Обзор современных подходов искусственного интеллекта для систем управления сложными объектами

Автор: Самигулина Галина Ахметовна, Самигулин Тимур Ильдусович

Журнал: Проблемы информатики @problem-info

Рубрика: Теоретическая и системная информатика

Статья в выпуске: 3 (40), 2018 года.

Бесплатный доступ

В статье проведен аналитический обзор интеллектуальных систем управления сложными объектами, построенных на основе генетических алгоритмов, оптимизации роя частиц и алгоритмов оптимизации муравьиных колоний за период с 2015 по 2018 год. Показаны важность применения биоинсперированных подходов искусственного интеллекта и перспективы их развития. Приведены основные достоинства и недостатки применения различных интеллектуальных алгоритмов при построении интеллектуальных систем управления сложными объектами. Показана актуальность разработок интеллектуальных систем при создании инновационных интеллектуальных технологий для различных практических приложений в промышленности, нефтегазовой отрасли, транспорте и других областях.

Еще

Аналитический обзор, сложный объект, интеллектуальные системы управления, генетические алгоритмы, оптимизация роя частиц, оптимизация муравьиных колоний

Короткий адрес: https://sciup.org/143167054

IDR: 143167054

Список литературы Обзор современных подходов искусственного интеллекта для систем управления сложными объектами

