Entity

Time filter

Source Type


Yang J.-Y.,Yuncheng University | Yang J.-Y.,Beijing Institute of Information and Control | Wang X.-Y.,Yuncheng University | Li X.-Z.,Xinyang Normal University | And 2 more authors.
Computers and Mathematics with Applications | Year: 2011

An HIV-infection model is proposed, its global stability of the disease free equilibrium is studied, and existence of the endemic equilibria is analyzed. The observed data in a city in China is used to determine the parameters in the model using the least-squares approach. The theoretical prediction agrees well with the data available from a local government agency in the city. © 2010 Elsevier Ltd. All rights reserved. Source


Li Y.,Harbin Institute of Technology | Wu C.,Harbin Institute of Technology | Liu J.,Beijing Institute of Information and Control | Luo P.,Harbin Institute of Technology
International Journal of Computational Intelligence Systems | Year: 2014

Predicting stock composite index is useful, which can raise the interest of both the investors and the corresponding researchers. This paper presented a new combination prediction model based on the technique of artificial intelligence and the principle of combination forecast. The principle of combination forecast, as a valid foundation of the new model, was strictly proved and carefully illustrated in this paper. Given the predicting rules, the new combination model was established by synthesizing three commonly used prediction models based on the principle of combination forecast. The comprehensive usage of qualitative forecast and quantitative forecast is also a feature of the new model. To valid the new model, comparison analysis and multi-agent simulation were both applied. Besides, the application of multi-agent simulation made the new model able to guide the investors’ operations in a real stock market. According to the theoretical proof, the comparison analysis and the simulation experiment, the new combination prediction model tends to be a powerful and applicable tool in making the investment decisions. © 2014, the authors. Source


Wang Z.,Beijing Institute of Information and Control | Wang Z.,Northwestern Polytechnical University
Proceedings of 2011 International Conference on Computer Science and Network Technology, ICCSNT 2011 | Year: 2011

Semantic network is the development direction of the world wide web, and it converts the traditional system and the abstract one-dimension table into the associations between semantics through ontology construction, one party for the separation of field data and operating data while the other party to provide new starting point for further researches on field data and business logic reuse. At present the remote education theory put forward the new demand for the management of knowledge base and business logic reuse. We also made progress in the study of the ontology construction, semantic database management and other areas, so it's up to date to achieve a remote education system prototype based on the semantic network. The thesis is about the development of OntoLearning remote education system prototype. OntoLearning is a remote education network system of multilayer based on Web layer, service layer, business application layer, integrated layer and resource layer. It is a main function module covering teaching, file management, objective establishment, and progress management of remote education system, of which the ontology through RDF language briefly describes the semantic relations of teaching management of each party. © 2011 IEEE. Source


Li N.,Northwestern Polytechnical University | Wang R.,Beijing Institute of Information and Control | Tian Y.-L.,Northwestern Polytechnical University | Zheng W.,Northwestern Polytechnical University
Mathematical Problems in Engineering | Year: 2016

During past decades, many automated software faults diagnosis techniques including Spectrum-Based Fault Localization (SBFL) have been proposed to improve the efficiency of software debugging activity. In the field of SBFL, suspiciousness calculation is closely related to the number of failed and passed test cases. Studies have shown that the ratio of the number of failed and passed test case has more significant impact on the accuracy of SBFL than the total number of test cases, and a balanced test suite is more beneficial to improving the accuracy of SBFL. Based on theoretical analysis, we proposed an PNF (Passed test cases, Not execute Faulty statement) strategy to reduce test suite and build up a more balanced one for SBFL, which can be used in regression testing. We evaluated the strategy making experiments using the Siemens program and Space program. Experiments indicated that our PNF strategy can be used to construct a new test suite effectively. Compared with the original test suite, the new one has smaller size (average 90% test case was reduced in experiments) and more balanced ratio of failed test cases to passed test cases, while it has the same statement coverage and fault localization accuracy. © 2016 Ning Li et al. Source


Li Y.,Harbin Institute of Technology | Wu C.,Harbin Institute of Technology | Wang X.,Harbin Institute of Technology | Wu S.,Beijing Institute of Information and Control
Knowledge-Based Systems | Year: 2013

Identifying short message services (SMSs) seed users helps to discover the information's originals and transmission paths. A tree-network model was proposed to depict the characteristics of SMS seed users who have such three features as "ahead of time", "mass texting" and "numerous retransmissions". For acquiring the established network model's width and depth, a clustering algorithm based on density was adopted and a recursion algorithm was designed to solve such problems. An objective, comprehensive and scale-free evaluation function was further presented to rank the potential seed users by using the width and the depth obtained above. Furthermore, the model's empirical analysis was made based on part of the Shenzhen's cell phone SMS data in February of 2012. The model is effective and applicable as a powerful tool to solve the SMS seed users' mining problem. © 2012 Published by Elsevier B.V. All rights reserved. Source

Discover hidden collaborations