Dependence assessment in human reliability analysis based on D numbers and AHP

Zhou, Xinyi; Deng, Xinyang; Deng, Yong; Mahadevan, Sankaran

doi:10.1016/j.nucengdes.2016.12.001

Cited by 109 publications

(39 citation statements)

References 63 publications

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“…Math tools such as D-numbers and evidence theory are widely used to handle the uncertainties and the data fusion in these systems. [45][46][47][48] In these cases, a fuzzy approach is recommended over distributed CEP systems in future research. In the future, we also intend to include the hardware implementation and energy requirements for distributed CEP systems.…”

Section: Discussionmentioning

confidence: 99%

New parallel processing strategies in complex event processing systems with data streams

Xiao

Zhan

Lai

et al. 2017

International Journal of Distributed Sensor Networks

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Sensor network-based application has gained increasing attention where data streams gathered from distributed sensors need to be processed and analyzed with timely responses. Distributed complex event processing is an effective technology to handle these data streams by matching of incoming events to persistent pattern queries. Therefore, a well-managed parallel processing scheme is required to improve both system performance and the quality-of-service guarantees of the system. However, the specific properties of pattern operators increase the difficulties of implementing parallel processing. To address this issue, a new parallelization model and three parallel processing strategies are proposed for distributed complex event processing systems. The effects of temporal constraints, for example, sliding windows, are included in the new parallelization model to enable the processing load for the overlap between windows of a batch induced by each input event to be shared by the downstream machines to avoid events that may result in wrong decisions. The proposed parallel strategies can keep the complex event processing system working stably and continuously during the elapsed time. Finally, the application of our work is demonstrated using experiments on the StreamBase system regardless of the increased input rate of the stream or the increased time window size of the operator.

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Section: Discussionmentioning

confidence: 99%

New parallel processing strategies in complex event processing systems with data streams

Xiao

Zhan

Lai

et al. 2017

International Journal of Distributed Sensor Networks

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“…Many math tools, such as AHP [37][38][39][40], fuzzy sets [41][42][43], D numbers [44][45][46][47], evidential reasoning [30,[48][49][50][51], and rough sets [52], are adopted with wide applications. In this section, the main concepts about the Dempster-Shafer (D-S) evidence theory are reviewed.…”

Section: Dempster-shafer Theory Of Evidencementioning

confidence: 99%

Evidential Model Validation under Epistemic Uncertainty

Deng

2018

Mathematical Problems in Engineering

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This paper proposes evidence theory based methods to both quantify the epistemic uncertainty and validate computational model. Three types of epistemic uncertainty concerning input model data, that is, sparse points, intervals, and probability distributions with uncertain parameters, are considered. Through the proposed methods, the given data will be described as corresponding probability distributions for uncertainty propagation in the computational model, thus, for the model validation. The proposed evidential model validation method is inspired by the idea of Bayesian hypothesis testing and Bayes factor, which compares the model predictions with the observed experimental data so as to assess the predictive capability of the model and help the decision making of model acceptance. Developed by the idea of Bayes factor, the frame of discernment of Dempster-Shafer evidence theory is constituted and the basic probability assignment (BPA) is determined. Because the proposed validation method is evidence based, the robustness of the result can be guaranteed, and the most evidence-supported hypothesis about the model testing will be favored by the BPA. The validity of proposed methods is illustrated through a numerical example.

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“…Facility location problem can be seen as a network optimization [55]. Many methods for optimization and decision-making under uncertainty, such as fuzzy sets [56][57][58], evidence theory [59], and D numbers [60][61][62], are applied to address this issue [63,64]. For the sake of simplicity, the problem is abstracted into a given undirected graph that consists of some network nodes.…”

Section: Problem Descriptionmentioning

confidence: 99%

Location of Facility Based on Simulated Annealing and “ZKW” Algorithms

Dong

Wang

Feng-hua

et al. 2017

Mathematical Problems in Engineering

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To cope with the facility location problem, a method based on simulated annealing and "ZKW" algorithm is proposed in this article. The method is applied to some real cases, which aims to deploy video content server at appropriate nodes in an undirected graph to satisfy the requirements of the consumption nodes with the least cost. Simulated annealing can easily find the optimum with less reliance on the initial solution. "ZKW" algorithm can find the shortest path and calculate the least cost from the server node to consumption node quickly. The results of three kinds of cases illustrate the efficiency of our method, which can obtain the optimum within 90 s. A comparison with Dijkstra and Floyd algorithms shows that, by using "ZKW" algorithm, the method can have large iteration with limited time. Therefore, the proposed method is able to solve this video content server location problem.

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Dependence assessment in human reliability analysis based on D numbers and AHP

Cited by 109 publications

References 63 publications

New parallel processing strategies in complex event processing systems with data streams

New parallel processing strategies in complex event processing systems with data streams

Evidential Model Validation under Epistemic Uncertainty

Location of Facility Based on Simulated Annealing and “ZKW” Algorithms

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