Download Adaptive and Natural Computing Algorithms: 10th by Dominik Olszewski (auth.), Andrej Dobnikar, Uroš Lotrič, PDF

By Dominik Olszewski (auth.), Andrej Dobnikar, Uroš Lotrič, Branko à ter (eds.)

The two-volume set LNCS 6593 and 6594 constitutes the refereed court cases of the tenth foreign convention on Adaptive and average Computing Algorithms, ICANNGA 2010, held in Ljubljana, Slovenia, in April 2010. The eighty three revised complete papers awarded have been rigorously reviewed and chosen from a complete of a hundred and forty four submissions. the second one quantity contains forty-one papers geared up in topical sections on development popularity and studying, tender computing, structures concept, help vector machines, and bioinformatics.

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Additional resources for Adaptive and Natural Computing Algorithms: 10th International Conference, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part II

Example text

This proves to be very beneficial in a sense of widening the gap between distant regions of map units. Therefore, only BMUs are taken onto the second level of GSOM. 2 Gravitational Clustering Identified BMUs from the first level of algorithm are now being interpreted as ddimensional particles in the d-dimensional space with mass equal to unity. During iterations, each particle is being moved around according to a simplified version of the Gravitation Law using the Second Newton’s Motion Law as proposed in [8].

Fβ is the formula is Fβ = 1 + β 2 β 2 ·(P +R) harmonic mean of the precision and recall. In order to evaluate a binary decision task, we first define a contingency matrix representing the possible outcomes of the classification, namely the true positives (TP - positive examples classified as positive), the True Negatives (TN - negative examples classified as negative), the False Positives (FP - negative examples classified as positive) and the False Negative (FN - positive samples classified as negative).

An Experimental Study on Electrical Signature Identification 39 For both one-against-all methods, the good performance indicates that the composed signature can be an accurate description for each one of the appliances in the database. Nevertheless, these findings may be related to the fact that the number of electrical appliances used is still very small.

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