Innovation design for complex products is a difficult issue in the military manufacturing industry. Ontology may provide a feasible way to rebuild the design process for complex products via sharing and reusing of design knowledge. In this paper, a design method used in the innovation design process of the complex products with knowledge modeling is proposed. Knowledge modeling is realized thro...

Modeling, designing and analyzing large scale multi-agent systems (MAS) with anywhere from tens of thousands to millions of autonomous agents will require mathematical and computational theories and models substantially different from those underlying the study of smallto medium-scale MAS made of only dozens, or perhaps hundreds, of agents. In this paper, we study certain aspects of the global ...

This paper deals with the early results of a new model of pedestrian flow, conceived within a measure-theoretical framework. The modeling approach consists in a discrete-time Eulerian macroscopic representation of the system via a family of measures which, pushed forward by some motion mappings, provide an estimate of the space occupancy by pedestrians at successive time steps. From the modelin...

Topic modeling on information networks is important for data analysis. Although there are many advanced techniques for this task, few methods either consider it into heterogeneous information networks or the readability of discovered topics. In this paper, we study the problem of topic modeling on heterogeneous information networks by putting forward LSAPTM. LSA-PTM first extracts meaningful fr...

nowadays, hidden markov models are extensively utilized for modeling stochastic processes. these models help researchers establish and implement the desired theoretical foundations using markov algorithms such as forward one. however, using stability hypothesis and the mean statistic for determining the values of markov functions on unstable statistical data set has led to a significant reducti...

Applying a knowledge-based approach to monitoring and controlling real-time systems is often infeasible because the execution time of backward-chaining queries is unpredictable. In this paper, we show how a decomposition of reasoning into forward and backward inference can bound the execution time of queries. We present a domain modeling technique with algorithms for classifying knowledge into ...