By Facchinetti Gisella, Franci Francesco, Mastroleo Giovanni, Pagliaro Vittorio (auth.), Jerzy Sołdek, Leszek Drobiazgiewicz (eds.)

ISBN-10: 144199226X

ISBN-13: 9781441992260

ISBN-10: 1461348471

ISBN-13: 9781461348474

Artificial Intelligence and defense in Computing Systems is a peer-reviewed convention quantity concentrating on 3 parts of perform and learn growth in details applied sciences:

-Methods of synthetic Intelligence provides tools and algorithms that are the foundation for purposes of synthetic intelligence environments.
-Multiagent Systems comprise laboratory examine on multiagent clever platforms in addition to upon their purposes in transportation and knowledge platforms.
-Computer safeguard and Safety provides suggestions and algorithms so one can be of significant curiosity to practitioners. in most cases, they specialize in new cryptographic algorithms (including a symmetric key encryption scheme, hash capabilities, mystery new release and sharing schemes, and safe facts storage), a proper language for coverage entry keep an eye on description and its implementation, and probability administration equipment (used for non-stop research either in allotted community and software program improvement projects).

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Extra resources for Artificial Intelligence and Security in Computing Systems: 9th International Conference, ACS’ 2002 Międzyzdroje, Poland October 23–25, 2002 Proceedings

Sample text

Dev. 33 64 MLPwith PCA LVQ without PCA 63 61 56 62 64 64 65 64 67 62 59 64 Tab. 1. , P9. Classification rule A performs as a "committee decision" on the basis ofthe majority of decis ions for cases PI - P9 (see [12]). Obtained results indicate the usefulness of neural networks in marketing data classification and in other similar issues. It is worth recommending the application ofMLP network (without PCA) in such a type ofproblems. 2 Cluster analysis of financial chart patterns (unsupervised process) In several areas of business and economy there is a need to perform cluster analysis.

An input layer transfers and distributes the input data in the network , one or more so called hidden layers actually process the information, and an output layer generates network output signals . The data is processed in a feed-forward manner (only in one direction , from input to output) [3, 13, 16, 19]. J. Sołdek et al. ), Artificial Intelligence and Security in Computing Systems © Springer Science+Business Media New York 2003 54 The neurons of hidden and output layers ofMLP generate their output signals y according to the rule (1): (1) where Xi is the i-th input signal (incoming to the given neuron) , Wi is the weight parameter of i-th input connection, and f is so called activation (transfer) function.

X) can be applied to a family of sets. By using it to equivalence classes obtained from a decision table we get a new measure instead of kwz , denoted by kAR . • a-approximation quality of D by C is expressed as follows: . dij -cardrC, nDj ) _ card Posc(D ) _ I- I j=1 card U - ~--'--'---c-a-r-d-U---- where d.. = lj 1 {0 if (10) e(Ci'D)~a otherwise where : n m a 4. 5. APPLICATION OF VPRS TO ANALYSIS OF PILOT'S DECISION MODEL In order to analyse the process of aircraft control by a pilot we must determine the necessary condition and decision attributes.

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Artificial Intelligence and Security in Computing Systems: 9th International Conference, ACS’ 2002 Międzyzdroje, Poland October 23–25, 2002 Proceedings by Facchinetti Gisella, Franci Francesco, Mastroleo Giovanni, Pagliaro Vittorio (auth.), Jerzy Sołdek, Leszek Drobiazgiewicz (eds.)


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