Abstract
In this work a temperature predictor has been designed. The prediction is made by an artificial neural network multilayer perceptron. Initially, the floating point algorithm was evaluated. Afterwards, the fixed point algorithm was designed on a Field Programmable Gate Array (FPGA). The architecture was fully parallelized and a maximum delay of 74 ns was obtained. The design tool used is System Generator of Xilinx.
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References
Taylor, J.W., Buizza, R.: Neural network load forecasting with weather ensemble predictions. IEEE Transactions on Power Systems 17(3), 626–632 (2002)
Lee, R., Liu, J.: iJADE WeatherMAN: a weather forecasting system using intelligent multiagent-based fuzzy neuro network. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 34(3), 369–377 (2004)
Sharma, A., Manoria, M.: A Weather Forecasting System using concept of Soft Computing: A new approach. In: International Conference on Advanced Computing and Communications, ADCOM 2006, December 20-23, pp. 353–356 (2006)
Yona, A., Senjyu, T., Saber, A.Y., Funabashi, T., Sekine, H., Kim, C.-H.: Application of Neural Network to One-Day-Ahead 24 hours Generating Power Forecasting for Photovoltaic System. In: International Conference on Intelligent Systems Applications to Power Systems, ISAP 2007, November 5-8, pp. 1–6 (2007)
Wittmann, M., Breitkreuz, H., Schroedter-Homscheidt, M., Eck, M.: Case Studies on the Use of Solar Irradiance Forecast for Optimized Operation Strategies of Solar Thermal Power Plants. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 1(1), 18–27 (2008)
Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)
Tosini, M.: Sistema basado en redes neuronales digitales aplicado a la predicción climática en ambientes con microclima controlado. JCS&T 7(1) (April 2007)
Peña, D.: Análisis de Series Temporales. Alianza Editorial, España (2010) ISBN: 84-206-9128-3
Bautista, E.: Predicción de Múltiples Puntos de Series de Tiempo Utilizando Support Vector Machines. Computación y Sistemas 7(3) ISSN 1405-5546
Trejos, J.: Presentación de las redes neuronales al análisis de datos. Métodos Matemáticos aplicados a las Ciencias. VII y VIII Simposios. Costa Rica (1994)
Ruck, D.W., Rogers, S.K., Kabrisky, M., Oxley, M.E., Suter, B.W.: The multilayer perceptron as an approximation to a Bayes optimal discriminant function. IEEE Transactions on Neural Networks 1(4), 296–298 (1990)
Colina, E., Rivas, F.: Redes Neuronales Artificiales in Introducción a las Técnicas de Computación Inteligente. In: Aguilar, J., Rivas, F. (eds.). Editorial Meritec (2001)
Matlab Neural Network Toolbox, http://www.mathworks.com/products/neuralnet/ (active on July 1, 2011)
Maxfield, C.: The Design Warrior’s Guide to FPGAs. Elsevier (2004)
Xilinx System Generator, http://www.xilinx.com/tools/sysgen.htm (active on July 1, 2011)
Matlab Simulink, http://www.mathworks.com/products/simulink/ (active on July 1, 2011)
Xilinx ISE, http://www.xilinx.com/tools/webpack.htm (active on July 1, 2011)
Palnitkar, S.: Verilog HDL. Prentice Hall (1996)
Pedroni, V.A.: Circuit Design with VHDL. The MIT Press (2004)
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Pérez, S.T., Vásquez, J.L., Travieso, C.M., Alonso, J.B. (2011). Artificial Neural Network in FPGA for Temperature Prediction. In: Travieso-González, C.M., Alonso-Hernández, J.B. (eds) Advances in Nonlinear Speech Processing. NOLISP 2011. Lecture Notes in Computer Science(), vol 7015. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25020-0_14
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DOI: https://doi.org/10.1007/978-3-642-25020-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25019-4
Online ISBN: 978-3-642-25020-0
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