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In order to solve the problem that previous relation researches in operational task-resource matching are hard to flexible computing for generating a new matching scheme from the existing scheme under the condition of operational tasks or resources adjusted in uncertainty cases, role-based approaches to operational task-resource flexible matching model and algorithm are proposed in the paper for flexible matching operational tasks with resources. Firstly, through introducing the concept of roles, the role-based calculation framework of operational task-resource flexible matching is constructed. Secondly, two aspect indexes about resource utilization ratio (RUR) and time utilization ratio (TUR) are given to reflect operational task-resource matching quality (TRMQ), which can be regarded as the objective function for modeling role-based operational task-resource flexible matching mathematical formulation. On the basis of this, the role-based artificial bee colony (RABC) algorithm, including five specific calculating operators, is put forward for solving the flexible matching problem with double encoding on operational tasks and resources by roles. Finally, via comparing with the previous methods in application cases, it can be validated that role-based model and proposed algorithm are more effective, which can be used to obtain a new incremental scheme from the existing matching scheme for adopting the operational tasks or resources adjustment. Moreover, there are flexible computation advantages of the approaches proposed in this paper to solve the problem about operational task-resource matching in large-scale. [ABSTRACT FROM AUTHOR]

Manned combat aerial vehicles (MCAVs), and unmanned combat aerial vehicles (UCAVs) together form a cooperative engagement system to carry out operational mission, which will be a new air engagement style in the near future. On the basis of analyzing the structure of the MCAV/UCAV cooperative engagement system, this paper divides the unique system into three hierarchical levels, respectively, i.e., mission level, task-cluster level and task level. To solve the formation and adjustment problem of the latter two levels, three corresponding mathematical models are established. To solve these models, three algorithms called quantum artificial bee colony (QABC) algorithm, greedy strategy (GS) and two-stage greedy strategy (TSGS) are proposed. Finally, a series of simulation experiments are designed to verify the effectiveness and superiority of the proposed algorithms. [ABSTRACT FROM AUTHOR]

To realize high accurate control of relative position and attitude between two spacecrafts, the coupling between position and attitude must be fully considered and a more precise model should be established. This paper breaks the traditional divide and conquer idea, and uses a mathematical tool, namely dual quaternion to establish the integrated 6 degree-of-freedom (6-DOF) model of relative position and attitude, which describes the coupled relative motion in a compact and efficient form and needs less information of the target. Considering the complex operation rules and the unclarity of the current relative motion model in dual quaternion, necessary mathematical foundations are given at first, followed by clear and detailed modeling process and analysis. Finally a generalized proportion-derivative (PD) controller law is designed. The simulation results show that based on the integrated model established by dual quaternion, this control law can achieve a high control accuracy of relative motion. [ABSTRACT FROM AUTHOR]

The traditional oriented FAST and rotated BRIEF (ORB) algorithm has problems of instability and repetition of keypoints and it does not possess scale invariance. In order to deal with these drawbacks, a modified ORB (MORB) algorithm is proposed. In order to improve the precision of matching and tracking, this paper puts forward an MOK algorithm that fuses MORB and Kanade-Lucas-Tomasi (KLT). By using Kalman, the object's state in the next frame is predicted in order to reduce the size of search window and improve the real-time performance of object tracking. The experimental results show that the MOK algorithm can accurately track objects with deformation or with background clutters, exhibiting higher robustness and accuracy on diverse datasets. Also, the MOK algorithm has a good real-time performance with the average frame rate reaching 90.8 fps. [ABSTRACT FROM AUTHOR]

Partial cooperation formulation is a more viable option than optimistic's and pessimistic's to solve an ill-posed bilevel programming problem. Aboussoror's partial cooperation model uses a constant as a cooperation index to describe the degree of follower's cooperation. The constant only indicates the leader's expectation coefficient for the follower's action, not the follower's own willingness. To solve this situation, a new model is proposed by using the follower's satisfactory degree as the cooperation degree. Then, because this new cooperation degree is a function which is dependent on the leader's choice and decided by the follower's satisfactory degree, this paper proves such proposed model not only leads an optimal value between the optimistic value and pessimistic's, but also leads a more satisfactory solution than Aboussoror's. Finally, a numerical experiment is given to demonstrate the feasibility of this new model. [ABSTRACT FROM AUTHOR]

The TODIM (an acronym in Portuguese for interactive and multiple attribute decision making) method is a valuable tool to solve the multiple attribute decision making (MADM) problems considering the behavior of the decision maker (DM), while it cannot be used to handle the problem with unknown weight information on attributes, in this paper, a novel method based on the classical TODIM method is proposed to solve the hybrid MADM problems with unknown weight information on attributes, in which attribute values are represented in four different formats: crisp numbers, interval numbers, triangular fuzzy numbers and trapezoidal fuzzy numbers. Firstly, the positive-ideal alternative and negative-ideal alternative are determined, and the gain and loss matrices are constructed by calculating the gain and loss of each alternative relatived to the ideal alternatives concerning each attribute based on different distance calculation formulas, which may avoid the information missing or information distortion in the process of unifying multiform attribute values into a certain representation form. Secondly, an optimization model based on the maximizing deviation (MD) method, by which the attribute weights can be determined, is established for the TODIM method. Further, the calculation steps to solve the hybrid MADM problems are given. Finally, two numerical examples are presented to illustrate the usefulness of the proposed method, and the results show that the DM's psychological behavior, attribute weights and the transformed information would highly affect the ranking orders of alternatives. [ABSTRACT FROM AUTHOR]

Model validation and updating is critical to model credibility growth. In order to assess model credibility quantitatively and locate model error precisely, a new dynamic validation method based on extremum field mean mode decomposition (EMMD) and the Prony method is proposed in this paper. Firstly, complex dynamic responses from models and real systems are processed into stationary components by EMMD. These components always have definite physical meanings which can be the evidence about rough model error location. Secondly, the Prony method is applied to identify the features of each EMMD component. Amplitude similarity, frequency similarity, damping similarity and phase similarity are defined to describe the similarity of dynamic responses. Then quantitative validation metrics are obtained based on the improved entropy weight and energy proportion. Precise model error location is realized based on the physical meanings of these features. The application of this method in aircraft controller design provides evidence about its feasibility and usability. [ABSTRACT FROM AUTHOR]

Dezert-Smarandache (DSm) theory, a new information fusion theory, is widely applied in image processing, multiple targets tracking identification, and other areas for its excellent processing ability of imperfect information. However, earlier research on DSm theory mainly focused on one sort of questions. An evidence fusion procedure is proposed based on the hybrid DSm model to compensate for a lack of research on the entire information procedure of DSm theory. This paper analyzes the evidence fusion procedure, as well as correlative node input and output information. Key steps and detailed procedures of evidence fusion are also discussed. Finally, an experiment illustrates the efficiency of the proposed evidence fusion procedure. [ABSTRACT FROM AUTHOR]