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Emergency decision itself is a scientific and complicated process, clarifying scarcity factors' influence on individual decision-making risk behaviors can help decision-making makers make a scientific decision. From scarcity factor in emergency, this study analyzes the decision-making risk behaviors, then puts forward the research hypotheses, Based on the questionnaire data, the research hypotheses...
In this paper, on the basis of sliding mode control theory, a new integral tangent adaptive fuzzy sliding mode control for aircraft engine was proposed. Based on the uncertainty model of aircraft engine, a hyperbolic tangent integral sliding surface was constructed at first, and it effectively overcome the problem of integral saturation effect which was often occur in the traditional integral sliding...
Reliable uncertainty estimation for time series prediction is critical in many fields, including physics, biology, and manufacturing. At Uber, probabilistic time series forecasting is used for robust prediction of number of trips during special events, driver incentive allocation, as well as real-time anomaly detection across millions of metrics. Classical time series models are often used in conjunction...
In large-scale data classification tasks, it is becoming more and more challenging in finding a true class from a huge amount of candidate categories. Fortunately, a hierarchical structure usually exists in these massive categories. The task of utilizing this structure for effective classification is called hierarchical classification. It usually follows a top-down fashion which predicts a sample...
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...
This paper presents an approach to trajectory tracking control for autonomous vehicles subject to parametric uncertainties. Such uncertainties may have the potential to significantly decrease the performance of the system, even to the point of destabilizing it. Therefore, these parametric variations must be taken into account during the design of the controller. To solve the trajectory tracking problem...
This paper introduces a multi-Bayesian framework for detection and classification of features in environments abundant with error-inducing noise. This approach takes advantage of Bayesian correction and classification in three distinct stages. The corrective scheme described here extracts useful but highly stochastic features from a data source, whether vision-based or otherwise, to aid in higher-level...
Background: research synthesis is still challenge in Software Engineering due to the heterogeneity of primary studies in the area. Also, it generates a significant volume of information which is complex to manage. Aims: to provide support to this kind of studies in SE. Method: we present the Evidence Factory, a tool designed to support the Structured Synthesis Method (SSM). SSM is a research synthesis...
Within the context of road estimation, the present paper addresses the problem of the fusion of several sources with different reliabilities. Thereby, reliability represents a higher-level uncertainty. This problem arises in automated driving and ADAS due to changing environmental conditions, e.g., road type or visibility of lane markings. Thus, we present an online sensor reliability assessment and...
We proposed two adaptive control methods for speed control of brushless direct current(BLDC) motor disturbed by two kinds of disturbances in this paper. The dynamic model of BLDC motor possessing either parametric uncertainties disturbed by unknown with known bound external disturbances or parametric uncertainties disturbed by unknown with known structure model external disturbances is considered,...
This paper addresses the robust non-fragile leader-following consensus problem for multi-agent systems against state-dependent uncertainties and controller coefficient variations. Without the requirement of knowledge of uncertainties of agents and controllers, adaptive distributed controllers are constructed to guarantee the follower agents tracking the leader agent. Asymptotic consensus results of...
We consider the problem of online robotic sampling in environmental monitoring tasks where the goal is to collect k best samples from n sequentially occurring measurements. In contrast to many existing works that seek to maximize the utility of the selected samples online, we aim to find the cardinality constrained subset of streaming measurements under irrevocable sampling decisions so that the prediction...
Deterrence is badly needed in the cyber domain but it is hard to be achieved. Why is conventional deterrence not working effectively in the cyber domain? What specific characteristics should be considered when deterrence strategies are developed in this man-made domain? These are the questions that this paper intends to address. The research conducted helps to reveal what cyber deterrence can do and...
This paper presents a new method for designing the weights used for development of robust controllers for a quadrotor model with parameter uncertainty. The weights alongside the controllers are developed for attitude and altitude tracking by resolving a constrained non-linear minimization problem formulated over the conventional mixed sensitivity optimization S over T method. The optimization routine...
In the field of architecture, 3D printing technology has the advantage of shortening the construction period by continuous addition and installing the desired shape and structure directly on site. However, the conventional 3D printer structure has limitations in practical use because of its versatility, mobility, and limited accessibility. In this study, a 3-axis gantry robot type 3D printing simulator...
Binarization is an important task in image processing. Numerous approaches to this problem are known: the thresholding algorithm, the Otsu method, etc. A promising direction in image processing is the use of fuzzy logic methods and the theory of fuzzy sets. Their use makes it possible to improve the quality of processing by providing information in a fuzzy form. Most of the existing fuzzy image processing...
Article deals with the problem of simulation modeling of robust control system for nonlinear plants with the input signal saturation, functioning under a priori uncertainty conditions and in the presence of several statement delays. With the help of computational experiments, the quality of the control system operation under various initial conditions of the controlled plant is illustrated.
The non-iterative algorithm that reveals the general physical basis of measuring processes and instrumental (computer) computations is proposed and investigated. The algorithm is based on the previously proposed postulate and consists in finding the optimal, locally defined width of the averaging interval. The optimal width of the interval provides the smallest error when measuring or computing the...
Consideration was given to construction of a robust control law for a class of scalar nonlinear dynamic plants under conditions of uncertainty and saturation of a control signal. The synthesis of the control law relies on the hyperstability criterion, L-dissipativity conditions and using in the main circuit an explicit reference model with two outputs and low-inertia filter-corrector.
Although many articles have shown that the control performance of interval type-2 fuzzy logic controllers (IT2 FLCs) is better than type-1 FLCs, the computational cost of it is high, which makes it hard to develop in the real world. Our previous research has recommended six TR approaches for their efficiency, but which one has the best performance is still an unknown problem. In the paper, IT2 FLCs...
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