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This paper proposes a method of searching for missing people in mountains by UAVs (Unmanned Aerial Vehicles) based on beacon signals. This method alternately updates the distribution of estimated target position and unknown parameters by particle filtering, and determines the next best observation location based on the idea of the uncertainty sampling. We will show how this method can be integrated...
Dempster-Shafer evidence theory (DST) is a theoretical framework for uncertainty modeling and reasoning. The determination of basic belief assignment (BBA) is crucial in DST, however, there is no general theoretical method for BBA determination. In this paper, a method of generating BBA using fuzzy numbers is proposed. First, the training data are modeled as fuzzy numbers. Then, the dissimilarities...
Dempster-Shafer theory (DST) is an important theory for information fusion. However, in DST how to determinate the basic belief assignment (BBA) is still an open issue. The interval number based BBA determination method is simple and effective, where the features of different classes' samples are modeled using the interval numbers, i.e., an interval number model is constructed for each focal element...
Dempster-Shafer theory of evidence is widely applied to uncertainty modelling and knowledge reasoning because of its advantages in dealing with uncertain information. But some conditions or requirements, such as exclusiveness hypothesis and completeness constraint, limit the development and application of that theory to a large extend. To overcome the shortcomings and enhance its capability of representing...
To embed ensemble techniques into belief decision trees for performance improvement, the bagging algorithm is explored. Simple belief decision trees based on entropy intervals extracted from evidential likelihood are constructed as the base classifiers, and a combination of individual trees promises to lead to a better classification accuracy. Requiring no extra querying cost, bagging belief decision...
We investigates a two-echelon supply chain with one risk-natural supplier and one loss-averse retailer where there is one short life cycles product with stochastic demand. The loss-averse preference is adopted to describe the retailer's decision-making behavior. We introduce a combined contract by organically combining the quantity flexibility contract and the buy-back contract with this issue. It...
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...
This paper develops the design of a batteries charger. This charger works as power factor correction and delivers a DC voltage to the battery. To this, a bridgeless boost topology is used, this and the battery are modeled and then, an adaptive control strategy is developed. This have into account the battery changes to tune the controller and keep sinusoidal the input current and keep it in phase...
Using dictionary atoms to reconstruct input vectors is of great interest in spare representation. However, a key challenge is how to find a proper dictionary. In this paper, we introduce an active dictionary learning (ADL) method which incorporates active learning criteria to select atoms for dictionary construction with the consideration of both classification and reconstruction errors. Specifically,...
This paper investigates the robustness of strong structural controllability for linear time-invariant directed networked systems with respect to structural perturbations, including edge additions and deletions. In this regard, an algorithm is presented that is initiated by endowing each node of a network with a successive set of integers. Using this algorithm, a new notion of perfect graphs associated...
Decentralized control of large-scale active-passive modular systems is considered. These systems consist of physically interconnected and generally heterogeneous modules, where local control signals can be only applied to a subset of these modules (i.e., active modules) and the rest are not subject to any control signals (i.e., passive modules). Using a set-theoretic adaptive control approach predicated...
The control design problem for uncertain autonomous vehicle platoon system is considered. The uncertainty is possibly nonlinear and time-varying. Subject to the condition of collision avoidance, the original dynamical model for autonomous vehicle platoon system is designed with bounded state. After a state transformation, the bounded state is converted into a globally unbounded one. The swarm properties...
This paper discusses the resilient H∞ filtering problem for a class of continuous-time linear systems with D stability constraints. Attention is focused on the design of a filter such that the filtering error system is quadratic D stability and guarantees a prescribed H∞ performance level, where the filter to be designed is assumed to be with multiplicative gain variations. The design conditions for...
We introduce Stacked Thompson Bandits (STB) for efficiently generating plans that are likely to satisfy a given bounded temporal logic requirement. STB uses a simulation for evaluation of plans, and takes a Bayesian approach to using the resulting information to guide its search. In particular, we show that stacking multiarmed bandits and using Thompson sampling to guide the action selection process...
Randomized neural network (RNN) is a highly feasible solution in the era of big data because it offers a simple and fast working principle in processing dynamic and evolving data streams. This paper proposes a novel RNN, namely recurrent type-2 random vector functional link network (RT2McRVFLN), which provides a highly scalable solution for data streams in a strictly online and integrated framework...
This paper present the design of a PID controller based on state feedback. The parameters of our PID are computed using linear matrix inequality (LMI) technique and applied to active queue management (AQM) at router to avoid congestion. The results has been compared with other AQMs used in network like random early detection (RED) and random exponential markage (REM) in order to demonstrate the advantage...
Incompleteness in interval-valued information systems has leaded to many difficulties in acquiring knowledge. Rough set theory, proposed by Pawlak, has been widely used to deal with uncertainty, granularity and incompleteness of information. In this paper, we propose a θ-rough model for incomplete interval-valued information systems based on tolerance-similarity relation. Moreover, the accuracy, roughness...
This paper examines trading process and price behavior when the uninformed speculator comes into the market before the informed trader. The informed trader couldn't make trading directly in the market, and rumors can help the informed trader to enter into the market to make more great profit. We divide the informed trader's entering strategies into four ways, and find that the late informed trader...
Online model-free reinforcement learning (RL) methods with continuous actions are playing a prominent role when dealing with real-world applications such as Robotics. However, when confronted to non-stationary environments, these methods crucially rely on an exploration-exploitation trade-off which is rarely dynamically and automatically adjusted to changes in the environment. Here we propose an active...
In data processing, merging of data requires definition of conflict degree between source information in order to select the appropriate merging operator. The diversity of merging operators and the variability of information precision and source reliability generate great difficulty in the selection of the appropriate merging operator. Possibility theory and Dempster Shafer (DS) theory are two main...
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