BIO-INSPIRED COMMUNICATION: A Review on Solution of Complex Problems for Highly Configurable Systems
Atif Ali, Yasir Hafeez, Syed Muzammil Hussainn, Muhammad Usama Nazir · 2020 3rd International Conference on Computing, Mathematics and Engineering Technologies (iCoMET) · 2020
Data science-based problems are becoming a challenge due to explosive amount of data, if not dreadful. To solve versatile complex problems for Highly configurable systems intelligent algorithms are in consideration. However, the awareness of the crossed strategy in researchers is gradually decreasing due to rapid growth of the field, so that the literature of bio inspired communication is only inclined to a few problem-solving algorithms (such as neural networks, ant colonies optimization, genetic algorithms, and particle swarms). In this paper we specifically elaborate the working of neural networks such as genetic algorithms like Ant Colony Optimization (ACO), Artificial bee colony (ABC), Fire Flies, Bacterial Search, Particle Swarm Optimization (PSO), Rhododendron Search, and other genetic algorithms like BAT, and Frog. This revision will pave the way for future research to select an algorithm based on adjustment. Communication in swarms has 3 driven rules. The attributes of the groups of swarms are emergent and stigmatic. Different insects, such as ants, wasps, termites, perform local work for a global purpose with ample resilience as they are not centrally shielded. Finally, the authors discuss biologically inspired communication usage in applications.