Researches on Brittle Seam Mining based Enterprise Situation Assessment and Prediction Mechanism in Hi-tech Enterprise cooperation-competition network

• Published in: The 26th Chinese Control and Decision Conference (2014 CCDC) pp. 1407 - 1412
• Main Authors: Yi Zhuo, Shijun Yao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2014
• Subjects: Biological Invasions; Biological system modeling; Brittle Point and Brittle Seam; Brittle Seam Mining; Business; Data mining; Enterprise Cooperation-Competition Network; Enterprise Situation Assessment and Prediction; Monitoring; Real-time systems; Sociology; Statistics
• ISBN: 147993707X; 9781479937073
• ISSN: 1948-9439; 1948-9447
• DOI: 10.1109/CCDC.2014.6852387

The assessment of high-tech enterprise is of great importance to the government, because a region or even a country's economic development depends largely on the development of high-tech Enterprises in this region or country. According to the problem of Situation Assessment and Prediction of high-tech enterprises in the enterprise cooperation-competition network, the concepts of Brittle Point and Brittle seam are introduced, and a Situation Assessment and Prediction Mechanism based on the Brittle Seam Mining Algorithm is proposed. In the Brittle Seam Mining Algorithm, competition assessment indexes system of high-tech enterprises are introduced to mining different enterprises relations, and the Biological Invasions Model such as the population diffusion reaction model and the population reproduction model are adopted to predict and detect the Brittle Point and Brittle seam. Meanwhile, the GIS technology is used in the visualization of Brittle seam. The simulation results verify the applicability of this method.