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SI DMCM 2023 : SPECIAL ISSUE on Dynamic Modeling and Control methods for the Nonlinear system using Artificial Mathematical Intelligence | |||||||||||
Link: https://www.degruyter.com/journal/key/dema/html#overview | |||||||||||
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Call For Papers | |||||||||||
๐บ๐ท๐ฌ๐ช๐ฐ๐จ๐ณ ๐ฐ๐บ๐บ๐ผ๐ฌ ๐๐ ๐ซ๐๐๐๐๐๐ ๐ด๐๐ ๐๐๐๐๐ ๐๐๐ ๐ช๐๐๐๐๐๐ ๐๐๐๐๐๐ ๐ ๐๐๐ ๐๐๐ ๐ต๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐ ๐๐๐๐๐ ๐จ๐๐๐๐๐๐๐๐๐ ๐ด๐๐๐๐๐๐๐๐๐๐๐ ๐ฐ๐๐๐๐๐๐๐๐๐๐๐ This special issue in ๐ซ๐ฌ๐ด๐ถ๐ต๐บ๐ป๐น๐จ๐ป๐ฐ๐ถ ๐ด๐จ๐ป๐ฏ๐ฌ๐ด๐จ๐ป๐ฐ๐ช๐จ (๐ฐ๐ญ:2.093) focuses on Dynamic Modeling and Control methods for the Nonlinear system using Artificial Mathematical Intelligence. In the new era of technologies, the needs for efficient Control Systems are much needed, and it is considered as prime importance to industrial development. A fully automated system, which would help in accurate identification of abnormalities and providing good management among the network of operations. The requirement for machine learning and optimization has become more and more vital to modern systems. Different areas of mathematics were significantly impacted by the development of artificial intelligence. The field of inverse problems, namely imaging science, may have been the first to adopt these cutting-edge techniques. Using these methods, challenging issues like denoising, in painting, super resolution, or (limited-angle) computed tomography have been solved. Thus, a paradigm shift might be seen within a few years, and innovative solutions are often at least partially based on artificial intelligence techniques. It was not immediately clear how artificial intelligence approaches would benefit this field, the field of partial differential equations was significantly slower to adopt these new techniques. In fact, it appears unnecessary to use learning-type techniques because a partial differential equation is a sound mathematical model. However, there has recently been a paradigm shift in this field as well as a result of the discovery that deep neural networks may overcome the dimensionality paradox in high dimensional environments. During the previous decade, soft computing has emerged as potential candidates for solving complex and intricate global optimization problems, which are otherwise difficult to explain by traditional methods. In present scenario Industrial optimization, Control system applications, and power system application fields have challenging deeds, which are to be unraveled by the researchers. Some Artificial Mathematical Mechanics for Machine Learning and Global Optimization include Artificial Neural Networks, Fuzzy logic, Genetic Algorithms (GA), Differential Evolution (DE), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Firefly Algorithm (FFA) algorithm, etc., are the methods have been successfully applied to a wide range of benchmark and real-world application problems. This special issue is an ideal platform for the researchers to come out with innovative ideas and approaches in the area of Nonlinear Control Methods for emerging Artificial Mathematical techniques. This issue gains much importance since it directly affects many fields of society. Our issue seeks to bring forward and highlight the challenges in AI based mathematical Computing and Analytics on a control system, which would help for the smart enhancement in many applications used for human welfare. SCOPE OF THE SPECIAL ISSUE 1. Nonlinear computing based AMI system. 2. Artificial Intelligence based system modeling. 3. Mathematical Modeling of the Nonlinear system. 4. Mathematical Foundations for Arti๏ฌcial Intelligence 5. Fundamental solution for control system modeling. 6. Control Theory and the applications of optimization. 7. Optimization in Stochastic Systems (Continuous or Discrete times). 8. Optimization for the data analytics. 9. Advanced Closed-loop System with intelligent decision methodology. 10. Optimized Scheduling and Nonlinear Methods. 11. Optimization for the system modeling. 12. Optimized Technique for Control System. 13. Machine learning based PID Controller. 14. Non-Linear Processing. 15. Process Optimization. 16. Optimized Industrial Control. 17. Supervised and unsupervised controlling. 18. Effective process control by non-linear processing Mechanics. The topics mentioned above should be enhanced with any Artificial Intelligence methodologies, should be full mathematical oriented. Authors are requested to submit their full revised papers complying the general scope of the journal. The submitted papers will undergo the standard peer-review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process. ==== ๐๐๐๐๐ ๐๐ฟ๐๐๐๐๐ B. Nagaraj, Rathinam Group of Institutions, Coimbatore, India Danilo Pelusi, Communication Engineering, University of Teramo, Italy Raffaele Mascella, Communication Engineering University of Teramo, Italy ==== ๐ฟ๐๐ผ๐ฟ๐๐๐๐ The deadline for submissions is ๐๐๐๐ ๐๐, ๐ฎ๐ฌ๐ฎ๐ฏ, but individual papers will be reviewed and published online on an ongoing basis. ==== ๐๐๐ ๐๐ ๐๐๐ฝ๐๐๐ All submissions to the Special Issue must be made electronically via the online submission system Editorial Manager ๐ก๐ญ๐ญ๐ฉ://๐ฐ๐ฐ๐ฐ.๐๐๐ข๐ญ๐จ๐ซ๐ข๐๐ฅ๐ฆ๐๐ง๐๐ ๐๐ซ.๐๐จ๐ฆ/๐๐๐ฆ๐ Please, choose the category โ๐บ๐๐๐๐๐๐ ๐ฐ๐๐๐๐ ๐๐ ๐ซ๐๐๐๐๐๐ ๐ด๐๐ ๐๐๐๐๐ ๐๐๐ ๐ช๐๐๐๐๐๐ ๐๐๐๐๐๐ ๐ ๐๐๐ ๐๐๐ ๐ต๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐ ๐๐๐๐๐ ๐จ๐ด๐ฐโ ==== ๐พ๐๐๐๐ผ๐พ๐ ๐๐๐ฆ๐จ๐ง๐ฌ๐ญ๐ซ๐๐ญ๐ข๐จ.๐๐๐ข๐ญ๐จ๐ซ๐ข๐๐ฅ@๐๐๐ ๐ซ๐ฎ๐ฒ๐ญ๐๐ซ.๐๐จ๐ฆ ๐๐ฌ๐ฌ๐ข๐ฌ๐ญ๐๐ง๐ญ๐๐๐ง๐๐ ๐ข๐ง๐ ๐๐๐ข๐ญ๐จ๐ซ@๐๐๐ ๐ซ๐ฎ๐ฒ๐ญ๐๐ซ.๐๐จ๐ฆ ==== ๐๐ค๐ง ๐ข๐ค๐ง๐ ๐๐ฃ๐๐ค๐ง๐ข๐๐ฉ๐๐ค๐ฃ, ๐ฅ๐ก๐๐๐จ๐ ๐ซ๐๐จ๐๐ฉ ๐ค๐ช๐ง ๐ฌ๐๐๐จ๐๐ฉ๐. ๐ก๐ญ๐ญ๐ฉ๐ฌ://๐ฐ๐ฐ๐ฐ.๐๐๐ ๐ซ๐ฎ๐ฒ๐ญ๐๐ซ.๐๐จ๐ฆ/๐ฃ๐จ๐ฎ๐ซ๐ง๐๐ฅ/๐ค๐๐ฒ/๐๐๐ฆ๐/ |
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