Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to
solve nonlinear optimization problems as well as the ability to be adapted to solve a variety …

A new population-based metaheuristic optimization algorithm named Simulated Kalman
Filter (SKF) is proposed as an adaptive beamforming algorithm for adaptive array antenna …

This paper introduces single-solution Simulated Kalman Filter (ssSKF), a new single-agent
optimisation algorithm inspired by Kalman Filter, for solving real-valued numerical …

ABSTRACT Simulated Kalman Filter (SKF) algorithm is a new population-based
metaheuristic optimization algorithm. In the original SKF algorithm, three parameter values …

Optimization problems arise in diverse fields such as engineering, economics, and industry.
Metaheuristic algorithms, including the Simulated Kalman Filter (SKF), have been …

Previously, an angle modulated simulated Kalman filter (AMSKF) algorithm has been
implemented for feature selection in peak classification of electroencephalogram (EEG) …

This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and
Particle Swarm Optimization (SKFPSO), for continuous numerical optimization problems …

This paper presents a performance evaluation of a new hybrid Simulated Kalman Filter and
Gravitational Algorithm (SKF-GSA), for continuous numerical optimization problems …

In this paper, a new population-based metaheuristic optimization algorithm named
Generalized Opposition-based Simulated Kalman Filter (GOBSKF) is proposed as adaptive …

Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the
Kalman filtering method. It had been successfully used for optimization of many engineering …