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Fig 1.

Initial population generated by 3 kinds of maps in 1000 iterations.

(a) Rand, (b) Tent map, (c) Chebyshev map, (d) Gauss map.

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Fig 1 Expand

Fig 2.

Probability generation of whale social behavior.

(a) Early iteration, b) Mid-iteration, c) Late iteration.

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Fig 2 Expand

Fig 3.

Original parameter a-value, -value and -value under 1000 iterations.

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Fig 4.

Modified parameter a-value, -value and -value under 1000 iterations.

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Fig 5.

Majority voting criteria.

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Table 1.

Benchmark functions used and their details.

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Table 1 Expand

Table 2.

Datasets used and their details.

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Table 3.

Parameter settings of IWOA and other selected algorithms.

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Table 3 Expand

Fig 6.

Logarithmic mean convergence curves of different algorithms.

(a)F1(Sphere function), b)F3(Schwefel 1.2 function), (c)F5(Rastrigin function), d)F7(Weierstrass function), (e)F1(30D), (f)F3(30D), (g)F5(30D), (h)F7(30D). (i)F1(100D), (j)F3(100D), (k)F5(100D), (l)F7(100D).

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Fig 6 Expand

Table 4.

The comparison of obtained solutions for 8 benchmark functions.

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Table 4 Expand

Fig 7.

Average running time of different algorithms.

(a) 30D Average running time(s), (b) 100D Average running time(s).

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Fig 7 Expand

Table 5.

p-value of the Wilcoxon test for the optimization results of IWOA and other algorithms based 8 benchmark functions (p> = 0.5 are in bold).

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Table 6.

Friedman test results of benchmark functions with different dimensions.

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Table 7.

The comparison of classification accuracy of different strategies.

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Table 8.

The comparison of classification accuracy of different classifiers.

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Table 9.

Parameter settings of IWOAIKFS and other selected algorithms.

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Table 9 Expand

Table 10.

Comparison between IWOAIKFS with other competitor optimizers based on accuracy (k = 5 and best are in bold).

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Fig 8.

Total mean accuracy of IWOAIKFS compared to other algorithms under all datasets.

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Fig 9.

The accuracy of IWOAIKFS compared to other optimizers.

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Fig 10.

The selection ratio of IWOAIKFS compared to other optimizers.

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Fig 11.

Convergence curve of IWOAIKFS versus other algorithms over all datasets (k = 5).

(a) Birds, (b) Blood, (c) Breast_cancer, (d) Bupa, (e) Car, (f) Chart, (g) Digits, (h) Glass, (i) Heart_disease, (j) Indian, (k) Ionosphere, (l) Iris, (m) Planning, (n) Wine, (o) Zoo.

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Fig 11 Expand

Table 11.

p-value of the Wilcoxon test for the classification accuracy results of IWOAIKFS and other optimizers (k = 5 and p > = 0.5 are in bold).

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Table 11 Expand

Table 12.

Friedman test results for datasets.

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Fig 12.

Boxplot of IWOAIKFS versus other algorithms over all datasets (k = 5).

(a) Birds, (b) Blood, (c) Breast_cancer, (d) Bupa, (e) Car, (f) Chart, (g) Digits, (h) Glass, (i) Heart_disease, (j) Indian, (k) Ionosphere, (l) Iris, (m) Planning, (n) Wine, (o) Zoo.

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Fig 12 Expand