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MODELLEME VE BENZETİM ORTAMINDA PARAMETRE OPTİMİZASYONU VE KULLANILAN TEKNİKLER

Year 2017, Volume: 5 Issue: 3, 685 - 697, 25.12.2017
https://doi.org/10.21923/jesd.307125

Abstract

Bu
çalışmada farklı alanlarda yapılan bilgisayarda benzetim modeli çalışmaları
incelenmiştir. Yapılan çalışmaların ortak özelliği, gerçek ortamda gözlenmesi
ve incelenmesi zor olan karmaşık sistemlerden oluşmaktadır ve bu sistemleri
analiz edebilmek için benzetim modeline ihtiyaç duyulmaktadır. Modellenen
sistemin hedefi gerçek sistemi yansıtmasıdır. Bunu bir çok kriter belirlediği
gibi en önemli kriterlerden biri, geniş parametre uzayına sahip bu sistemlerin
istenen davranışı yansıtabilecek doğru parametrelerin kullanımını sağlamaktır.
Bunun için, parametre ayarlama işlemlerini otomatik ve sistematik bir şekilde
gerçekleştirebilecek bir takım yöntemlere ihtiyaç vardır.  Bu çalışmamızda modellenen sistemlerle
birlikte ortaya çıkan parametre ayarlama problemini çözmeye yönelik yapılan
çalışmaların çözüm önerileri ve kullanmış oldukları yöntemler kısaca
açıklanarak sunulmuştur.

