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With the increasing task demand for complex system, the timeliness of the system is becoming a prominent problem, especially in the inefficient system and may even lead to safety problems. This paper proposes a modeling method considering the issue of timeliness for complex system, in which the clock semantic information of MARTE (the modeling and analysis of real-time and embedded systems) is added into UML (United Modeling Language) model element through the extension mechanism of UML to describe the time constraint information. The UML model with MARTE annotation is recorded as a UML/MARTE model and the formal definition of the UML/MARTE model elements is given. Finally, the aircraft landing process is taken as an example to carry out modeling analysis to verify the validity of the model.

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With the advancement of modern technology and the improvement of the level of social productivity, people are paying more and more attention to the reduction of labor intensity and the change of working environment. At the same time, in order to explore the application of multisensor fusion in the design and operation algorithm of manipulator mechanical system, we first introduced the big data fusion, proposed the multisensor data fusion algorithm, and analyzed the gradient descent method, auxiliary filtering method, and Kalman filter. Finally, the rated motion parameters of each axis motor of the manipulator are analyzed, and at the same time, the motion state of each axis motor of the manipulator under nonrated speed is analyzed. The research proposal in this paper is aimed at contributing to improving productivity.

Bayesian Networks is a widely used formalism for representing uncertain knowledge in Artificial Intelligence. It has become the standard methodology for the construction of systems relying on probabilistic knowledge and has been applied in a variety of real-worlds tasks. In this work, we first present an index system for evaluating network information resource according to the study of predecessors as well as our own views. In addition, a method for evaluating network information resource using Bayesian Networks is proposed to construct the assessment model and effectively aggregate experts' knowledge and experience, especially, in the case of data missing. Then we apply the method to evaluate information resource of a website. The results show that the method is effective and reasonable.