Computer and Information Sciences - ISCIS 2004: 19th by Erol Gelenbe (auth.), Cevdet Aykanat, Tuǧrul Dayar, İbrahim PDF

By Erol Gelenbe (auth.), Cevdet Aykanat, Tuǧrul Dayar, İbrahim Körpeoğlu (eds.)

ISBN-10: 3540235264

ISBN-13: 9783540235262

ISBN-10: 3540301828

ISBN-13: 9783540301820

The sequence of ISCIS (International Symposium on computing device and knowledge Sciences) symposia were held every year because 1986, as a rule in Turkey and infrequently out of the country. it's the major machine technology and engineering assembly equipped through Turkish teachers and was once based by means of Erol Gelenbe. every year ISCIS draws a signi?cant variety of overseas members from around the world. The nineteenth ISCIS used to be geared up by means of Bilkent college, division of desktop Engineering, and used to be held in Kemer-Antalya, Turkey in the course of 27–29 October 2004. For ISCIS 2004, a complete of 335 papers went throughout the overview method and plenty of high quality papers competed for reputation. This quantity of the Springer Lecture Notes in laptop technological know-how (LNCS) sequence comprises a hundred of these papers that widely fall into the next parts of curiosity: arti?cial int- ligence and computing device studying, special effects and person interfaces, machine networksand safety, laptop imaginative and prescient and picture processing,databasesystems, modeling and function evaluate, typical languageprocessing, parallel and allotted computing, real-time keep watch over functions, software program engineering and programming structures, and conception of computing.

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Extra info for Computer and Information Sciences - ISCIS 2004: 19th International Symposium, Kemer-Antalya, Turkey, October 27-29, 2004. Proceedings

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12000 of these are used as learning set, and others are used in test. 85, respectively. 007895. The error is computed based on mean square error (MSE) [15]. Fig. 2. 000 iterations. After the off-line neural network training is finished, the neural network, which works online, is coded with obtained synaptic weights as seen in Figure 2. The neural network includes 20 neurons in the hidden layer, and it has been tried to obtain the neural network controller with the least number of perceptron in the hidden layer.

However, it has a complex computational structure and needs too much computation time. On the other hand, a neural network can give results rather quickly. In the simulation studies, it is observed that the training process is too much important for the accuracy of the obtained ANN control system. Generalization is also made through the reproduction of a situation that was absent from the training set. On the other hand, the system is more successful for the trajectory, which is in training set than one, which is not in training set.

ISCIS 2004, LNCS 3280, pp. 11–20, 2004. © Springer-Verlag Berlin Heidelberg 2004 12 et al. recognized and classified by different system units. In this paper, it was aimed to reach higher classification accuracy by assigning weights to important attributes in classification. This was done with some modifications to affinity measures of AISs and then a new system named AWAIS (Attribute Weighted Artificial Immune System) has come into existence. AiNet, one of the algorithms in which shape-space representation is used, is both a network-based and population-based AIS algorithm to be used in data mining and classification applications [4].

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Computer and Information Sciences - ISCIS 2004: 19th International Symposium, Kemer-Antalya, Turkey, October 27-29, 2004. Proceedings by Erol Gelenbe (auth.), Cevdet Aykanat, Tuǧrul Dayar, İbrahim Körpeoğlu (eds.)

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