References

  • Banjanovic-Mehmedovic, L., Karic, S. 2011. Robotic Assembly Replanning Agent Based on Neural Network Adjusted Vibration Parameters. ss. 297-312 Mellouk, A. ed. 2011. Advances in Reinforcement Learning, InTech, Rijeka
  • Başak, M.E., Kuntman, A., Kuntman, H. 2009. MOS parameter extraction and optimization with genetic algorithm, Journal of Electrical and Electronics Engineering, Istanbul University, 9(2), 1101-1107.
  • Benoît, C., Guillaume H. 2005. Automatic Tuning of Agent-Based Models Using Genetic Algorithms. International Workshop on Multi-Agent-Based simulation VI, July 25, Utrecht, 41-57.
  • Bolme, D.S., Beveridge, J.R., Draper, B.A., Phillips, P.J., Lui, Y.M. 2011. Automatically Searching for Optimal Parameter Settings Using a Genetic Algorithm. Computer Vision Systems - 8th International Conference (ICVS), 20-22 September 2011, Sophia Antipolis, 213-222.
  • Brax, N., Andonoff, E., Gleizes, M., Glize, P. 2013. Self-adapted aided decision-making: Application to maritime surveillance. Proceedings of the 5th International Conference on Agents and Artificial Intelligence (ICAART), 15-18 February, Barcelona, 419-422.
  • Bullnheimer, B., Hartl, R.F., Strauss, C. 1997. A New Rank Based Version of the Ant System: A Computational Study, Central European Journal for Operations Research and Economics, 7, 25-38
  • Calvez, B., Hutzler, G. 2005. Automatic tuning of agent-based models using genetic algorithms. Proceedings of the 6th International Workshop on Multi-Agent Based Simulation (MABS'05), 26 July, Utrecht, 41-57.
  • Calvez, B., Hutzler, G. 2007. Adaptive Dichotomic Optimization: a New Method for the Calibration Of Agent Based Models. 21st Annual European Simulation and Modelling Conference (ESM 2007), 22-24 October, Malta.
  • Darty, K., Saunier, J., Sabouret, N. 2015. Calibration of Multi-Agent Simulations through a Participatory Experiment. Proceedings of the 2015 International Conference on Autonomous Agents and Multi Agent Systems{AAMAS}, 4-8 May, İstanbul, 1683-1684.
  • Deliktaş, B., Türker, H.T., Coşkun, H., Bikçe, M., Özdemir, E. 2005. Genetik Algoritma Parametrelerinin Betonarme Kiriş Tasarımı Üzerine Etkisi. Bölgesel Jeoloji-Tektonik ve Sismotektonik Deprem Kaynak Mekanizmaları ve Dalga Yayınımı Sempozyumu, 23-25 Mart, Kocaeli, 46-54.
  • Dobslaw, F. 2010. A Parameter Tuning Framework for Metaheuristics Based on Design of Experiments and Artificial Neural Networks. Proceeding of the International Conference on Computer Mathematics and Natural Computing, 13-14 September, Rome, 213-216.
  • Doğru F. 2015. Güncel Optimizasyon Yöntemleri Kullanılarak Rezidüel Gravite Anomalilerinden Parametre Kestirimi. Hacettepe Üniversitesi Yerbilimleri Uygulama ve Araştırma Merkezi Bülteni, 36(1), 31-43.
  • Dorigo, M., Gambardella, L.M. 1997. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem, IEEE Transactions on Evolutionary Computation, 1(1), 53-66.
  • Gambardella, L.M., Dorigo, M. 1995. Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem. In Proceedings of the Eleventh International Conference on Machine Learning, 9-12 July, California, 252-260.
  • Imbault, F., Lebart, K. 2004. A stochastic optimization approach for parameter tuning of support vector machines. 17th International Conference on Pattern Recognition (ICPR), 23-26 August, Cambridge, 597-600.
  • Köse, U., Güraksın, E., Deperlioğlu, Ö. 2015. Girdap Optimizasyon Algoritması Tabanlı Destek Vektör Makineleri ile Diyabet Tespiti. Tıp Teknolojileri Ulusal Kongresi(TIPTEKNO), 15-18 Ekim, Muğla, 471-474.
  • Lee, S., Kang, S., Han, D. 2006. Agent-Based Flexible Video conference System with Automatic QoS Parameter Tuning. Trends in Artificial Intelligence, 9th Pacific Rim International Conference on Artificial Intelligence (PRICAI), 7-11 August, Guilin, 51-60.
