2014 International Conference on Informatics, Networking and by Jiaxing Zhang
By Jiaxing Zhang
This court cases quantity includes chosen papers offered on the 2014 foreign convention on Informatics, Networking and clever Computing, held in Shenzhen, China. Contributions conceal the most recent advancements and advances within the box of Informatics, Networking and clever Computing.
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Additional resources for 2014 International Conference on Informatics, Networking and Intelligent Computing
Blanning, R. W. 1996. A fuzzy logic framework for scenario support. Journal of Decision Systems, 5: 287–305. , & Lilly, J. H. 2004. Evolutionary Design of a Fuzzy Classifier from Data. IEEE Transactions on Systems, Man, and Cybernetics, 34(B): 1894–1906. , Fernández de Viana, I. & Herrera F. 2005. Learning Cooperative Linguistic Fuzzy Rules Using the Best-Worst Ant System Algorithm. International Journal of Intelligent Systems, 20: 433–452. , & Colorni, A. 1996. Ant System: Optimization by Colony of Cooperating Agents.
Business intelligence in risk management: Some recent progresses. Information Sciences 256 (2014), 1–7.  Neil Foshay, Craig Kuziemsky. Towards an implementation framework for business intelligence in healthcare. International Journal of Information Management, Volume 34, Issue 1, February 2014, Pages 20–27.  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.
This technique was proposed by Karaboga, (2005) and further improved by Karaboga & Basturk, (2008). The ABC algorithm works with a colony of artificial bees. The colony consists of three groups of bees: employed bees (workers), on lookers, and scouts. The position of a food source represents a possible solution to the optimization problem and the nectar amount of a food source corresponds to the quality (fitness) of the associated solution. The number of the employed bees or the onlooker bees is equal to the number of solutions in the population.