By Jiaxing Zhang
This lawsuits quantity includes chosen papers awarded on the 2014 overseas convention on Informatics, Networking and clever Computing, held in Shenzhen, China. Contributions hide the most recent advancements and advances within the box of Informatics, Networking and clever Computing.
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Additional info for 2014 International Conference on Informatics, Networking and Intelligent Computing
It is a critical issue to optimize the usage of city infrastructures and resources, improve city management and operating efficiency, and promote the sustainability of city’s development. In this paper, we present a city management system, which combines tightly geospatial information with business intelligence to provide more powerful management and decision-making functionalities. 2 RELATED WORKS City management systems collect huge amounts of data in their daily operations and transactions. These data include structured and unstructured data, such as text, image, audio, video and spatial information.
7] Heiner Lasi. Industrial intelligence-a business intelligence-based approach to enhance manufacturing engineering in industrial companies. Procedia CIRP, 12(2013), 384–389.  Sonia Rivest, Yvan Bédard, Marie-Josée Proul, Martin Nadeau, Frederic Hubert, Julien Pastor. SOLAP technology: Merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data. ISPRS Journal of Photogrammetry & Remote Sensing 60 (2005), 17–33. , Lebel, G. F. Integrating GIS components with knowledge discovery technology for environmental health decision support International Journal of Medical Informatics 70(1), 79–94, 2003.
IEEE Transactions on Systems, Man, and Cybernetics, 34 (B): 1031–1044. , & Nojima,Y. 1999. Improving the Performance of Fuzzy Classifier Systems for Pattern Classification Problems with Continuous Attributes. IEEE Transactions on Industrial Electronics, 46: 1057–1068. , & Nojima,Y. Analysis of interpretabilityaccuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning. International Journal of Approximate Reasoning, 44: 4–31. Karaboga, D. 2005. An Idea Based on Honey Bee Swarm for Numerical Optimization.