Computational Intelligence in Mechatronics
Solving Real-World Problems in Electronic Systems Design
- 1st Edition - September 15, 2026
- Latest edition
- Editor: Mohamed Arezki Mellal
- Language: English
Computational Intelligence in Mechatronics: Solving Real-World Problems in Electronic Systems Design provides a comprehensive exploration of the diverse applications of comput… Read more
Computational Intelligence in Mechatronics: Solving Real-World Problems in Electronic Systems Design provides a comprehensive exploration of the diverse applications of computational intelligence in the realm of applied electronics. By compiling cutting-edge research and practical case studies, the book bridges the gap between theory and practice, offering insights into how CI techniques can be effectively utilized to solve real-world problems in electronic systems design, analysis, and optimization. Through a combination of theoretical foundations, algorithmic implementations, and practical examples, readers will gain a deeper understanding of the potential benefits and limitations of CI in various applications within the field of applied electronics.
From optimizing circuit designs to enhancing signal processing algorithms, CI has demonstrated its efficacy in addressing challenges across diverse domains such as telecommunications, consumer electronics, renewable energy systems, and medical devices. As the demand for intelligent electronic systems continues to grow, understanding and harnessing the potential of computational intelligence becomes imperative for researchers, engineers, and practitioners in the field of applied electronics.
From optimizing circuit designs to enhancing signal processing algorithms, CI has demonstrated its efficacy in addressing challenges across diverse domains such as telecommunications, consumer electronics, renewable energy systems, and medical devices. As the demand for intelligent electronic systems continues to grow, understanding and harnessing the potential of computational intelligence becomes imperative for researchers, engineers, and practitioners in the field of applied electronics.
- Explains the potential of computational intelligence in the field of applied electronics
- Combines theoretical foundations, algorithmic implementations, and practical examples
- Inspires further research, innovation, and collaboration in leveraging computational intelligence to address evolving challenges and opportunities in applied electronics
Researchers and graduate students in computational intelligence and mechatronics
1, Design and Optimization of Electronic Components using Genetic Algorithms
2. Embedded Systems Design: Challenges and Innovations Using Computational Intelligence
3. Medical Device Development and Optimization Techniques : A Review
4. Optimization of Energy Consumption in Unmanned Aerial Vehicles (UAVs) using Particle Swarm Optimization
5. Signal Processing Techniques for Advanced Embedded Communication Systems
6. Fault Diagnosis in Electronic Systems Using Computational Intelligence: State-of-the-Art Approaches
7. Prognostics and Health Management in Electronic Devices by Deep Learning
8. Lifetime and Lifecycle Prediction of Electronic Components using Machine Learning
9. Obsolescence Replacement Strategies: A Systematic Approach based on Computational Intelligence
10. Genetic Algorithms in Circuit Design Optimization
11. Particle Swarm Optimization for Efficient Embedded System Design
12. Advanced Signal Processing Techniques using Artificial Neural Networks
13. Application of Ant Colony Optimization in UAV Routing and Control
14. Fuzzy Logic Applications in Medical Device Design and Optimization
15. Brain-Inspired Computing for Enhanced Embedded Systems
16. Hybrid Optimization Techniques for Fault Diagnosis in Electronic Circuits
17. Designing Efficient Medical Devices using Differential Evolution
18. Cuckoo Algorithm for Lifecycle Prediction of Electronic Components
19. Artificial Bee Colony Optimization for UAV Mission Planning
20. Integrating Fuzzy Logic with Artificial Neural Networks for Signal Processing Applications
2. Embedded Systems Design: Challenges and Innovations Using Computational Intelligence
3. Medical Device Development and Optimization Techniques : A Review
4. Optimization of Energy Consumption in Unmanned Aerial Vehicles (UAVs) using Particle Swarm Optimization
5. Signal Processing Techniques for Advanced Embedded Communication Systems
6. Fault Diagnosis in Electronic Systems Using Computational Intelligence: State-of-the-Art Approaches
7. Prognostics and Health Management in Electronic Devices by Deep Learning
8. Lifetime and Lifecycle Prediction of Electronic Components using Machine Learning
9. Obsolescence Replacement Strategies: A Systematic Approach based on Computational Intelligence
10. Genetic Algorithms in Circuit Design Optimization
11. Particle Swarm Optimization for Efficient Embedded System Design
12. Advanced Signal Processing Techniques using Artificial Neural Networks
13. Application of Ant Colony Optimization in UAV Routing and Control
14. Fuzzy Logic Applications in Medical Device Design and Optimization
15. Brain-Inspired Computing for Enhanced Embedded Systems
16. Hybrid Optimization Techniques for Fault Diagnosis in Electronic Circuits
17. Designing Efficient Medical Devices using Differential Evolution
18. Cuckoo Algorithm for Lifecycle Prediction of Electronic Components
19. Artificial Bee Colony Optimization for UAV Mission Planning
20. Integrating Fuzzy Logic with Artificial Neural Networks for Signal Processing Applications
- Edition: 1
- Latest edition
- Published: September 15, 2026
- Language: English
MM
Mohamed Arezki Mellal
Prof. Mellal is a Professor at the Department of Mechanical Engineering, Faculty of Technology, M’Hamed Bougara University, Boumerdes, Algeria. He was temporarily associated with Teaching and Research (ATER) at the Department of Industrial Engineering and Maintenance, University Institute of Technology Louis Pasteur, University of Strasbourg, France. He is affiliated to the LMSS Laboratory (Solid Mechanics and Systems Laboratory, M’Hamed Bougara University, Algeria) and was affiliated to the Control, Vision and Robotics team of the ICube Laboratory (The Engineering Science, Computer Science and Imaging Laboratory, University of Strasbourg, France).
Prof Mellal has contributed to papers on reliability and cost optimization of fuel cell systems, heat and power dispatch using flower pollination algorithms, and heterogeneous components in pharmaceutical production plants, among many others.
Affiliations and expertise
Université de Boumerdes, Boumerdes, Algeria