2023
DOI: 10.1016/j.chaos.2023.114028
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Novel knacks of chaotic maps with Archimedes optimization paradigm for nonlinear ARX model identification with key term separation

Khizer Mehmood,
Naveed Ishtiaq Chaudhary,
Zeshan Aslam Khan
et al.
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Cited by 14 publications
(3 citation statements)
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“…The SITS system has two characteristic roots with positive real parts when h 0 K = , and the system is unstable. It can be concluded that the eigenvalues all have negative real parts by substituting εl C and εh C into the characteristic Equation (36), and this simultaneously satisfies the stability constraints of Equation (39), indicating that the SITS is asymptotically stable. Therefore, the proposed hybrid simulation system with SCVG is stable.…”
Section: Simulation Verification Of the Effect For Scvgmentioning
confidence: 90%
See 1 more Smart Citation
“…The SITS system has two characteristic roots with positive real parts when h 0 K = , and the system is unstable. It can be concluded that the eigenvalues all have negative real parts by substituting εl C and εh C into the characteristic Equation (36), and this simultaneously satisfies the stability constraints of Equation (39), indicating that the SITS is asymptotically stable. Therefore, the proposed hybrid simulation system with SCVG is stable.…”
Section: Simulation Verification Of the Effect For Scvgmentioning
confidence: 90%
“…To ensure the stability of SITS, the coefficients in the first column of the Routh array must be positive, as illustrated in Equation (39).…”
Section: Stability and Steady-state Error Analysismentioning
confidence: 99%
“…Hassan introduces a multi-objective variant of the marine predator's algorithm (MPA), incorporating concepts from Quantum theory to enhance the MPA's ability to balance between exploration and exploitation [35]. Mehmood combines Archimedes' optimization algorithm (AOA) with chaotic maps to optimize complex engineering problems [36]. Zhou introduces LASMA, a local dimensional mutation strategy, and an all-dimensional neighborhood search strategy for the slime mould algorithm (SMA) to improve the algorithm's exploration and exploitation abilities [37].…”
Section: Literature Reviewmentioning
confidence: 99%