China
Africa
Explore chapters and articles related to this topic
Malware Detection and Mitigation
Published in Nicholas Kolokotronis, Stavros Shiaeles, Cyber-Security Threats, Actors, and Dynamic Mitigation, 2021
Gueltoum Bendiab, Stavros Shiaeles, Nick Savage
Bio-inspired computing, short for biologically inspired computing (BIC), is an emerging approach, inspired by biological evolution, to develop new models that provide a solution for complex optimization problems in a timely manner [53]. It relies heavily on the fields of biology, computer science, and mathematics. In recent years, the explosion of data has created challenges difficult to approach with traditional and conventional optimization algorithms and led the scientific community to develop bio-inspired algorithms that can be applied as a solution, such as NNs, genetic algorithms (GAs), and swarm intelligence (SI), in which meta-heuristic optimization methods replicate biological organisms’ behavior to address optimization problems [54]. BIC algorithms have been recognized as important for solving highly complex problems to provide working solutions in time, especially with dynamic problem definitions, pattern recognition, fluctuations in constraints, incomplete information, and limited computation capacity. Computing models such as NN, GA, and SI are major constituent models of the bio-inspired approach.
Bio-Inspired Scheduling for Factory Automation in the TD-LTE System
Published in IETE Technical Review, 2022
Won Jae Ryu, Gandeva Bayu Satrya, Soo Young Shin
Recently, the domain of bio-inspired computing has gained prominence. With organizations and societies gearing toward the digital era, there has been an explosion of data [40]. In this context, intelligent metaheuristic algorithms can learn and provide a suitable working solution for complex problems. Within metaheuristics, bio-inspired computing algorithms are gaining prominence because they are intelligent and can learn and adapt to biological organisms [41]. In this study, bio-inspired computing is implemented to optimize resource allocation in industrial WSNs based on TD-LTE systems.