A Novel Binary Chaotic Cloud Flower Pollination Algorithm for Analog Fault Diagnosis

Applications of Flower Pollination Algorithm in Electrical Power Systems: A Review

“…It was found that the non-repetition of the chaotic sequences allowed for optimal solutions to be found in each case. Analog diagnostics makes use of a support vector machine (SVM) technique to identify fault samples [50], [51]. The SVM technique is vulnerable to the selection process problems described in [50], [51].…”

“…Analog diagnostics makes use of a support vector machine (SVM) technique to identify fault samples [50], [51]. The SVM technique is vulnerable to the selection process problems described in [50], [51]. Cui et al [50] implemented a Binary Modified Chaos-FPA (BCCFPA), which makes use of the chaos maps and cloud model to enhance the solution quality of the base FPA [50].…”

“…The SVM technique is vulnerable to the selection process problems described in [50], [51]. Cui et al [50] implemented a Binary Modified Chaos-FPA (BCCFPA), which makes use of the chaos maps and cloud model to enhance the solution quality of the base FPA [50]. The BCCFPA was tested against various binary modified metaheuristic algorithms to determine which could produce the optimal solutions to the selection challenges present with the SVM technique [50].…”

“…Cui et al [50] implemented a Binary Modified Chaos-FPA (BCCFPA), which makes use of the chaos maps and cloud model to enhance the solution quality of the base FPA [50]. The BCCFPA was tested against various binary modified metaheuristic algorithms to determine which could produce the optimal solutions to the selection challenges present with the SVM technique [50]. The results display that the BCCFPA possessed the strongest optimization capabilities amongst the tested algorithms and overcame the premature convergence of FPA [50].…”

“…The BCCFPA was tested against various binary modified metaheuristic algorithms to determine which could produce the optimal solutions to the selection challenges present with the SVM technique [50]. The results display that the BCCFPA possessed the strongest optimization capabilities amongst the tested algorithms and overcame the premature convergence of FPA [50]. Kaur et al [52] investigated the effectiveness of four variants of the CHAOS-FPA by conducting tests on nine benchmarks of high dimensional functions.…”