An improved black widow optimization algorithm for surfaces conversion

TL;DR: This study proposes a hybrid deep learning architecture, HDS, combining MSA-DCNN and LSTM, for automatic epileptic seizure detection using EEG signals, achieving improved performance and real-time detection capabilities compared to conventional methods.

TL;DR: In this article , the authors proposed an enhanced northern goshawk optimization algorithm to further improve the ability to solve challenging tasks by applying the polynomial interpolation strategy to the whole population, the quality of the solutions can be enhanced to keep a fast convergence to the better individual.

TL;DR: This study enhances the Black Widow Optimization algorithm by integrating alternative selection schemes, resulting in a novel variant, PIBWO, which outperforms existing algorithms in cloud task scheduling, achieving improved makespan reduction, energy consumption minimization, and cost efficiency.

TL;DR: An enhanced golden jackal optimization (GJO) algorithm is used to optimize the shape of complex composite shape-adjustable generalized cubic Ball (CSGC-Ball) surfaces to improve the convergence speed and calculation accuracy of the original GJO.

TL;DR: A framework is developed to explore the connection between effective optimization algorithms and the problems they are solving and a number of "no free lunch" (NFL) theorems are presented which establish that for any algorithm, any elevated performance over one class of problems is offset by performance over another class.

TL;DR: Optimization results prove that the WOA algorithm is very competitive compared to the state-of-art meta-heuristic algorithms as well as conventional methods.

TL;DR: A new optimization algorithm based on the law of gravity and mass interactions is introduced and the obtained results confirm the high performance of the proposed method in solving various nonlinear functions.

TL;DR: The statistical results and comparisons show that the HHO algorithm provides very promising and occasionally competitive results compared to well-established metaheuristic techniques.