  • Xin-HuaQiu, ZhenWang, QingXue. Investment in deepwater oil and gas exploration projects: a multi-factor analysis with a real options model//Petroleum Science. Springer, 2015. V. 12, Issue 3. P. 525-533.
  • Samigulina G. A. Immune network modeling technology for complex objects intellectual control and forecasting system: Monograph. Yelm, WA, USA: Science Book Publishing House, 2015.
  • Захаров В. H. Интеллектуальные системы управления: основные понятия и определения//Известия РАН. ТиСУ. 1997. Т. 3. С. 138-145.
  • Guivang Wang, Shuo Xiao, Xi Chen, Xin Li. Application of genetic algorithm in automatic train operation//Wireless Personal Communications. Springer, 2018. V. 99. P. 140.
  • Longda Wang, Xingcheng Wang, Dawei Sun, Hua Hao. Multi-objective Optimization Improved GA Algorithm and Fuzzy PID Control of ATO System for Train Operation//Proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2017. Springer, 2017. P. 13-22.
  • Dimitrios Efthvmiou, Katerina Chrvsostomou, Maria Mofroulaki, Georgia Aifantopolou. Electric vehicles charging infrastructure location: a genetic algorithm approach//European Transport Research Review. Springer, 2017. V. 9, Issue 2. P. 27.
  • Menad Nait Amar, Nourddine Zeraibi, Kheireddine Redouane. Optimization of WAG Process Using Dynamic Proxy, Genetic Algorithm and Ant Colony Optimization//Arabian Journal for Science and Engineering. Springer Berlin Heidelberg. 2018. V. 43. P. 1-14.
  • Karina Arvanti Permatasari, Totok R. Bianto, Sony Andrivanto, Sonny Irawan, Ridho Bavaji. Optimization of Water Recycle at Steam Flood EOR Using Genetic Algorithm//ICIPEG 2016. Springer, Singapore, 2017.
  • Fatemeh Minian, Hamed Sabouhi, Jafar Hushmand, Ahmad Hallaj, Hiwa Khaledi, Mojtaba Mohammadpour. Gas turbine preventive maintenance optimization using genetic algorithm//International Journal of System Assurance Engineering and Management. Springer India. V. 8. P. 594-601.
  • Thinh Cong Tran, Pavel Brandstetter, Vo Hoang Duv, Hau Huu Vo, Chau Dong. PID Speed Controller Optimization Using Online Genetic Algorithm for Induction Motor Drive//Proceedings of International Conference on Advanced Engineering Theory and Applications. AETA 2016: Recent Advances in Electrical Engineering and Related Sciences. Springer, Cham. 2017. P. 564-576.
  • Kumaran Rajarathinam, James Barry Gomm, Ding-Li Yu, Ahmed Saad Abdelhadi. PID controller tuning for a multivariable glass furnace process by genetic algorithm//International Journal of Automation and Computing. Springer 2016. V. 13, Issue 1. P. 64-72.
  • Ahmed Alkamachi, Ergun Eryelebi. Modelling and Genetic Algorithm Based-PID Control of H-Shaped Racing Quadcopter//Arabian Journal for Science and Engineering. Springer, 2017. V. 42, Issue 7. P. 2777-2786.
  • Jamali A., Khaleghi E., Gholaminezhad I., Nariman-Zadeh N., Gholaminia B., Jamal-Omidi A. Multi-objective genetic programming approach for robust modeling of complex manufacturing processes having probabilistic uncertainty in experimental data//Journal of Intelligent Manufacturing. Springer US, 2017. V. 28, Issue 1. P. 149-163.
  • Son Thai, Nam-II Kim, Jaehong Lee, Joo-Won Kang. Optimum design of cable nets by using genetic algorithm//International Journal of Steel Structures. Springer, 2017. V. 17, Issue 3. P. 1183-1198.
  • Jing Wang, Naichao Song, Envu Jiang, Da Xu, Weihua Deng, Ling Mao. The Application of the Particle Swarm Algorithm to Optimize PID Controller in the Automatic Voltage Regulation System//Proceedings of International Conference on Intelligent Computing for Sustainable Energy and Enviroment. LSMS 2017, ICSEE 2017: Advanced Computational Methods in Energy, Power, Electric Vehicles and Their Integration. Springer Singapore, 2017. P. 529-536.
  • Xialong Xu, Hanzhong Rong, Marcello Trovati, Mark Liprott, Nik Bessis. CS-PSO: chaostic particle swarm optimization algorithm for solving combinatorial optimization problems//Soft Computing. Springer, 2018. V. 22, Issue 3. P. 783-795.
  • Shu-Zhi Gao, Xiao-Feng Wu, Liang-Liang Luan, Jie-Sheng Wang, Gui-Cheng Wang. PSO optimal control of model-free adaptive control for PVC polymerization process//International Journal of Automation and Computing. Springer, 2017. Vol. 14, Issue 3. P. 140.
  • Fateh Berrouk, Kamel Bounava. Optimal Power Flow For Multi-FACTS Power System Using Hybrid PSO-PS Algorithms//Journal of Control, Automation and Electrical Systems. Springer, 2018. V. 29, Issue 2. P. 177-191.
  • Md Azharuddin, Prasanta K. Jana. PSO -based approach for energy-efficient and energy-balanced routing and clustering in wireless sensor networks//Soft Computing. Springer, 2017. V. 21, Issue 22. P. 6825-6839.
