Documents disponibles écrits par cet auteur

Estimation of energy yield from wind farms using artificial neural networks / Mabel, M. Carolin in IEEE transactions on energy conversion, Vol. 24 N° 2 (Juin 2009) 

Public ISBD [article]  in IEEE transactions on energy conversion > Vol. 24 N° 2 (Juin 2009) . - pp. 459 - 464 Titre : Estimation of energy yield from wind farms using artificial neural networks Type de document : texte imprimé Auteurs : Mabel, M. Carolin, Auteur ; E. Fernández, Auteur Année de publication : 2009 Article en page(s) : pp. 459 - 464 Note générale : energy conversion Langues : Anglais (eng) Mots-clés : Mathematics  computing;  mean  square  error  methods;  neural  nets;  power  engineering  computing;  wind  power  plants Résumé : This paper uses the data from seven wind farms at Muppandal, Tamil Nadu, India, collected for three years from April 2002 to March 2005 for the estimation of energy yield from wind farms. The model is developed with the help of neural network methodology, and it involves three input variables-wind speed, relative humidity, and generation hours-and one output variable, which give the energy output from wind farms. The modeling is done using MATLAB software. The most appropriate neural network configuration after trial and error is found to be 3-5-1 (3 input layer neurons, 5 hidden layer neurons, 1 output layer neuron). The mean square error for the estimated values with respect to the measured data is 7.6times10-3. The results demonstrate that this work is an efficient energy yield estimation tool for wind farms. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4738388&sortType%3Das [...] [article] Estimation of energy yield from wind farms using artificial neural networks [texte imprimé] / Mabel, M. Carolin, Auteur ; E. Fernández, Auteur . - 2009 . - pp. 459 - 464. energy conversion Langues : Anglais (eng) in IEEE transactions on energy conversion > Vol. 24 N° 2 (Juin 2009) . - pp. 459 - 464 Mots-clés : Mathematics  computing;  mean  square  error  methods;  neural  nets;  power  engineering  computing;  wind  power  plants Résumé : This paper uses the data from seven wind farms at Muppandal, Tamil Nadu, India, collected for three years from April 2002 to March 2005 for the estimation of energy yield from wind farms. The model is developed with the help of neural network methodology, and it involves three input variables-wind speed, relative humidity, and generation hours-and one output variable, which give the energy output from wind farms. The modeling is done using MATLAB software. The most appropriate neural network configuration after trial and error is found to be 3-5-1 (3 input layer neurons, 5 hidden layer neurons, 1 output layer neuron). The mean square error for the estimated values with respect to the measured data is 7.6times10-3. The results demonstrate that this work is an efficient energy yield estimation tool for wind farms. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4738388&sortType%3Das [...]

A novel maximum dispersion territory design model arising in the implementation of the WEEE-directive / E. Fernández in Journal of the operational research society (JORS), Vol. 61 N° 3 (Mars 2010) 

Public ISBD [article]  in Journal of the operational research society (JORS) > Vol. 61 N° 3 (Mars 2010) . - pp. 503–514 Titre : A novel maximum dispersion territory design model arising in the implementation of the WEEE-directive Type de document : texte imprimé Auteurs : E. Fernández, Auteur ; J. Kalcsics, Auteur ; S. Nickel, Auteur Année de publication : 2011 Article en page(s) : pp. 503–514 Note générale : Recherche opérationnelle Langues : Anglais (eng) Mots-clés : Heuristics  Optimization  Logistics  Recycling  Territory  design Index. décimale : 001.424 Résumé : The problem discussed in this paper is motivated by the new recycling directive Waste Electrical and Electronic Equipment of the European Commission. The core of this law is, that each company which sells electrical or electronic equipment in a European country has the obligation to recollect and recycle an amount of returned items which is proportional to its market share. To assign collection stations to companies, in Germany for one product type a territory design approach is planned. However, in contrast to classical territory design, the territories should be geographically as dispersed as possible to avoid that a company, respectively its logistics provider responsible for the recollection, gains a monopoly in some region. First, we identify an appropriate measure for the dispersion of a territory. Afterwards, we present a first mathematical programming model for this new problem as well as a solution method based on the Greedy Randomized Adaptive Search Procedure methodology. Extensive computational results illustrate the suitability of the model and assess the effectiveness of the heuristic. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n3/abs/jors200970a.html [article] A novel maximum dispersion territory design model arising in the implementation of the WEEE-directive [texte imprimé] / E. Fernández, Auteur ; J. Kalcsics, Auteur ; S. Nickel, Auteur . - 2011 . - pp. 503–514. Recherche opérationnelle Langues : Anglais (eng) in Journal of the operational research society (JORS) > Vol. 61 N° 3 (Mars 2010) . - pp. 503–514 Mots-clés : Heuristics  Optimization  Logistics  Recycling  Territory  design Index. décimale : 001.424 Résumé : The problem discussed in this paper is motivated by the new recycling directive Waste Electrical and Electronic Equipment of the European Commission. The core of this law is, that each company which sells electrical or electronic equipment in a European country has the obligation to recollect and recycle an amount of returned items which is proportional to its market share. To assign collection stations to companies, in Germany for one product type a territory design approach is planned. However, in contrast to classical territory design, the territories should be geographically as dispersed as possible to avoid that a company, respectively its logistics provider responsible for the recollection, gains a monopoly in some region. First, we identify an appropriate measure for the dispersion of a territory. Afterwards, we present a first mathematical programming model for this new problem as well as a solution method based on the Greedy Randomized Adaptive Search Procedure methodology. Extensive computational results illustrate the suitability of the model and assess the effectiveness of the heuristic. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v61/n3/abs/jors200970a.html