Using discussion logic in analyzing online group discussions: A text mining approach

We propose a Discussion Logic-based Text Analytics (DiLTA) framework, which combines theories developed in social science and text mining fields. The framework extracts features that uncover discussion logic and uses these features in analyzing online discussions. A series of models are proposed including conversation disentanglement, coherence analysis, and visualization. Validation experiments showed that DiLTA achieved significantly superior performance over existing text analytics methods in reconstructing internal structure. A case study using DiLTA-enabled visualization on a healthcare forum illustrates the great potential of DiLTA in assisting comprehension of the internal linkage, structure, and logic of online group discussions.     

基于GO法的单输出爆炸逻辑网络系统可靠性分析

为有效提高爆炸逻辑网络系统可靠性水平,识别系统的薄弱环节,基于GO法(goal oriented methodology)原理建立了爆炸逻辑网络可靠性分析方法。根据某单输出爆炸逻辑网络的工作原理建立了GO图模型,并利用状态组合法进行可靠性定量计算和定性分析,结果表明单输出爆炸逻辑网络系统的可靠度为0.977,最小割集为雷管I_1、雷管I_2、雷管I_3、零门N_1和零门N_3。建立了单输出爆炸逻辑网络系统的可靠性框图,并计算了系统可靠度,结果与GO法状态组合法一致,验证了GO法运用于单输出爆炸逻辑网络可靠性分析的可行性。     

长江武惠堤堤防渗透破坏风险计算模型及应用

针对渗透水压力引起堤防渗透破坏问题,以堤防渗透破坏风险为目标,考虑堤防计算水位条件和土层渗透系数的不确定性,建立了堤防渗透破坏风险计算模型。以长江武惠堤17+750断面为例,对汉口水文站水位监测资料进行分析并拟合水位概率密度函数,对该断面渗流规律进行有限元分析,从而拟合渗透破坏概率密度函数,以此建立该断面堤防渗透破坏风险定量表达式。研究结果表明,武惠堤17+750断面堤防在警戒水位与防洪设计水位下,渗透破坏概率分别为0.442 9、0.764 0,渗透破坏风险分别为0.001 421、0.002 52;堤防渗透破坏风险随着堤外水位的升高而增加,但在防洪设计水位内运行时,堤防渗透破坏风险低,堤防渗流安全可得到有效控制。     

Throughput-based fair bandwidth allocation in OBS networks

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max-min fairness in traditional IP networks to the fair-loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput-based-FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.     

变分布的量子行为粒子群优化算法求解工程约束优化问题

针对工程形状设计领域中带有多个约束条件的非线性设计优化问题,提出了一种自适应的基于高斯分布的量子行为粒子群优化(AG-QPSO)算法。通过自适应地调整高斯分布,AG-QPSO算法能够在搜索的初始阶段有很强的全局搜索能力,随着搜索过程的进行,算法的局部搜索能力逐渐增强,从而满足了算法在搜索过程不同阶段的需要。为了验证算法的有效性,在压力容器和张弦设计问题这两个工程约束优化问题上进行50轮独立实验。实验结果表明,在满足所有约束条件的情况下,AG-QPSO算法在压力容器设计问题上取得了5890.9315的平均解和5885.3328的最优解,在张弦设计问题上取得了0.01096的平均解和0.01096的最优解,远优于标准粒子群优化(PSO)算法、具有量子行为的粒子群优化(QPSO)算法和高斯量子行为粒子群(G-QPSO)算法等现有的算法的结果,同时AG-QPSO算法取得的结果的方差较小,说明该算法具有很好的鲁棒性。     

A hybrid evaluation method for human error probability by using extended DEMATEL with Z-numbers: A case of cargo loading operation

Human error probability (HEP) evaluation and prediction is one of the most significant tasks to enhance human reliability in marine industry. Among various kinds of HEP evaluation techniques, the Human Error Assessment and Reduction Technique (HEART) technique is regarded as an effective and empirical tool that has been widely adopted in various fields. However, current HEART techniques are insufficient to address HEP evaluation problem in which the self-assurance of expert's judgment and inter-dependencies between Error-producing conditions (EPCs) are considered. Therefore, the purpose of this paper is to develop a hybrid HEART framework (H-HEART-F) to address this problem by integrating Z-numbers and the decision-making trial and evaluation laboratory (DEMATEL) method. First, the Z-numbers are introduced to model the uncertainty and self-assurance of evaluation information from various experts. Then, the Z-number power weighted average (Z-PWA) operator is proposed to aggregate the individual evaluation information into a group direct influenced matrix. Next, an extended DEMATEL method based on possibility degree measure is constructed to determine the proportion of effect of each EPC by considering the self-assurance of expert's judgment and inter-dependencies between EPCs. Finally, the HEP estimation for the cargo loading operation in oil or chemical tanker ship is presented to demonstrate the availability and feasibility of the H-HEART-F. After that, the sensitivity analysis and comparison study are conducted to further illustrate the reasonableness and effectiveness of the proposed method.     

Efficient estimation of extreme quantiles using adaptive kriging and importance sampling

This study considers an efficient method for the estimation of quantiles associated to very small levels of probability (up to O(10⁻⁹)), where the scalar performance function J is complex (eg, output of an expensive-to-run finite element model), under a probability measure that can be recast as a multivariate standard Gaussian law using an isoprobabilistic transformation. A surrogate-based approach (Gaussian Processes) combined with adaptive experimental designs allows to iteratively increase the accuracy of the surrogate while keeping the overall number of J evaluations low. Direct use of Monte-Carlo simulation even on the surrogate model being too expensive, the key idea consists in using an importance sampling method based on an isotropic-centered Gaussian with large standard deviation permitting a cheap estimation of small quantiles based on the surrogate model. Similar to AK-MCS as presented in the work of Schöbi et al., (2016), the surrogate is adaptively refined using a parallel infill criterion of an algorithm suitable for very small failure probability estimation. Additionally, a multi-quantile selection approach is developed, allowing to further exploit high-performance computing architectures. We illustrate the performances of the proposed method on several two to eight-dimensional cases. Accurate results are obtained with less than 100 evaluations of J on the considered benchmark cases.