  • Vasu Ganji, Sivakumar Mangipudi, Ramalingaraju Manvala. A novel model order reduction technique for linear continuous-time systems using PSO-DV algorithm//Journal of Control, Automation and Electrical Systems. Springer, 2017. V. 28, Issue 1. P. 68-77.
  • Alejandro Rodriguez-Molina, Miguel Gabriel Villarreal-Cervantes, Mario Aldape-Perez. An adaptive control study for the DC motor using metaheuristic algorithms//Soft Computing. Springer, 2017. P. 1-18.
  • Guo-Han Lin, Jing Zhang, Zhao-Hua Liu. Hybrid particle swarm optimization with differential evolution for numerical and engineering optimization//International Journal of Automation and Computing. Springer, 2018. V. 15, Issue 1. P. 103-114.
  • Haiping Ma, Sengang Ye, Dan Simon, Minrui Fei. Conceptual and numerical comparisons of swarm intelligence optimization algorithms//Soft Computing. Springer, 2017. V. 21, Issue 11. P. 3081-3100.
  • Livi Zhang, Chao Xiao, Teng Fei. Improved ant colony optimization algorithm based on RNA computing//Automatic Control and Computer Sciences. Springer, 2017. V. 51. P. 366-375.
  • Yi Zhou, Fazhi He, Yimin Qiu. Dynamic strategy based parallel ant colony optimization on GPUs for TSPs//Science China Information Sciences. Springer, 2017. V. 60. P. 68-102.
  • Chinjiang Liu. Optimal design of high-rise building wiring based on ant colony optimization//Cluster Computing. Springer, 2018. P. 1-8.
  • Lei Yang, Kangshun Li, Wensheng Zhang, Zhenxu Ke. Ant colony classification mining algorithm based on pheromone attraction and exclusion//Soft Computing. Springer, 2017. V. 21, Issue 19. P. 5741-5753.
  • Zheng Enxing, Liu Ranran. Routing Technology in Wireless Sensor Network Based on Ant Colony Optimization Algorithm//Wireless Personal Communications. Springer, 2017. V. 95, Issue 3. P. 1911-1925.
  • Zhaojun Zhang, Funian Hu, Na Zhang. Ant colony algorithm for satellite control resource scheduling problem//Applied Intelligence. Springer, 2018. V. 48, Issue 2. P. 1-11.
  • Boubertakh H. Knowledge-based ant colony optimization method to design fuzzy proportional integral derivative controllers//Journal of Computer and Systems Sciences International. Springer, 2017. V. 56, Issue 4. P. 681-700.
  • Chih-Ta Yen, Ming-Feng Cheng. A study of fuzzy control with ant colony algorithm used in mobile robot for shortest path planning and obstacle avoidance/7 Microsystem Technologies. Springer, 2018. V. 24, Issue 1. P. 125-135.
  • Salman A. Khan, Anijad Mahmood. Fuzzy goal programming-based ant colony optimization algorithm for multi-objective topology design of distributed local area networks/7 Neural Computing and Applications. Springer, 2017. Vol. 28, Issue 8. P. 1-19.
  • Chiranjit Changdar, Rajat Kumar Pal, G. S. Mahapatra. A genetic ant colony optimization based algorithm for solid multiple travelling salesman problem in fuzzy rough environment/7 Soft Computing. Springer, 2017. V. 21, Issue 16. P. 4661-4675.
  • Seved Mohsen Mousavi, Ardcshir Bahrcinincjad, S. Nurmava Musa, Farazila Yusof. A modified particle swarm optimization for solving the integrated location and inventory control problems in a two-echelon supply chain network/7.Journal of Intelligent Manufacturing. Springer, 2017. V. 28, Issue 1. P. 191-206.
  • Sidahmed Bcnabdcrrahmanc. Combining boosting machine learning and swarm intelligence for real time object detection and tracking: towards new meta-heuristics boosting classifiers/7 International.Journal of Intelligent Robotics and Applications. Springer, 2017. V. 1, Issue 4. P. 410-428.
  • Xuewu Wang, Yingpan Shi, Yixin Yan, Xingsheng Gu. Intelligent welding robot optimization based on discrete elite PSO/7 Soft Computing. Springer, 2017. V. 21, Issue 20. P. 5869-5881.
  • Sankalap Arora, Satvir Singh. Butterfly optimization algorithm: a novel approach for global optimization/7 Soft Computing. Springer, 2017. V. 22, Issue 6. P. 1-20.
  • Redouane Boudjemaa, Diego Oliva. A multi-objective approach to weather radar network architecture/7 Soft Computing, 2018. V. 22, Issue 3. P. 1-18.
  • Ibrahim Ivucukkoc. Integrating ant colony and genetic algorithms in the balancing and scheduling of complex assembly lines/7 The International.Journal of Advanced Manufacturing Technology. Springer, 2016. V. 82. P. 265-285.
  • Santosh Kumar Vernia, Shekhar Yadav, Shvam Krishna Nagar. Optimization of Fractional Order PID Controller Using Grey Wolf Optimizer/7.Journal of Control, Automation and Electrical Systems. Springer, 2017. V. 28, Issue 3. P. 314-322.
  • Yu-guang Zhong, Bo Ai. A modified ant colony optimization algorithm for multi-objective assembly line balancing/7 Soft Computing. Springer, 2017. V. 21, Issue 22. P. 6881-6894.
Еще
Статья научная