Use of artificial neural networks to improve traffic flow on roads
DOI:
https://doi.org/10.26423/rctu.v3i2.152Keywords:
Artificial Intelligence, Artificial Neural Networks, FPGA, Simple Perceptron, intelligent traffic lightAbstract
This article aims to give an idea of how artificial Neural Networks (ANNs), a technique of Artificial Intelligence (AI) can be coupled to solve the problem of traffic on the roads in the city of Riobamba, Chimborazo province, country Ecuador using four standard traffic lights, through an example using electronic components such as FPGAs (Field Programmable Gate Array) and sensors in the field, by detecting and counting cars can give more fluidity to traffic indicated.
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References
Kornilov AR (1997)Intelligent technologies new opportunities for modern industry. Information Technology.vol.3(6), pp 1-14
DeboeckGuido J. (2000) Pattern recognition and prediction with self-organizing maps and ork /AIabtext.html supporting software review: visualizationthrough viscovery [en línea]. http://www.gordiand-knot.com Gordian Institute Electronic NewsLetter. [Consulta: 20 de febrero 2000.].
Neurofisiología [CD-ROM] Enciclopedia Microsoft(R) Encarta(R) 99. (c) 1993-1998 Microsoft Corporation.
Freeman J A and Skapura DM(1993) Redes Neuronales, Algoritmos, aplicaciones y técnicas de propagación. México: Addison-Wesley. 306 p.
Fff Hilera González J, Martínez Hernández V (1995) Redes neuronales artificiales: fundamentos, modelos y aplicaciones. Madrid, RA-MA. 389 p
Campanario JM(1995)Using neural networks to study networks of scientific journals. Scientometrics. vol. 33(1). pp 23-40.
Honkela T y otros (1996) Newsgroup exploration with WEBSOM method and browsing interface. Espoo. Helsinki, University of Technology, Laboratories of Computer and Information Science. (Technical Report, A32).
Kaski S y otros (1996)Creating an order in digital libraries with selft-organizing map. In: Proceeding of World Congress on Neural Networks.WCNN'96. Mahwah, NJ, INNS Press. pp814-817
Polanco Xavier, Francois C and Keim J F (1997) Artificial neural network technology for the classification and cartography of scientific and technical information. In: PerizBand Egghe L (1997) Procceding Sixth International Conference of the International Society for Scientometrics and Informetrics. Jerusalem, Israel.Universidad Hebrew of Jerusalem. pp. 319-330.
Swanson D R and Smalheiser N R (1997) An interactive system for finding complementary literatures: a stimulus to scientific discovery. Artificial Intelligence. vol. 91(3), vol. 183-203. También disponible en http://kiwi.uchicago.edu/web.
Rumelhart D E and McClelland J L (eds.) (1986) Parallel Distributed Processing. vo, 1: Foundations. MIT Press.
Fiesler E (1994) Neural Network clasification and formalization. En: Computer Standards and Interfaces. vol. 16, special issue on Neural Networks Standards, Fulcher J (edt.), Elseiver.
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Copyright (c) 2016 Edwin Mejía, Walter Armando Orozco Iguasnia

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