Nature-inspired heuristic paradigms for parameter estimation of control autoregressive moving average systems
作者： Ammara Mehmood , Aneela Zameer , Muhammad Asif Zahoor Raja , Rabia Bibi , Naveed Ishtiaq Chaudhary
DOI: 10.1007/S00521-018-3406-4
关键词: Error function 、 Heuristic (computer science) 、 Autoregressive–moving-average model 、 Swarm intelligence 、 Estimation theory 、 Algorithm 、 Computer science 、 Variance (accounting) 、 Fitness function 、 Particle swarm optimization
摘要: Aim of this research is to explore the strength evolutionary and swarm intelligence techniques for parameter identification control autoregressive moving average (CARMA) systems. The fitness function CARMA system problem formulated through error created in mean square sense, learning unknown parameters model carried out with an effective global search based on genetic algorithms particle optimization algorithm. Comparative study design methodology conducted from actual systems different values noise variance degree freedom model. correctness proposed scheme validated results various performance measures absolute error, weight deviation, account Theil’s inequality coefficient, their variants sufficiently large number independent runs.
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