Hybrid Systems
Gypsy Nandi · 2023
This chapter focuses on hybrid systems, and its importance and applications in soft computing. Hybrid systems in soft computing offer a flexible and powerful approach to problem solving, allowing for robust and efficient solutions in complex domains where traditional methods may fall short. Some commonly used soft computing techniques that can be integrated into hybrid systems include fuzzy logic, artificial neural network, evolutionary computation, and swarm intelligence. Neurogenetic systems, also known as neurogenetic hybrid systems, combine the principles and techniques of neural networks and genetic algorithms (GAs). Fuzzy-Neural systems, also known as Neuro-Fuzzy systems, are hybrid intelligent systems that combine fuzzy logic and artificial neural networks. Fuzzy-Genetic Systems, also known as Genetic-Fuzzy systems or Fuzzy-Genetic algorithms, are hybrid intelligent systems that combine the principles of fuzzy logic and GAs.