基于FUZZY-BN-FTA的厂区架空燃气管道泄漏可能性研究

为研究厂区架空燃气管道泄漏的故的可能性,提出模糊数学方法、贝叶斯网络模型以及故障树模型相结合的集成模型。通过GeNIe软件建立架空燃气管道泄漏事故的模糊贝叶斯网络模型;引入Leaky Noisy-or Gate扩展模型对模糊贝叶斯网络中节点的条件概率表进行修正,结合基本事件先验概率预测架空燃气管道泄漏的概率值,并引入3个基本事件重要度确定基本事件的重要性排序,同时进行敏感性分析确定主要影响因素,提出控制措施。研究结果表明:厂区车辆撞击、管道疲劳损耗、管材质量不佳、安装设计不合理、焊接缺陷为导致架空燃气管道泄漏的主要因素。研究结果可为工业企业安全管理人员有针对性地制定控制措施,减少事故发生率提供参考。

MATHEMATICAL EXPECTATION ABOUT DISCRETE RANDOM VARIABLE WITH INTERVAL PROBABILITY OR FUZZY PROBABILITY

The character and an algorithm about DRVIP（ discrete random variable with interval probability） and the secured kind DRVFP （discrete random variable with crisp event-fuzzy probability） are researched. Using the fuzzy resolution theorem, the solving mathematical expectation of a DRVFP can be translated into solving mathematical expectation of a series of RVIP. It is obvious that solving mathematical expectation of a DRVIP is a typical linear programming problem. A very functional calculating formula for solving mathematical expectation of DRVIP was obtained by using the Dantzig＇s simplex method. The example indicates that the result obtained by using the functional calculating formula fits together completely with the result obtained by using the linear programming method, but the process using the formula deduced is simpler.

RANDOM VARIABLE WITH FUZZY PROBABILITY

Mathematic description about the second kind fuzzy random variable namely the random variable with crisp event-fuzzy probability was studied. Based on the interval probability and using the fuzzy resolution theorem, the feasible condition about a probability fuzzy number set was given,go a step further the definition and characters of random variable with fuzzy probability (RVFP) and the fuzzy distribution function and fuzzy probability distribution sequence of the RVFP were put forward. The fuzzy probability resolution theorem with the closing operation of fuzzy probability was given and proved. The definition and characters of mathematical expectation and variance of the RVFP were studied also. All mathematic description about the RVFP has the closing operation for fuzzy probability,as a result, the foundation of perfecting fuzzy probability operation method is laid.

Decision making with fuzzy probability assessments and fuzzy payoff

A novel method for decision making with fuzzy probability assessments and fuzzy payoff is presented. The consistency of the fuzzy probability assessment is considered. A fuzzy aggregate algorithm is used to indicate the fuzzy expected payoff of alternatives. The level sets of each fuzzy expected payoff are then obtained by solving linear programming models. Based on a defuzzification function associated with the level sets of fuzzy number and a numerical integration formula (Newton-Cotes formula), an effective approach to rank the fuzzy expected payoff of alternatives is also developed to determine the best alternative. Finally, a numerical example is provided to illustrate the proposed method.

PROCEDURE FOR COMPUTING THE POSSIBILITY AND FUZZY PROBABILITY OF FAILURE OF STRUCTURES

Traditionally, the calculation of reliability of fuzzy random structures is based on the well-known formulation of probability of fuzzy events. But sometimes the results of this formulation will not indicating the real state of safety of fuzzy-random structures. Based on the possibility theory, a computational procedure for the reliability analysis of fuzzy failure problems and random-fuzzy failure problems of mechanical structures that contain fuzzy variables were presented. A procedure for the analysis of structural reliability of problems of fuzzy failure criterion was also proposed. The failure possibility of fuzzy structures and possibility distribution of the probability of failure of fuzzy-random structures can be given by the proposed methods. It is shown that for the hybrid probabilistic and fuzzy reliability problems, the probability of failure should be suitably taken as a fuzzy variable in order to indicate the real safety of system objectively. Two examples illustrate the validity and rationality of the proposed methods.

