Aims and scope

Intelligence Modeling in Electromechanical Systems is a prestigious international peer-reviewed journal dedicated to fostering excellence and innovation in the realms of intelligence modeling and its integration into electromechanical systems. The journal's primary aim is to publish high-quality scientific papers that make significant contributions to the understanding, advancement, and real-world application of intelligence-driven solutions within the context of electromechanical systems.

Scope:

The scope of "Intelligence Modeling in Electromechanical Systems" spans a diverse spectrum of both conventional and cutting-edge domains, including but not limited to:

  1. Intelligence Modeling: Unveiling the theoretical underpinnings and practical applications of intelligence modeling, encompassing machine learning algorithms, neural networks, deep learning, expert systems, and adaptive learning.

  2. Artificial Intelligence in Engineering: Investigating the symbiosis between artificial intelligence and engineering, uncovering innovative applications in product design, manufacturing processes, and decision support systems.

  3. Control Strategies: Advancing control methodologies that leverage intelligence modeling to regulate, optimize, and adapt the behavior of electromechanical systems. This includes research in adaptive control, real-time decision-making, and dynamic system response.

  4. Electromechanical Systems: Exploring the intricate interplay between electrical and mechanical components within complex systems, including robotics, automation, sensors, actuators, control systems, and the integration of intelligence for enhanced performance.

  5. Human-Machine Collaboration: Exploring the integration of intelligence modeling to facilitate seamless collaboration between humans and machines, leading to improved user experiences and task outcomes.

  6. Emerging Technologies: Highlighting breakthroughs and pioneering research in areas such as quantum-inspired intelligence, swarm robotics, and the fusion of intelligence modeling with emerging electromechanical technologies.

  7. Interdisciplinary Synergy: Emphasizing the value of interdisciplinary collaboration in addressing complex real-world challenges at the intersection of intelligence modeling and electromechanical systems.

  8. Robotics: Research on the design, modeling, and control of robots that include both electrical and mechanical components.

  9. Automation and Mechatronics: Interdisciplinary research that combines mechanical design with electronic control for automated systems.

  10. Control Systems: Articles on algorithms and systems that control the behavior and performance of electromechanical components.

  11. Actuation Systems: Research on the design, modeling, and control of actuators that convert electrical signals into mechanical actions.

  12. Sensors and Instrumentation: Studies focusing on the development and application of sensors for various physical measurements in electromechanical systems.

  13. Power Electronics: Papers on the management and distribution of electrical power in mechanical systems.

  14. Energy Systems: Studies on the efficient use and management of energy in electromechanical systems, including renewable energy sources.

  15. System Integration: Research on the integration of electrical and mechanical subsystems into a unified, functional system.

  16. Intelligent Algorithms: Papers that incorporate machine learning, artificial intelligence, and data analytics into electromechanical systems for enhanced performance and adaptability.

IMES serves as a pivotal platform for disseminating influential research that unifies diverse domains, catalyzing cross-disciplinary collaboration and driving transformative innovation. By advancing the realms of intelligence modeling, computational intelligence, and state-of-the-art algorithms, the journal aims to foster the growth of knowledge and the effective application of intelligence-driven solutions across a multitude of fields.