Manta ray foraging optimization (MRFO) tends to get trapped in local optima as it relies on the direction provided by the previous individual and the best individual as guidance to search for the optimal solution. As enriching population diversity can effectively solve this problem, in this paper...
Gill plate extraction methods vary between species, by the size of the ray, and locally preferred practices (Fig.5). In most locations, the head is usually removed from the rest of the carcass once the ray has been landed (Fig.5a), although gill plate removal from the head does also oc...
However, instead of using different still images as a scale photograph, we use the same photograph with a floating PVC pipe as a reference scale to measure the manta ray body size. This approach provides more robust measurements, particularly when using low-cost drones with high uncertainty in ...
Figure 5. Average analysis of MRFOTL-GCDC system in 80% of the TR database. Figure 6 portrays the detailed GC classifier outcomes of the MRFOTL-GCDC method using 20% of the TS database. The results that were produced by the MRFOTL-GCDC approach has properly distinguished the images ...
The manta ray foraging optimization algorithm (MRFO) is one of the promised meta-heuristic optimization algorithms. However, it can stick to a local minimum, consuming iterations without reaching the optimum solution. So, this paper proposes a hybridizat
The manta-ray foraging optimization (MRFO) technique is proposed to be combined with a pseudo-parameter-based genetic algorithm (GA) to overcome and improve the poor performance of standard MRFO. The GA’s objective function depends only on three variables, whatever the number of independent vari...
dual active bridge converter; fractional order controller; metaheuristic algorithms; chaotic manta-ray foraging optimization; artificial ecosystem-based optimization; power electronics 1. Introduction 1.1. Overview Climate change is a fundamental threat to humanity and planetary health [1]. Moreover, power...
dual active bridge converter; fractional order controller; metaheuristic algorithms; chaotic manta-ray foraging optimization; artificial ecosystem-based optimization; power electronics 1. Introduction 1.1. Overview Climate change is a fundamental threat to humanity and planetary health [1]. Moreover, power...
The manta ray foraging optimizer (MRFO) is a novel nature-inspired optimization algorithm that simulates the foraging strategy and behavior of manta ray groups, i.e., chain, spiral, and somersault foraging. Although the native MRFO has revealed good competitive capability with popular meta-heurist...