Download Advanced Machine Learning Technologies and Applications: by Hiroshi Sakai, Mao Wu, Michinori Nakata, Dominik Ślęzak PDF

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By Hiroshi Sakai, Mao Wu, Michinori Nakata, Dominik Ślęzak (auth.), Aboul Ella Hassanien, Abdel-Badeeh M. Salem, Rabie Ramadan, Tai-hoon Kim (eds.)

This publication constitutes the refereed court cases of the 1st foreign convention on complicated computer studying applied sciences and functions, AMLTA 2012, held in Cairo, Egypt, in December 2012. The fifty eight complete papers provided have been conscientiously reviewed and chosen from ninety nine intial submissions. The papers are prepared in topical sections on tough units and purposes, computer studying in development attractiveness and photograph processing, desktop studying in multimedia computing, bioinformatics and cheminformatics, facts category and clustering, cloud computing and recommender systems.

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Additional resources for Advanced Machine Learning Technologies and Applications: First International Conference, AMLTA 2012, Cairo, Egypt, December 8-10, 2012. Proceedings

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A Decision Tree- Rough set Hybrid System for Stock Market Trend Prediction. International Journal of Computer Applications 6(9), 1–6 (2010) 19. : Approximate Boolean Reasoning: Foundations and Applications in Data Mining. , Skowron, A. ) Transactions on Rough Sets V. LNCS, vol. 4100, pp. 334–506. Springer, Heidelberg (2006) 20. : Rough Sets – Theoretical Aspects of Reasoning about Data. Kluwer (1991) 21. : Rudiments of Rough Sets. Information Sciences 177(1), 3–27 (2007) 22. : A Statistical Method for Determining Importance of Variables in an Information System.

Currently, Petri nets are gaining a growing interest among people both in Artificial Intelligence due to its adequacy to represent the approximate reasoning process as a dynamic discrete event system [1]-[4],[9],[11]-[13],[15]-[17] as well as in Molecular Biology as a modeling tool to describe complex processes in developmental biology [5],[7]. In the paper [15], "Generalised F uzzy P etri N ets (GF P N s)" for knowledge representation and approximate reasoning have been proposed. G. Looney [9].

LNCS, vol. 3100, pp. 78–95. Springer, Heidelberg (2004) 4. : Rules in incomplete information systems. Information Sciences 113(3-4), 271–292 (1999) 5. : Representation of nondeterministic information. Theoretical Computer Science 29(1-2), 27–39 (1984) 6. : Systemy Informacyjne: Podstawy Teoretyczne. WNT (1983) (in Polish; English translation: Information Systems: Theoretical Foundations) 7. : Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers (1991) 8. , Yao, Y.

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