Applications of Evolutionary Computation: EvoApplications by Cecilia Di Chio, Anthony Brabazon, Marc Ebner, Muddassar

By Cecilia Di Chio, Anthony Brabazon, Marc Ebner, Muddassar Farooq, Andreas Fink, Jorn Grahl, Gary Greenfield, Penousal Machado, Michael O'Neill, Ernesto Tarantino, Neil Urquhart

This booklet constitutes the refereed court cases of the overseas Workshops at the purposes of Evolutionary Computation, EvoApplications 2010, held in Istanbul, Turkey, in April 2010 colocated with the Evo* 2010 occasions. because of the massive variety of submissions bought, the court cases for EvoApplications 2010 are divided throughout volumes (LNCS 6024 and 6025). the current quantity includes contributions for EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG. The forty seven revised complete papers offered have been conscientiously reviewed and chosen from a complete of 86 submissions. This quantity provides a cautious collection of correct EC examples mixed with a radical exam of the recommendations utilized in EC. The papers within the quantity illustrate the present cutting-edge within the software of EC and will aid and encourage researchers and execs to advance effective EC tools for layout and challenge fixing.

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In: GECCO 2007: Genetic and evolutionary computation Conference, London, UK (2007) 5. : IADIDS-Design of A Distributed Intrusion Detection System Based on Independent Agents. In: Proceedings of International Conference on Intelligent Sensing and Information Processing, pp. 254–257 (2004) 6. : Defending a Computer System using Autonomous Agents. In: Proceedings of the 18th National Information Systems Security Conference (1995) 7. : Immune System Approaches to Intrusion Detection - A Review. , Timmis, J.

M. B. Ayoob Fig. 3. Simulated real time AAA system pattern. Test signals: θ1 = -22°, θ2 = -8°, θ3 =8°, θ4 = 22°, ∆θ=15° and 4 dB SNR. Blue and green represent the true and test response respectively. Fig. 4. Simulated real time AAA system pattern. Test signals: θ1= -30°, θ2 = -40°, θ3 = -55°, θ4 = -70°, ∆θ=15°, and 4dB SNR. Blue and green represent the true and test response respectively. Fig. 3 shows a beam pattern when angular separation between test sources is 12° and their SNR is 4 dB, although the training was performed on sources of ∆θ = 10°.

Ima Uyar R-continuous Tests. R-continuous values changing from 8 up to 15 are applied to the improved jREMISA to decide the best r-continuous value that yields the best true and false positives. TCP, UDP and ICMP population sizes are 100 chromosomes each and 50% is used as affinity threshold value. As it is seen in Fig. 3, there is not a great difference in the results of true positives; most of them are above 97%. False positive rates are below 1,5 % except the first two. R-continuous value of 15 has 0% false positive rate.

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