  • Maniezzo, V., Colorni, A., Dorigo, M. 1994. The ant system applied to the quadratic assignment problem, IEEE Transactions on Knowledge and Data Engineering, 11(5), 769-778.
  • Manuel, F., Franziska, K., Frank, P. 2004. Techniques for Analysis and Calibration of Multi-Agent Simulations. ss. 305-321, Gleizes, M.P., Omicini, A., Zambonelli, F. ed. 2004. Engineering Societies in the Agent World(ESAW), Springer Berlin Heidelberg, Berlin.
  • Manuel, F., Franziska, K., Frank, P. 2006. Approaches for Resolving the Dilemma between Model Structure Refinement and Parameter Calibration in Agent Based Simulations. In 5th International Joint Conference on Autonomous Agents and Multi-agent Systems, 8-12 May, Hakodate, 120-122.
  • Öksüm, E., Dolmaz, M.N. 2006. Prizma Modelleri Kullanılarak Sentetik Mağnetik Anomalilerin Gauss-Newton Yöntemi ile Ters Çözümlenmesi. Süleyman Demirel Üniversitesi-Fen Bilimleri Enstitüsü Dergisi, 10(3), 437-446.
  • Pereira, A., Duarte, P., Reis, L.P. 2008. Agent-based Ecological Model Calibration - on the Edge of a New Approach. Computing Research Repository, abs/0809.1686, 107-113
  • Sallans, B., Pfister, A., Karatzoglou, A., Dorffner, G. 2003. Simulation and validation of an integrated markets model, J. Artificial Societies and Social Simulation, 6(4), 693-706
  • Salwala, C., Kotrajara, V., Horkaew, P. 2010. Improving Performance for Emergent Environments Parameter Tuning and Simulation in Games Using GPU. 2010 3rd International Conference on Computer Scienceand Information Technology (ICCSIT), 9-11 July, Chengdu, 37-41.
  • Saraçoğlu, H., Demirören, A. 2007. Parametreleri Genetik Algoritma ile Ayarlanan Bulanık Kontrolör Yardımıyla Otomatik Gerilim Kontrolü. Elektrik Elektronik-Bilgisayar Mühendisliği 12. Ulusal Kongresi, 14-18 Kasım, Eskişehir.
  • Saraçoğlu, B., Güvenç, U., Dursun, M., Poyraz, G, Duman, S. 2013. Biyocoğrafya Tabanlı Optimizasyon Metodu Kullanarak Asenkron Motor Parametre Tahmini. İleri Teknoloji Bilimleri Dergisi, 2(1), 46-54
  • Stützle, T., Hoos, H. 1997. The MAX-MIN Ant System and Local Search for the Traveling Salesman Problem. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC'97), 13-16 April, USA, 313-329.
  • Stützle, T., Hoos, H. 1997. Improvements on the Ant System: Introducing the MAX-MIN Ant System. ss. 245-249. Smith, George D., Steele, Nigel C., Albrecht, Rudolf F. ed. 1997. Artificial Neural Networks and Genetic Algorithms, Springer Vienna, Norwich.
  • Şahin, Y., Eroğlu, A. 2014. Kapasite Kısıtlı Araç Rotalama Problemi İçin Metasezgisel Yöntemler: Bilimsel Yazın Taraması, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 19(4), 337-355.
  • Valenzano, R.A., Sturtevant, N.R., Schaeffer, J., Buro, K., Kishimoto, A. 2010. Simultaneously Searching with Multiple Settings: An Alternative to Parameter Tuning for Suboptimal Single-Agent Search Algorithms. Proceedings of the 20th International Conference on Automated Planning and Scheduling-ICAPS, 12-16 May, Toronto, 177-184.
  • White, T., Pagurek, B., Oppacher, F. 1998. ASGA: Improving the Ant Systemby Integration with Genetic Algorithms. Proceedings of the Third Genetic Programming Conference, 22-25 July, Wiskonsin, 610-617.
  • Yanıkoğlu, H., Özkara, E., Yüceer, M. 2010. Kinetik Model Parametrelerinin Belirlenmesinde Kullanılan Optimizasyon Tekniklerinin Kıyaslanması. 9. Ulusal Kimya Mühendisliği Kongresi(UKMK-9), 22-25 Haziran, Ankara.
  • Yüceer, M., Atasoy, İ., Berber, R. 2004. Kinetik Modellerde Optimum Parametre Belirleme İçin Bir Yazılım: PARES, 6. Ulusal Kimya Mühendisliği Kongresi- UKMK-6, 7-10 Eylül, İzmir.
  • Yüceer, M., Atasoy, I, Berber, R. 2005. An integration based optimization approach for parameter estimation in dynamic models. Computer Aided Chemical Engineering, Cilt. 20(1), 631-636.
  • Yüceer, M., Atasoy, I., Berber, R. 2008. A software for parameter estimation in dynamic models. Brazilian J. of Chem. Engineering, Cilt. 25(4), 813 – 821.