Intention Estimation of Adversarial Spatial Target Based on Fuzzy Inference

Estimating the intention of space objects plays an important role in air-craft design,aviation safety,military and otherfields,and is an important refer-ence basis for air situation analysis and command decision-making.This paper studies an intention estimation method based on fuzzy theory,combining prob-ability to calculate the intention between two objects.This method takes a space object as the origin of coordinates,observes the target’s distance,speed,relative heading angle,altitude difference,steering trend and etc.,then introduces the spe-cific calculation methods of these parameters.Through calculation,values are input into the fuzzy inference model,andfinally the action intention of the target is obtained through the fuzzy rule table and historical weighted probability.Ver-ified by simulation experiment,the target intention inferred by this method is roughly the same as the actual behavior of the target,which proves that the meth-od for identifying the target intention is effective.

FUZZY PROBABILITY PREDICTION METHOD FOR TROPICAL CYCLONE TRACK

Based on forecasting criteria of tropical cyclone categories of left and right turning and stable track and fuzzy mathematical principles, a fuzzy probability prediction method is formulated for track changes. It is 48-h valid for forecasting sudden change or stable track as well as giving fuzzy probability of trajectory, for the use in decision-making. As shown in operational experiments, if is easy to operate, simple to illustrate, objective to quantify.definite to conclude. and satisfactory to actualize. It is dependable with high level of reference, especially when the fuzzy probability is greater than 70%. for errors in direction and 48-h mean distance errors are all lower than those at major forecasting centers at home or abroad.

A Fuzzy Probability-based Markov Chain Model for Electric Power Demand Forecasting of Beijing, China

In this study, a fuzzy probability-based Markov chain model is developed for forecasting regional long-term electric power demand. The model can deal with the uncertainties in electric power system and reflect the vague and ambiguous during the process of power load forecasting through allowing uncertainties expressed as fuzzy parameters and discrete intervals. The developed model is applied to predict the electric power demand of Beijing from 2011 to 2019. Different satisfaction degrees of fuzzy parameters are considered as different levels of detail of the statistic data. The results indicate that the model can reflect the high uncertainty of long term power demand, which could support the programming and management of power system. The fuzzy probability Markov chain model is helpful for regional electricity power system managers in not only predicting a long term power load under uncertainty but also providing a basis for making multi-scenarios power generation/development plans.

Sequential Probability Ratio Test of Correlation Coefficient Using Fuzzy Hypothesis Testing

One of the important fields in statistics is testing hypothesis of correlation coefficient. The extension of the idea of testing correlation to fuzzy hypothesis is of great interesting. In this study, we examined the use of fuzzy hypothesis testing approach for the Sequential Probability Ratio Test (SPRT) of correlation coefficient. Use of fuzzy hypothesis testing for correlation coefficient with SPRT is illustrated by an example.

Multicut L-Shaped Algorithm for Stochastic Convex Programming with Fuzzy Probability Distribution

Two-stage problem of stochastic convex programming with fuzzy probability distribution is studied in this paper. Multicut L-shaped algorithm is proposed to solve the problem based on the fuzzy cutting and the minimax rule. Theorem of the convergence for the algorithm is proved. Finally, a numerical example about two-stage convex recourse problem shows the essential character and the efficiency.

Robust Design Rule with Definite Purpose Character Based on Fuzzy Probability and Study of its Characteristics

The design target with definite purpose character of product quality wasdescribed in a real fuzzy number ( named fuzzy target for short in this paper), and its membershipjunctions in common use were given. According to the fuzzy probability theory and the robust designprinciple, the robust design rule based on fuzzy probability (named fuzzy robust design rule forshort) was put forward and its validity and practicability were analyzed and tested with a designexample. The theoretical analysis and the design examples make clear that, while the fuzzy robustdesign rule was used, the fine design effect can be obtained and the fuzzy robust design rule can bevery suitable for the choice of the membership function of the fuzzy target; so it has a particularadvantage.

