explosion. Cage-like obstacles were constructed using square steel rods with different cross section size. The results demonstrated that the flame could get accelerated due to the hydrodynamic instability and obstacle-induced turbulence, which enhanced the explosion overpressure. In the near field, the overpressure wave travelled slower and the maximum overpressure could almost keep constant. Reducing the cross section size, or increasing the obstacle height or the obstacle number per layer could determine the rise of the maximum overpressure, the maximum pressure rising rate and the overpressure impulse. For uniformly constructed obstacles, self-similar theory was chosen to measure the influence of the hydrodynamic instability, and a parameter β was adopted to measure the flame acceleration caused by obstacle-induced turbulence, the value of which was 2 in this research. Based on the acoustic theory, an overpressure prediction model was proposed and the predicted results agreed with the measured values better than previous models, such as TNT equivalency model and TNO multi-energy model.     

Evaluation on consequences prediction of fire accident in emergency processes for oil-gas storage and transportation by scenario deduction

This paper takes the safety in emergency processes as the starting point, from the perspective of scenario deduction, to study the consequences of fire accidents for oil-gas storage and transportation. Through the statistical analysis of actual accident cases, 19 frequently occurring basic scenarios in emergency processes are summarized. The scenario evolution paths of fire accidents for oil-gas storage and transportation are given by analyzing the evolution law of the accident development. Fuzzy numbers are introduced to express experts' qualitative judgment on accident scenarios. The empirical probabilities of scenario nodes are obtained by defuzzification calculation, and the state probability of each scenario node is calculated by using the dynamic Bayesian network joint probability formula. Under the comprehensive consideration about the probability statistics of actual accident cases, the critical scenario nodes on the evolution path and their final scenario probabilities are jointly determined to realize the optimization of the scenario evolution path. By constructing the correlation between the optimized scenario evolution path and the accident consequences, an accident consequence prediction model is established. The occurrence probability of accident consequences is calculated by the defuzzification method and dynamic Bayesian network. The accuracy of the consequence prediction model is verified by the July 16 Dalian's Xingang Harbor oil pipeline explosion accident. The research results provide scientific basis for helping decision makers to make the effective emergency measures that are most conducive to the rapid elimination of accidents and reducing the severity of accident consequences.     

Safety evaluation of leak in a storage tank using fault tree analysis and risk matrix analysis

The work presented in this paper used a quantitative analysis of relevant risks through the development of fault tree analysis and risk analysis methods to aid real time risk prediction and safety evaluation of leak in a storage tank. Criticality of risk elements and their attributes can be used with real time data to predict potential failures likely to occur. As an example, a risk matrix was used to rank risk of events that could lead to a leak in a storage tank and to make decisions on risks to be allowed based on past statistical data. An intelligent system that recognizes increasing level(s) and draws awareness to the possibility of additional increase before unsafe levels are attained was used to analyse and make critical decisions. After a visual depiction of relationships between hazards and controls had been actualized, dynamic risk modelling was used to quantify the effect controls can potentially have on hazards by applying historical and real-time data into a probabilistic model. The output of a dynamic risk model is near real-time quantitative predictions of risk likelihood. Results from the risk matrix analysis method mixed with RTD and FTA were analyzed, evaluated, and compared.     

Effective method of predicting confined pressure behavior under isotropic turbulence

Explosion pressure prediction is indispensable to ensure process safety against accidental gas explosions. This work is aimed at establishing a theoretical method for predicting confined methane-air explosion pressure under isotropic turbulence. The results indicated that the pressure rise rate becomes significantly increased by the existence of isotropic turbulence, which effect on peak value of explosion pressure is negligible. Among various models of turbulent burning velocity, the calculated pressure rise rate using Chiu model, Williams model and Liu model is relatively closer to experimental value. With the increase of turbulent integral length and RMS turbulent fluctuation velocity, the pressure rise rate becomes increased continuously. The influence of adiabatic compression and isothermal compression on pressure rise rate could be ignored. To predict explosion pressure in a more accurate way, the dynamic variation of turbulent integral length and RMS turbulent fluctuation velocity should be considered in the future.     

不同噪声强度对煤矿工人作业失误率的影响研究

为探究噪声强度对煤矿工人作业失误率的影响程度,采用实验室模拟试验和现场调研收集数据的方式对噪声和作业失误率间的关系展开研究,利用模拟试验所得结果和煤矿现场调研收集结果分别构建噪声-作业失误率、噪声-“三违”数量回归预测模型,定量分析作业失误率、“三违”数量和噪声水平之间的关系,研究结果表明:煤矿“三违”数量、实验室模拟...     

基于等维新息灰色马尔科夫的地铁客流量预测*

为准确预测地铁客流量的发展趋势,采用等维新息灰色GM（1,1）预测模型与马尔科夫模型相结合的方式建立等维新息灰色马尔科夫模型,探讨等维新息灰色马尔科夫模型在地铁客流量预测领域的应用;运用平均相对误差、后验差比值和小误差概率3种指标对模型精度进行检验。结果表明:等维新息灰色马尔科夫模型与原始数列的拟合程度较高,预测精度等级为Ⅰ级（优）,优于传统灰色GM(1,1)模型和等维新息灰色GM(1,1)模型的预测精度,更加符合地铁客流的实际情况。     

库岸涉水滑坡危险性现状分析与预测评价

为合理评价库岸涉水滑坡危险性,基于层次分析法与模糊理论,构建滑坡危险性现状评价模型,并利用优化支持向量机构建滑坡变形预测模型,通过对比分析实现滑坡危险性综合判断.结果表明:大柿树滑坡危险性现状为69.78分,风险等级为Ⅲ级,属高度危险;通过危险性预测评价,滑坡变形呈持续增加趋势,将趋于不利方向发展;综合滑坡危险性现状分...