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Nowadays, the process of data mining is one of the most important topics in scientific and business problems. Grid Computing can be used as infrastructures to provide an effective computational support for distributed data mining applications. The paper proposed a data mining architecture from large-scale distributed and semantically heterogeneous data(More)
knowledge services can help users find or form solutions to some problems. But it is very difficult to perform knowledge discovery in distributed heterogeneous data. The paper proposed a personalized knowledge services system based on user context and ontology. Firstly, a user model is formally described by ontology knowledge according to user context. Then(More)
E-business and logistics systems provide support for business activities of many enterprises. But the heterogeneities of those systems hamper their interoperations and increase the cost of integration among different systems. This paper proposes an ontology-based semantic integration framework for e-business and logistics systems, which consists of the(More)
This paper is to design an intelligent weighing system to solve the problems in enterprises, such as incompatibility with hardware and software environment in different enterprise scenarios, the fixed interface layout and the dilemma that a single-way computational formulas can not fit the workflow of complementation of weighing system flexibly. A(More)
In this paper, we investigate the problem of autonomous integrated navigation of strapdown inertial navigation system (SINS)/ celestial navigation system (CNS) for a ballistic missile. To handle the nonlinear missile dynamic model, three filtering methods including extended Kalman filter (EKF), extended Kalman particle filter (EKPF) and unscented particle(More)
We propose an improved Unscented Particle Filter (UPF) algorithm for the Celestial Navigation System/Redshift (CNS/Redshift) integrated navigation system. The algorithm adopts the iterated spherical simplex unscented transformation rather than the traditional unscented transformation. The navigation per- formance of the proposed algorithm is assessed by(More)
Today, many public organizations, industries, and scientific labs produce and manage large amounts of complex data and information that are distributed and semantically heterogeneous. Knowledge acquisition from distributed data resources to support decision making is receiving an increasing attention. The paper proposes a distributed knowledge acquisition(More)
Attribute relation learning is important, but has been few studied. This paper proposes hybrid strategies for attribute relation acquisition from candidate attributes. The composition of candidate attributes is firstly analyzed and subdivided into three types: non-attribute vocabularies, invalid attribute, and valid attribute. Secondly, the HowNet-based(More)
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