q-积三角模上的Fuzzy概率积分及其应用模型

针对新设计的一对q-Fuzzy和算子,及q-Fuzzy积算子,证明满足T三角模与S三角模条件,接着定义一种k-模糊测度,并在k-模糊测度空间下定义q-Fuzzy和概率积分;最后将q-Fuzzy和概率积分应用到医疗头盔性能优化上;对医疗头盔性能优化过程中采用优序图法和改进的反熵权法计算权重;其次应用模糊概率积分和结合最大概率原则对医疗头盔性能优化状态进行评估,并对评估结果进行排序;最后用模糊概率值得出的结果与模糊综合评价法得到的结果进行对比,结果是完全一致,验证了提出的q-Fuzzy和概率积分法更加精炼准确,克服了模糊综合评价结果的模糊性和辨识性。

故障树和模糊贝叶斯网络在管廊运维风险评估中的应用研究

地下综合管廊是城市的生命线,一旦出现问题就会对人们生命财产安全造成巨大损害。为了系统地分析管廊运维风险,建立了基于模糊贝叶斯网络的风险评估框架。首先,通过分析管廊运维风险源与风险形成的原因以确定风险事件和风险类别;其次,建立管廊运维风险故障树来梳理风险因素之间的逻辑关系,将故障树映射为贝叶斯网络;最后,结合专家模糊评价,构建地下综合管廊运维风险评估模型。案例分析结果显示:中间事件“火灾、爆炸”与“危害气体浓度过高”的发生概率较高。敏感性分析结果显示:“运维人员操作和维护不当”是导致管廊运维风险发生的根本事件,因此需要制定严格管理措施及规范,加强对运维人员的素质培训,以降低管廊运维过程中各种风险的发生概率。

概率融合的抗侧翻智能主动悬架控制研究

为了提升高质心车辆的侧倾稳定性和平顺性,降低车辆侧翻事故造成的伤亡率,提出一种基于概率融合隶属度函数构建理论的侧翻工况预测和控制方法。首先,通过采集车辆侧翻工况数据,选取车辆状态变量,基于影响权重确定与车辆侧翻相关的关键影响因子。其次,根据时间序列对数据进行时间片段划分,设计动态贝叶斯预测网络,对下一时间片段内车辆侧翻概率进行预测。最后,根据车辆性能参数与控制器参数的映射规则,建立概率融合的Takagi-Sugeno(T-S)模糊隶属度函数,设计车辆主动悬架抗侧翻鲁棒控制器。CARSIM/Simulink联合仿真结果表明,与被动悬架、半主动悬架、多目标控制主动悬架相比,所提方法可以平稳且高效地防止车辆侧翻,提升车辆行驶的安全性。

模糊概率法在薄皮甜瓜亲本自交系选择中的应用

为了筛选出薄皮甜瓜的优良亲本自交系,通过模糊概率法对35份自交系的生育日数、可溶性固形物含量、单株结果数、前期长势、口感、香味、裂果性、果实外观、单株产量9个指标进行综合评价,共筛选出10份性状优异的亲本自交系。排名第一的是M22-121,其单株结果数和单株产量均排名第一,分别为4.50个和1.155 kg,可溶性固形物含量为14.05%,排名第四,单瓜重为256.67 g。供试材料总体样本的数量性状中生育日数、可溶性固形物变异度较小,分别为1.75%和14.64%。变异系数较大的性状为单株结果数、单株产量、单瓜重,变异系数分别为30.28%、30.79%和35.37%,说明生产上应加强对这几个指标的选择,以获得较好的选择效果。

基于前景理论的疫后旅游景区交通方式选择行为

基于有限理性的前景理论构建了旅客出行方式选择模型,通过对某景区旅游者的个人信息、出行基本情况以及出行意向进行了调查分析,揭示出其出行行为的特点。并且进一步运用前景理论研究旅游者的出行方式选择行为,在完全理性和有限理性的条件下分别计算了各异质类旅客对不同客运方式的模糊选择概率。在此基础上,建立了基于有限理性作用下旅客个体出行决策的模型,得出了各异质类旅客对不同客运方式的出行偏好。通过比较不同类型旅客的出行偏好,可分析出高收入和务工旅客更倾向于驾车出行,而学生游客更倾向于乘坐大巴。相关研究的结论对于旅游景区周边交通设施的规划和建设有一定的指导意义,可更好地服务和满足游客的出行需求。

