Computational science and its applications -- ICCSA 2009 : - download pdf or read online

By O Gervasi; MyiLibrary.; et al (eds)

ISBN-10: 364202453X

ISBN-13: 9783642024535

The two-volume set LNCS 5592 and 5593 constitutes the refereed lawsuits of the foreign convention on Computational technology and Its functions, ICCSA 2009, held in Seoul, Korea, in June/July, 2009. the 2 volumes comprise papers featuring a wealth of unique examine ends up in the sphere of computational technology, from foundational concerns in computing device technological know-how and arithmetic to complicated purposes in almost all sciences employing computational ideas. the subjects of the totally refereed papers are dependent in accordance with the 5 significant convention subject matters: computational tools, algorithms and clinical purposes, excessive functionality technical computing and networks, complex and rising applications,  in addition to info platforms and knowledge applied sciences. additionally, submissions from greater than 20 workshops and technical periods give a contribution to this publication. These disguise subject matters equivalent to geographical research, city modeling, spatial information, instant and advert hoc networking, logical, clinical and computational elements of pulse phenomena in transitions, high-performance computing and data visualization, sensor community and its functions, molecular simulations buildings and tactics, collective evolutionary structures, software program engineering procedures and functions, molecular simulations constructions and procedures, web verbal exchange protection, defense and privateness in pervasive computing environments, and cellular communications

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Additional resources for Computational science and its applications -- ICCSA 2009 : International Conference, Seoul, Korea, June 29 - July 2, 2009, Proceedings. Part 1

Example text

Another way to improve BP algorithm is to use variable learning rate. It is offered to speed up convergence by increasing learning rate on flat surfaces and decreasing the learning rate when the slope increases in the error valley. Different ways are introduced for varying the learning rate [25]. The following describes the procedure used in this study: The trajectory of error function without momentum The trajectory of error function with momentum Stable point Fig. 3. H. Vahidnia et al. i. If the squared error, over the entire training set, increases by more than some set percentage ξ (typically 1 to 4%) after a weight update, then the weight update is discarded, the learning rate η is multiplied by some factor 0<ρ<1, and the momentum coefficient α (if it is used) is set to zero.

H. Vahidnia et al. i. If the squared error, over the entire training set, increases by more than some set percentage ξ (typically 1 to 4%) after a weight update, then the weight update is discarded, the learning rate η is multiplied by some factor 0<ρ<1, and the momentum coefficient α (if it is used) is set to zero. ii. If the squared error decreases after a weight update, then the weight update is accepted and η is multiplied by some factor ε>1. If α has been previously set to zero, it is reset to its original value.

Our EPP is particularly characterized by an estimation of the timing, duration, and strength of every effect that it contains. These Using Causality Relationships for a Progressive Management of Hazardous Phenomena 9 parameters can be assessed beforehand or calculated on-the-fly. In this paper, we assume that the user provides the system with estimations of these parameters. From the spatial database that derives from our spatial model (Figure 5, left), we are able to determine the spatial positions that may be affected by every effect event in the EPP.

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Computational science and its applications -- ICCSA 2009 : International Conference, Seoul, Korea, June 29 - July 2, 2009, Proceedings. Part 1 by O Gervasi; MyiLibrary.; et al (eds)


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