A new metaheuristic approach based on orbit in the multi-objective optimization of wireless sensor networks

Wireless Networks - Wireless sensor networks (WSNs) is a research area which has been used in various applications and has continuously developed up to now. WSNs are used in many applications,...     

COVID-19 diagnosis on CT images with Bayes optimization-based deep neural networks and machine learning algorithms

Neural Computing and Applications - Early diagnosis of COVID-19, the new coronavirus disease, is considered important for the treatment and control of this disease. The diagnosis of COVID-19 is...     

Cricket behaviour-based evolutionary computation technique in solving engineering optimization problems

Meta-heuristicalgorithms are widely used in various areas such as engineering, statistics, industrial, image processing, artificial intelligence etc. In this study, the Cricket algorithm which is a novel nature-inspired meta-heuristic algorithm approach which can be used for the solution of some global engineering optimization problems was introduced. This novel approach is a meta-heuristic method that arose from the inspiration of the behaviour of crickets in the nature. It has a structure for the use in the solution of various problems. In the development stage of the algorithm, the good aspects of the Bat, Particle Swarm Optimization and Firefly were experimented for being applied to this algorithm. In addition to this, because of the fact that these insects intercommunicate through sound, the physical principles of sound propagation in the nature were practiced in the algorithm. Thanks to this, the compliance of the algorithm to real life tried to be provided. This new developed approach was applied on the familiar global engineering problems and the obtained results were compared with the results of the algorithm applied to these problems.