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In the big data era, the information about the same object collected from multiple sources is inevitably conflicting. The task of identifying true information (i.e., the truths) among conflicting data is referred to as truth discovery, which incorporates the estimation of source reliability degrees into the aggregation of multi-source data. However, in many real-world applications, large-scale data...
Degradation reliability prediction under stochastic failure threshold is studied. The explicit expression of reliability is derived, by charactering the uncertainty of failure threshold with probability distribution. Then, a possibilistic approach for reliability modeling and prediction for degrading components is presented, by use of possibility distribution.
In multiple attribute decision analysis (MADA) problems, one often needs to deal with assessment information with uncertainty. The evidential reasoning approach is one of the most effective methods to deal with such MADA problems. As a kernel of the evidential reasoning approach, an original evidential reasoning (ER) algorithm was firstly proposed by Yang et al, and later they modified the ER algorithm...
Prioritization of non-functional requirements (NFRs) is a research field that needs more attention. We demonstrate ARRoW, a novel approach for automatic runtime reappraisal and update of the weights of NFRs given new evidence collected from the environment during the execution of the system. In this paper, we showcase how ARRoW is used in an substantial industrial case study. Our results shows how...
[Context/Motivation] Decision-making for self-adaptive systems (SAS) requires the runtime trade-off of multiple non-functional requirements (NFRs) and the costs-benefits analysis of the alternative solutions. Usually, it requires the specification of weights for NFRs and decision-making strategies. Generally, these weights are defined at design-time with the support of previous experiences and domain...
This paper investigates the various aspects of the capacity value of photovoltaic systems (PV-systems) and the effect of their penetration levels on power system reliability. Unlike wind power, the available output power of PV-systems can be classified into two specific time periods: certainly unavailable during the night and uncertainly available during the day. In other words, during the night,...
The collaborative recommendation mechanism is beneficial for the subject in an open network to find efficiently enough referrers who directly interacted with the object and obtain their trust data. The uncertainty analysis to the collected trust data selects the reliable trust data of trustworthy referrers, and then calculates the statistical trust value on certain reliability for any object. After...
The adoption of managerial decisions in quality management is characterized by the need to take into account both the presence of uncertainty and its impact on customer requirements, and the quality assessment as the degree to which the predicted result of innovation meets the expected requirements of consumers. It is proposed to use decision-making methods that do not take into account estimates...
Generally, investment decision is an evaluation of the proposed alternatives for the investor using a set of indicators. Evident, that to the start of the investment, the project should be finished and valid, however, search of investment resources and other difficulties can delay significantly start of the investment stage, which would increase risks. Therefore, it is important in addition to evaluating...
In this paper, we introduce the main concepts of a new maximum livelihood evidential reasoning (MAKER) framework for data-driven inferential modelling and decision making under different types of uncertainty. It consists of two types of model: state space model (SSM) and evidence space model (ESM), driven by the data that reflects the relationships between system inputs and output. SSM is constructed...
The Dempster-Shafer evidence combination method will appear inconsistent conclusions for the conflict evidence. One new universal evidence combination method was proposed. According to the concept of the Pearson correlation coefficient. Evidence distances which represent the conflict degree were calculated, and then the weight coefficient were further converted. The evidences probability were redistributed...
A cyber-physical system (CPS) typically utilizes networks of computers and communication systems to automatically monitor and manage the interactions and data exchanges between plant, sensor, controller and actuator elements within the CPS. The design and implementation of such a CPS are particularly challenging due to their requirements of high reliability and resiliency to possible components' failure...
Economy, reliability and environmental friendly are primary goals when modeling modern unit commitment problems. In this study, we establish a multi-objective unit commitment model considering the above objectives. In particular, the pricing support for ultra-low emissions is addressed together with startup/shutdown, generation and environment concerns when calculating the operation cost of thermal...
Testability growth is a process that aims to improve the testability level of the equipment via identifying and removing the testability design defects (TDDs). The establishment of the existing testability growth model (TGM) needs to consider a variety of factors, it's difficult to describe it accurately. To solve this problem, a TGM based on evidential reasoning (ER) method with nonlinear optimization...
Different belief sources often provide conflicting evidence, due to e.g. varying source reliability or deliberate deception. Source trust expresses the source reliability as seen by the analyst. In case of conflicting sources the analyst needs a strategy for managing and revising source trust. Intuitively, trust should be reduced for sources that produce advice which is in conflict with the ground...
Cloud service monitoring is a critical need for both providers and customers to assess the state of resources and the level of delivery of services. However, existing Cloud service monitoring methods are typically inapplicable in case the targeted service parameters are inaccessible, e.g., Cloud Service Providers do not allow external access to some service parameters for varied reasons (proprietary...
The problem of joint sequential change detection and isolation in a multichannel system is considered. It is assumed that a disruption occurs at some unknown time, and changes the distributions of the observations in an unknown subset of channels. The problem is to quickly detect the change, and at the same time to reliably isolate the affected channels. A novel scheme is proposed for this task, which...
This paper is a strong critic to the classical procedure used for the prediction of failure occurrences for mechanical and electronic equipment. The present procedure is based on the concept of randomness that has the undoubted vantage of the easiness, moreover, it is traditionally used so it is well known by scientists, technicians and experts in the field, but it a priori renounces to the knowledge...
In this paper we study how supervised machine learning could be applied to build simplified models of realtime (RT) reliability management response to the realization of uncertainties. The final objective is to import these models into look-ahead operation planning under uncertainties. Our response models predict in particular the real-time reliability management costs and the resulting reliability...
Importance measures for system reliability analysis are used to estimate the relative importance of components to the system reliability, and further to provide useful information to improve system performance. Components in phased mission systems (PMS) may have unequal structural importance working in different phases with different reliability logics, and their reliability parameters also may vary...
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