Page 83 - Neşide Dergisi 6.Sayı

DOSYA

Kaynaklar 13. Fuzzy model for real-time reservoir opera-
tion. Journal of Water Resources Planning and Ma-
1- Kosko, B.: ”Fuzzy Engineering”, Prentice Hall. nagement Vol 128, N.O 1(2002) 66-73. (Co-authors
2- Klir, G. J.; Yuan, B.: ”Fuzzy Sets and Fuzzy Tanja Dubrovin and Ari Jolma.)
Logic Theory and Applications”, Prentice Hall. 14. Many-valued Similarity Reasoning. An Axi-
3- Goldberg, D. E.: ”Genetic Algortihms in Sear- omatic Approach. Int. Jour. Multiple-Valued Logic.
ch, Optimization, and Machine Learning”, Addison (2002) (Co-author Paavo Kukkurainen.)
Wesley Publishing Inc. 15. Traffic Signal Control on Similarity Logic Re-
4- Michalewicz, Z.: ”Genetic Algorithms + Data asoning. Fuzzy sets and Systems. (Co-author Jarkko
Structures = Evolution Programs “, Springer Verlag Niittymäki.)
5-Linkens, D. A.; Nyongesa, M.: ”Genetic Al- 16. Survey of Theory and Applications of Lu-
gorithms for Fuzzy Control Part 1: Offline systems kasiewicz-Pavelka Fuzzy Logic. in: Lectures on Soft
development and applications”, IEE Proc.-Control Computing and Fuzzy Logic. Advances in Soft Com-
Theory Applications, 142 (1995). puting. Physica-Verlag, Heidelberg 2001. 313-337.
(Eds. A. di Nola and G. Gerla).
6- Lee, A, M.;Takagi, H.:” Dynamic Control of
Genetic Algorithms using Fuzzy Logic Techniques”, 17. Dia, Hussein., Freeway Travel Time Estima-
Fifth International Conferenge on Genetic Algorith- tion Using Neural Networks, Proceedings of the 4 th
ms, Morgan Kaufmann, (1993). International Conference Smart Solution at
7- Chiang, K. C.; Chung, H. Y.; Lin, J. J.: “A Self Works, May, 1999, Adelaide.
Learning Fuzzy Logic Controller Using Genetic Al- 18. Dia, Hussein., An Object-Oriented Neural
gorithms with Reinforcement”, IEEE Transactions on Network Approach to Short-Term Traffic Forecastin-
th
Fuzzy Systems, 5, August, (1997). g,11 Mini Euro Conference on Artificial Intelligen-
8- Herrera, F.; Lozano, M.; Verdegay, J. L.: ”Ge- ce in Transportation Systems and Science, August,
netic Algorithms and Fuzzy Logic in Control Proces- 1999, Helsinki,Finland.
ses”, Technical Report #DECSAI 95109, Universidad 19. Dia, Hussein., (1996). Artificial Neural
de Granada, İspanya, (1995). Network Models for Automated Freeway Incident
9- Papageorgiou, M.; Kotsialos, A.: ”Freeway Detection. Ph. D.Dissertation. (Monash Universit-
Ramp Metering: An Overview”, IEEE Intelligent y:Clayton).
Transportation Systems Conference Proceeding, 20. Dia, Hussein. and Rose, G.(1998). Develop-
Dearbom (MI), USA, 2000 ment and Evulation of Neural Network Freeway
10- Teodorvic, D.; Vukadinovic,K.: ”Traffic Cont- Incident Detection Models Using Field Data. Spe-
rol and Transport Plannning A Fuzzy Setes and Neu- cial Issue on the Applications of Neural Network in
ral Networks Approach”, Kluwer academic Publis- Transportation. Transportation Research Part C, Vol.
her, (1998). 5, No. 5, pp..313-331
11- Taylor, C.; Meldrum, D.: ”Evaluation of a 21. Smith, B.L. and Demetsky, M.J. (1994).
Fuzzy Logic Ramp Metering Algortithms: A Compa- Short-Term Traffic Flow Prediction: Neural Network
rative Study Among three Ramp Metering Algorit- Approach Transportation Research Record, 1453,
hms used in Greater Seaattle Area”, Draft Research pp. 98-104
Report, University of Washington, 22. Dia, Hussein., (1997). Artificial Neural
12- Bogenberger, K.; Keller, H.: ”An Evoluti- Network Models for Automated Freeway Incident
onary Fuzzy System for Coordinated and Traffic Detection. Ph. D.Dissertation. (Monash University:
Responsive Ramp Metering”, Proceeding of the 34 Clayton).
th
Hawaii international Conferenge on System Scien-
ces, (2001).

YAPAY ZEKÂ

81