ОПТИМИЗИРАНЕ НА БАЗА ОТ ПРАВИЛА С ГЕНЕТИЧНА РАЗМИТА СИСТЕМА
Ключови думи:
hybrid systems, genetic fuzzy system, artificial intelligence
Абстракт
This paper examines the concepts for designing and building a system that integrates the potential of fuzzy modeling with the capabilities of genetic algorithms in the process of finding optimal solutions. The rule-based genetic fuzzy system is a hybrid system that aims at optimizing the weight of the rules in the knowledge base of FSSAM. Some results from the optimization process are shown as an illustration of the system’s capabilities.
Литература
[1] HERRERA, F., M. LOZANO, HERRERA-VIEDMA, E., VERDEGAY, J.. Fuzzy tools to improve genetic algorithms. Proc. of the European Congress on Intelligent Techniques and Soft Computing, Aachen, Germany, 1994, pp. 1532-1539.
[2] ГЕОРГИЕВА П.. Генетични размити системи, Полиграф, 2016.
[3] ГЕОРГИЕВА П.. Изследване на модели на софт компютинг за управление в реално време, Академик Дринов, София, 2013.
[4] GEORGIEVA P. V.. FSSAM: A Fuzzy Rule-Based System for Financial Decision Making in Real Time. - Handbook of Fuzzy Sets Comparison - Theory, Algorithms and Applications, Science Gate Publishing, 2016, pp. 121-148.
[5] JANG, R.. Fuzzy inference systems. NJ: Prentice-Hall, 1997.
[6] GEORGIEVA, P. V.. Fuzzy Rule-based Systems for Decision-making. Engineering Sciences, BAS, Vol. LIII, 2016, No 1, pp. 5-16.
[7] ZAFARI, A.. Developing a fuzzy inference system by using genetic algorithm and expert knowledge. Netherlands: Enschede, 2014.
[8] Popchev, I., Georgieva, P.. A Fuzzy Approach for Solving Multicriteria Investment Problems. –In: Iskander M. (eds) Innovative Techniques in Instruction Technology, E-learning, E-assessment, and Education. Springer Science+Business Media B.V., 2008, pp. 427-431.
[9] MELIN, P., CASTILLO, O., RAMÍREZ, E.. "Analysis and Design of Intelligent Systems Using Soft Computing Techniques," Series: Advances in Soft Computing, Vol. 41, 2007.
[10] GEORGIEVA, P. V., POPCHEV, I., STOYANOV., ST.. A Multi-Step Procedure for Asset Allocation in Case of Limited Resources. – CIT BAS, Vol. 15, no. 3, 2015, pp. 41–51
[11] GEORGIEVA, P. V.. Genetic Fuzzy System for Financial Management. CIT, BAS, Sofia 2018.
[12] GEORGIEVA P. V.. Applying FSSAM for Currency Rates Forecasting. –In: Transactions on Machine Learning and Artificial Intelligence, Manchester, SSE UK, Vol. 4, 2016, no. 3, pp. 30-40.
[2] ГЕОРГИЕВА П.. Генетични размити системи, Полиграф, 2016.
[3] ГЕОРГИЕВА П.. Изследване на модели на софт компютинг за управление в реално време, Академик Дринов, София, 2013.
[4] GEORGIEVA P. V.. FSSAM: A Fuzzy Rule-Based System for Financial Decision Making in Real Time. - Handbook of Fuzzy Sets Comparison - Theory, Algorithms and Applications, Science Gate Publishing, 2016, pp. 121-148.
[5] JANG, R.. Fuzzy inference systems. NJ: Prentice-Hall, 1997.
[6] GEORGIEVA, P. V.. Fuzzy Rule-based Systems for Decision-making. Engineering Sciences, BAS, Vol. LIII, 2016, No 1, pp. 5-16.
[7] ZAFARI, A.. Developing a fuzzy inference system by using genetic algorithm and expert knowledge. Netherlands: Enschede, 2014.
[8] Popchev, I., Georgieva, P.. A Fuzzy Approach for Solving Multicriteria Investment Problems. –In: Iskander M. (eds) Innovative Techniques in Instruction Technology, E-learning, E-assessment, and Education. Springer Science+Business Media B.V., 2008, pp. 427-431.
[9] MELIN, P., CASTILLO, O., RAMÍREZ, E.. "Analysis and Design of Intelligent Systems Using Soft Computing Techniques," Series: Advances in Soft Computing, Vol. 41, 2007.
[10] GEORGIEVA, P. V., POPCHEV, I., STOYANOV., ST.. A Multi-Step Procedure for Asset Allocation in Case of Limited Resources. – CIT BAS, Vol. 15, no. 3, 2015, pp. 41–51
[11] GEORGIEVA, P. V.. Genetic Fuzzy System for Financial Management. CIT, BAS, Sofia 2018.
[12] GEORGIEVA P. V.. Applying FSSAM for Currency Rates Forecasting. –In: Transactions on Machine Learning and Artificial Intelligence, Manchester, SSE UK, Vol. 4, 2016, no. 3, pp. 30-40.
Публикуван
2018-07-21
Как да се цитира
Georgieva, P., & Popchev, I. (2018). ОПТИМИЗИРАНЕ НА БАЗА ОТ ПРАВИЛА С ГЕНЕТИЧНА РАЗМИТА СИСТЕМА. КОМПЮТЪРНИ НАУКИ И КОМУНИКАЦИИ, 7(1), 132-139. изтеглен на от https://csc.bfu.bg/index.php/CSC/article/view/220
Раздел
Конференция на БСУ „Синя икономика и синьо развитие“. ISBN 978-619-7126-57-0
Copyright (C) 2018 Penka Georgieva, Ivan Popchev
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