PARAMETER OPTIMIZATION AND USED TECHNIQUES IN MODELING AND SIMULATION

Year 2017, Volume: 5 Issue: 3, 685 - 697, 25.12.2017
https://doi.org/10.21923/jesd.307125

Abstract











In this paper, the simulation model studies on computer made
in different fields are examined. The common feature of the work carried out is
that the work is related to complex systems which are difficult to observe and
analyze in the real environment thus, simulation models are needed to analyze
these systems. The goal of the modeled system is to reflect the real system. It
sets many criteria. One of the most significant is to use the correct
parameters which can reflect the desired behavior of these systems with large
parameter space. In this study proposed solution for the modeling systems'
problems associated with the parametere tuning and methods used by modelling
systems to solve these problems are briefly explained.

References

  • Banjanovic-Mehmedovic, L., Karic, S. 2011. Robotic Assembly Replanning Agent Based on Neural Network Adjusted Vibration Parameters. ss. 297-312 Mellouk, A. ed. 2011. Advances in Reinforcement Learning, InTech, Rijeka
  • Başak, M.E., Kuntman, A., Kuntman, H. 2009. MOS parameter extraction and optimization with genetic algorithm, Journal of Electrical and Electronics Engineering, Istanbul University, 9(2), 1101-1107.
  • Benoît, C., Guillaume H. 2005. Automatic Tuning of Agent-Based Models Using Genetic Algorithms. International Workshop on Multi-Agent-Based simulation VI, July 25, Utrecht, 41-57.
  • Bolme, D.S., Beveridge, J.R., Draper, B.A., Phillips, P.J., Lui, Y.M. 2011. Automatically Searching for Optimal Parameter Settings Using a Genetic Algorithm. Computer Vision Systems - 8th International Conference (ICVS), 20-22 September 2011, Sophia Antipolis, 213-222.
  • Brax, N., Andonoff, E., Gleizes, M., Glize, P. 2013. Self-adapted aided decision-making: Application to maritime surveillance. Proceedings of the 5th International Conference on Agents and Artificial Intelligence (ICAART), 15-18 February, Barcelona, 419-422.
  • Bullnheimer, B., Hartl, R.F., Strauss, C. 1997. A New Rank Based Version of the Ant System: A Computational Study, Central European Journal for Operations Research and Economics, 7, 25-38
  • Calvez, B., Hutzler, G. 2005. Automatic tuning of agent-based models using genetic algorithms. Proceedings of the 6th International Workshop on Multi-Agent Based Simulation (MABS'05), 26 July, Utrecht, 41-57.
  • Calvez, B., Hutzler, G. 2007. Adaptive Dichotomic Optimization: a New Method for the Calibration Of Agent Based Models. 21st Annual European Simulation and Modelling Conference (ESM 2007), 22-24 October, Malta.
  • Darty, K., Saunier, J., Sabouret, N. 2015. Calibration of Multi-Agent Simulations through a Participatory Experiment. Proceedings of the 2015 International Conference on Autonomous Agents and Multi Agent Systems{AAMAS}, 4-8 May, İstanbul, 1683-1684.
  • Deliktaş, B., Türker, H.T., Coşkun, H., Bikçe, M., Özdemir, E. 2005. Genetik Algoritma Parametrelerinin Betonarme Kiriş Tasarımı Üzerine Etkisi. Bölgesel Jeoloji-Tektonik ve Sismotektonik Deprem Kaynak Mekanizmaları ve Dalga Yayınımı Sempozyumu, 23-25 Mart, Kocaeli, 46-54.
  • Dobslaw, F. 2010. A Parameter Tuning Framework for Metaheuristics Based on Design of Experiments and Artificial Neural Networks. Proceeding of the International Conference on Computer Mathematics and Natural Computing, 13-14 September, Rome, 213-216.
  • Doğru F. 2015. Güncel Optimizasyon Yöntemleri Kullanılarak Rezidüel Gravite Anomalilerinden Parametre Kestirimi. Hacettepe Üniversitesi Yerbilimleri Uygulama ve Araştırma Merkezi Bülteni, 36(1), 31-43.
  • Dorigo, M., Gambardella, L.M. 1997. Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem, IEEE Transactions on Evolutionary Computation, 1(1), 53-66.
  • Gambardella, L.M., Dorigo, M. 1995. Ant-Q: A Reinforcement Learning Approach to the Traveling Salesman Problem. In Proceedings of the Eleventh International Conference on Machine Learning, 9-12 July, California, 252-260.
  • Imbault, F., Lebart, K. 2004. A stochastic optimization approach for parameter tuning of support vector machines. 17th International Conference on Pattern Recognition (ICPR), 23-26 August, Cambridge, 597-600.
  • Köse, U., Güraksın, E., Deperlioğlu, Ö. 2015. Girdap Optimizasyon Algoritması Tabanlı Destek Vektör Makineleri ile Diyabet Tespiti. Tıp Teknolojileri Ulusal Kongresi(TIPTEKNO), 15-18 Ekim, Muğla, 471-474.
  • Lee, S., Kang, S., Han, D. 2006. Agent-Based Flexible Video conference System with Automatic QoS Parameter Tuning. Trends in Artificial Intelligence, 9th Pacific Rim International Conference on Artificial Intelligence (PRICAI), 7-11 August, Guilin, 51-60.