基于EMD-BiLSTM-ANFIS的负荷区间预测

考虑到新型电力负荷随机性增强,传统的准确预测方法已无法满足要求,提出一种EMD-BiLSTM-ANFIS(Empirical Mode Decomposition-Bi-directional Long Short-Term Memory-Adaptive Network-based Fuzzy Inference System)分位数预测负荷概率密度的方法,使用负荷预测区间取代点预测的准确数值,能为电力系统分析与决策提供更多数据,增强预测的可靠性。首先将原始负荷序列通过EMD(Empirical Mode Decomposition)分解成若干分量,并通过计算样本熵分为3类分量。然后将重构后的3类分量与由相关性筛选的外界因素特征采用BiLSTM、ANFIS模型进行训练和分位数回归(QR:Quantile Regression),并将分量的预测区间结果累加得到最终负荷的预测区间。最后利用核密度估计输出任意时刻用户负荷概率密度预测结果。通过与CNN-BiLSTM(Convolutional Neural Network-Bidirectional Long Short-Term Memory)、LSTM(Long Short-Term Memory)模型对比点预测及区间预测结果,证明了该方法的有效性。

具有Fuzzy概率的Fuzzy可靠性问题的求解途径

本文提出了工程实践中常见的清晰事件－Ｆｕｚｙ概率的Ｆｕｚｙ可靠性分析问题的求解途径。首先讨论了Ｆｕｚｙ数的代数运算法则，然后在此基础上将Ｆｕｚｙ可靠性求解问题转换为Ｆｕｚｙ数的运算问题，从而使这类Ｆｕｚｙ可靠性分析问题在理论上得到了解决。本文还给出了一个算例。

地下水影响下裂隙岩质边坡变形的 Fuzzy 测度分析

根据裂隙岩质边坡工程实际,采用 Fuzzy 数学理论中的 Fuzzy 测度理论,将工程开挖引起裂隙岩质边坡移动变形这一客观现象视为一模糊事件,依此建立了在地下水影响下岩体移动变形预测分析的 Fuzzy 测度模型。利用该模型可对边坡岩体移动变形参数进行反分析,并可对边坡开挖过程中引起的岩体移动变形进行定量计算,进而对地下水影响下岩质边坡总体稳定性和稳定程度进行预测。对已有的矿山边坡岩体移动变形及其稳定性进行了具体的分析预测,结果符合工程实际。

基于概率信息与协作学习的鲁棒T-S模糊建模方法

T-S模糊建模方法在非线性系统建模中取得了大量的应用.然而,T-S模型在参数辨识过程中忽略了结构风险项,同时没有考虑各个规则之间的联系,因此在数据受到非高斯噪声和异常点的影响时,模型容易失效.针对以上不足,提出了基于概率信息与协作学习的模糊建模方法.该方法建立了规则之间协作学习机制以保证模型的连续性、平滑性与鲁棒性,并进一步构建了包含正则化项、误差项、规则概率信息及规则之间协作关系项的目标函数,用于提高模型的泛化能力和建模性能.除此之外,建立了空间投影机制,将数据低维特征空间的非线性关系转换为高维投影空间的线性关系,以增强规则之间的协作性.针对该模型,建立了基于最小二乘的求解方法,获得了可靠的模型参数.数学算例仿真和实际锻压实验表明:所提出的方法在面对噪声以及强非线性影响时,依然能在规则数较低的情况下保持优秀的建模性能.对比其他优秀的模糊建模方法,该模型有着更强的抗干扰能力,且建模均方根误差(RMSE)远低于其他建模方法.综上所述,所提出的方法对传统方法和建模理论进行了改进,即使面对强非线性系统拥有较强的泛化能力、鲁棒性以及优秀的建模能力,并且能够以较少的模糊规则对工程当中非线性、不确定性系统建模.