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Computational Intelligence and Information Technology: First by K. Thirumalaivasan, R. Nakkeeran (auth.), Vinu V Das, Nessy

By K. Thirumalaivasan, R. Nakkeeran (auth.), Vinu V Das, Nessy Thankachan (eds.)

This booklet constitutes the court cases of the 1st overseas convention on Computational Intelligence and data know-how, CIIT 2011, held in Pune, India, in November 2011. The fifty eight revised complete papers, sixty seven revised brief papers, and 32 poster papers provided have been rigorously reviewed and chosen from 483 preliminary submissions. The papers are contributed through cutting edge lecturers and business specialists within the box of laptop technological know-how, details expertise, computational engineering, cellular conversation and safety and provide a level to a typical discussion board, the place a positive conversation on theoretical recommendations, sensible principles and result of the cutting-edge will be developed.

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Extra info for Computational Intelligence and Information Technology: First International Conference, CIIT 2011, Pune, India, November 7-8, 2011. Proceedings

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1 Split Complex RTRL for RNN Learning The mostly used algorithm used for training RNN is RTRL algorithm proposed by Williams et al. [12]. The inputs, outputs, weights, and activation functions in RTRL algorithm are assumed to be real valued. This algorithm is stable and able to do continuous processing in order to implement dynamical systems described by the temporal stream of their inputs and outputs. In case of Rayleigh fading channel, the input to the RNN predictor is complex, hence we need to use an RNN with complex weights and activation functions to approximate the behavior of the dynamic system [6].

3. Flowchart of system's operation 36 A. A. M. b. Fig. 5 shows a curve in n which hours of a day set on horizontal axis and outtput power of system with opttical sensor and also fixed system in 45 degree, sett on vertical axis. here hours of a day versus output power of adaptive tw woFig. 6 shows a graph wh axis system and fixed system m in 45 degree. Fig. 7 shows a graph where w hours of a day versus optput power of system w with optical sensor and adaptive two-axis system. b a Fig. 4. a) Electronic board, used to test, b) Photograph of presented sun tracker 8 7 output power of PV panel 6 5 4 3 2 1 0 fixed panel at 45 degree two-axis tracker with optical sensor 8 10 12 14 hours of a day 16 18 20 with Fig.

It should be mentioned that presented tracker is of two axis type, and it can regulate solar panel in horizontal and vertical directions. V. Das and N. ): CIIT 2011, CCIS 250, pp. 30–37, 2011. © Springer-Verlag Berlin Heidelberg 2011 A New Adaaptive Algorithm for Two-Axis Sun Tracker without Sensor 31 panel sets on a special anglle- usually in vertical direction- next output power of paanel is measured. The measured Power is sent to microcontroller, and then the azimuth and ulated by the algorithm.

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