  • Maniezzo, V., Colorni, A., Dorigo, M. 1994. The ant system applied to the quadratic assignment problem, IEEE Transactions on Knowledge and Data Engineering, 11(5), 769-778.
  • Manuel, F., Franziska, K., Frank, P. 2004. Techniques for Analysis and Calibration of Multi-Agent Simulations. ss. 305-321, Gleizes, M.P., Omicini, A., Zambonelli, F. ed. 2004. Engineering Societies in the Agent World(ESAW), Springer Berlin Heidelberg, Berlin.
  • Manuel, F., Franziska, K., Frank, P. 2006. Approaches for Resolving the Dilemma between Model Structure Refinement and Parameter Calibration in Agent Based Simulations. In 5th International Joint Conference on Autonomous Agents and Multi-agent Systems, 8-12 May, Hakodate, 120-122.
  • Öksüm, E., Dolmaz, M.N. 2006. Prizma Modelleri Kullanılarak Sentetik Mağnetik Anomalilerin Gauss-Newton Yöntemi ile Ters Çözümlenmesi. Süleyman Demirel Üniversitesi-Fen Bilimleri Enstitüsü Dergisi, 10(3), 437-446.
  • Pereira, A., Duarte, P., Reis, L.P. 2008. Agent-based Ecological Model Calibration - on the Edge of a New Approach. Computing Research Repository, abs/0809.1686, 107-113
  • Sallans, B., Pfister, A., Karatzoglou, A., Dorffner, G. 2003. Simulation and validation of an integrated markets model, J. Artificial Societies and Social Simulation, 6(4), 693-706
  • Salwala, C., Kotrajara, V., Horkaew, P. 2010. Improving Performance for Emergent Environments Parameter Tuning and Simulation in Games Using GPU. 2010 3rd International Conference on Computer Scienceand Information Technology (ICCSIT), 9-11 July, Chengdu, 37-41.
  • Saraçoğlu, H., Demirören, A. 2007. Parametreleri Genetik Algoritma ile Ayarlanan Bulanık Kontrolör Yardımıyla Otomatik Gerilim Kontrolü. Elektrik Elektronik-Bilgisayar Mühendisliği 12. Ulusal Kongresi, 14-18 Kasım, Eskişehir.
  • Saraçoğlu, B., Güvenç, U., Dursun, M., Poyraz, G, Duman, S. 2013. Biyocoğrafya Tabanlı Optimizasyon Metodu Kullanarak Asenkron Motor Parametre Tahmini. İleri Teknoloji Bilimleri Dergisi, 2(1), 46-54
  • Stützle, T., Hoos, H. 1997. The MAX-MIN Ant System and Local Search for the Traveling Salesman Problem. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC'97), 13-16 April, USA, 313-329.
  • Stützle, T., Hoos, H. 1997. Improvements on the Ant System: Introducing the MAX-MIN Ant System. ss. 245-249. Smith, George D., Steele, Nigel C., Albrecht, Rudolf F. ed. 1997. Artificial Neural Networks and Genetic Algorithms, Springer Vienna, Norwich.
  • Şahin, Y., Eroğlu, A. 2014. Kapasite Kısıtlı Araç Rotalama Problemi İçin Metasezgisel Yöntemler: Bilimsel Yazın Taraması, Süleyman Demirel Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 19(4), 337-355.
  • Valenzano, R.A., Sturtevant, N.R., Schaeffer, J., Buro, K., Kishimoto, A. 2010. Simultaneously Searching with Multiple Settings: An Alternative to Parameter Tuning for Suboptimal Single-Agent Search Algorithms. Proceedings of the 20th International Conference on Automated Planning and Scheduling-ICAPS, 12-16 May, Toronto, 177-184.
  • White, T., Pagurek, B., Oppacher, F. 1998. ASGA: Improving the Ant Systemby Integration with Genetic Algorithms. Proceedings of the Third Genetic Programming Conference, 22-25 July, Wiskonsin, 610-617.
  • Yanıkoğlu, H., Özkara, E., Yüceer, M. 2010. Kinetik Model Parametrelerinin Belirlenmesinde Kullanılan Optimizasyon Tekniklerinin Kıyaslanması. 9. Ulusal Kimya Mühendisliği Kongresi(UKMK-9), 22-25 Haziran, Ankara.
  • Yüceer, M., Atasoy, İ., Berber, R. 2004. Kinetik Modellerde Optimum Parametre Belirleme İçin Bir Yazılım: PARES, 6. Ulusal Kimya Mühendisliği Kongresi- UKMK-6, 7-10 Eylül, İzmir.
  • Yüceer, M., Atasoy, I, Berber, R. 2005. An integration based optimization approach for parameter estimation in dynamic models. Computer Aided Chemical Engineering, Cilt. 20(1), 631-636.
  • Yüceer, M., Atasoy, I., Berber, R. 2008. A software for parameter estimation in dynamic models. Brazilian J. of Chem. Engineering, Cilt. 25(4), 813 – 821.
There are 35 citations in total.

Details

Subjects Engineering
Journal Section Derleme veya Çeviri Makale \ Review or Translated Articles
Authors

RABİA Korkmaz Tan 0000-0002-3777-2536

ŞEBNEM Bora 0000-0003-0111-4635

Publication Date December 25, 2017
Submission Date April 19, 2017
Acceptance Date December 1, 2017
Published in Issue Year 2017 Volume: 5 Issue: 3

Cite

APA Korkmaz Tan, R., & Bora, Ş. (2017). MODELLEME VE BENZETİM ORTAMINDA PARAMETRE OPTİMİZASYONU VE KULLANILAN TEKNİKLER. Mühendislik Bilimleri Ve Tasarım Dergisi, 5(3), 685-697. https://doi.org/10.21923/jesd.307125