nature inspired algorithms

It is important to calculate the optimum design parameters of synchronous generator (SG) to obtain the desired total harmonic distortion (THD). In this study, we aim to determine the optimum rotor design parameters of SG by using grey wolf optimizer (GWO) algorithm. For this purpose regression modelling is performed to mathematically modelling the relationship between the selected rotor design parameters (factors namely slot pitch, center slot pitch, and damper width) and THD (response). This factor combination is not previously investigated in the related literature. Then by using GWO the optimization is performed on this regression equation. Maxwell simulations have been used for numerical experiments. The results of GWO are compared with the results of genetic algorithm (GA). The results indicate that the GWO algorithm can be well adapted to similar optimization processes and can be effectively used. As a result, the voltage THD of the SG is reduced to 0.3951 under the acceptable magnetic flux conditions. This GWO aided optimization study is significant in that it demonstrates how the performance of SG can be improved by making minor changes to the production line that has been adjusted for mass production without changing the outer diameter and dimensions of SG.

VANETs are a subset of MANETs in which vehicles are considered as network nodes. These networks have been created to communicate between vehicle and traffic control on the roads. VANETs have similar features to MANETs, and their main special property is the high-speed node mobility which makes a quick-change topology in the network. The rapid change of network topology is a major challenge in routing. One of the well-known routing protocols in VANETs is the AODV routing protocol. In this inquiry, nature-inspired algorithms such as GOA and GA are used to improve routing in VANETs to search the optimal configuration of the AODV routing protocol, and its impact on network evaluation criteria has been investigated. The rating measures applied in this research are the packet delivery ratio, end-to-end delays, and normalized routing load.