Artificial Intelligence and Soft Computing: 13th by Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard

By Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada

The two-volume set LNAI 8467 and LNAI 8468 constitutes the refereed court cases of the thirteenth overseas convention on synthetic Intelligence and smooth Computing, ICAISC 2014, held in Zakopane, Poland in June 2014. The 139 revised complete papers provided within the volumes, have been conscientiously reviewed and chosen from 331 submissions. The sixty nine papers incorporated within the first quantity are fascinated by the next topical sections: Neural Networks and Their purposes, Fuzzy structures and Their functions, Evolutionary Algorithms and Their purposes, class and Estimation, laptop imaginative and prescient, picture and Speech research and certain consultation three: clever equipment in Databases. The seventy one papers within the moment quantity are geared up within the following topics: facts Mining, Bioinformatics, Biometrics and scientific purposes, Agent structures, Robotics and keep an eye on, synthetic Intelligence in Modeling and Simulation, numerous difficulties of man-made Intelligence, specified consultation 2: desktop studying for visible info research and defense, certain consultation 1: purposes and homes of Fuzzy Reasoning and Calculus and Clustering.

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Additional resources for Artificial Intelligence and Soft Computing: 13th International Conference, ICAISC 2014, Zakopane, Poland, June 1-5, 2014, Proceedings, Part I

Example text

The outcomes of our investigation can be used to improve efficient capturing of light in solar energy conversion cells [1]. Therefore, our main research interests are toward the properties of SPPs. SPPs are electromagnetic waves propagating along metal-dielectric interfaces and exist over a wide range of frequencies, evanescently decaying in the perpendicular direction. Such electromagnetic surface waves arise via the coupling of the electromagnetic fields to oscillations of the conductor electron’s plasma [7].

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Parallel realisation of the RTRN neural network learning. M. ) ICAISC 2008. LNCS (LNAI), vol. 5097, pp. 11–16. Springer, Heidelberg (2008) 4. : Parallel realisation of the recurrent Elman neural network learning. M. ) ICAISC 2010, Part II. LNCS (LNAI), vol. 6114, pp. 19–25. Springer, Heidelberg (2010) 5. : Parallel realisation of the recurrent multi layer perceptron learning. M. ) ICAISC 2012, Part I. LNCS (LNAI), vol. 7267, pp. 12–20. Springer, Heidelberg (2012) 6. : Parallel approach to learning of the recurrent Jordan neural network.

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