values and ranking based on modified fuzzy VIKOR.Table 21.32 (A) Results of all tools for sustainable green development.Table 21.32 (B) Results of all tools for manufacturing competency.
18 Chapter 23Table 23.1 Circular structure of pufferfish.Table 23.2 Parameters about meta-heuristic optimization algorithm in the test pr...Table 23.3 Benchmark functions.Table 23.4 Benchmark test results.
19 Chapter 24Table 24.1 Multimodal and unimodal benchmark problems.Table 24.2 Multi-modal of fixed dimension benchmarks problems.Table 24.3 Multi-modal of fixed dimension benchmarks problems.Table 24.4 Parameters of the approaches.Table 24.5 SSO, GWO, and HGWOSSO numerical findings of multimodal and unimodal b...Table 24.6 SSO, GWO, and HGWOSSO statistical findings of multimodal and unimodal...Table 24.7 SSO, GWO, and HGWOSSO numerical findings of multimodal of fixed-dimen...Table 24.8 SSO, GWO, and HGWOSSO statistical findings of multimodal of fixed-dim...Table 24.9 SSO, GWO, and HGWOSSO numerical findings of multimodal of fixed-dimen...Table 24.10 SSO, GWO, and HGWOSSO statistical findings of multimodal of fixed-di...Table 24.11 Comparisons between GWO, SSO, and HGWOSSO.
20 Chapter 25Table 25.1 Swarm-based intelligent methods, its merits, and demerits.Table 25.2 Evolutionary algorithms, merits, and demerits.Table 25.3 Physics-based algorithms, merits, and demerits.Table 25.4 Merits and demerits of ecology-based algorithms.
21 Chapter 26Table 26.1 Reduced systems and the fitness values of the PMSM drive in the discr...Table 26.2 Some popular time-domain parameters of the reduced PMSM drive model i...Table 26.3 Some popular performance indices of the reduced PMSM drive system in ...Table 26.4 Controller gains and the fitness function values of the reduced-order...
22 Chapter 27Table 27.1 Datasheet of four marketable PV modules [20, 21].Table 27.2 Range of decision variables for TDM.Table 27.3 Optimal parameters of TDM using different algorithms for KC200GT.Table 27.4 Optimal parameters of TDM using different algorithms for CS6K-280M.Table 27.5 Optimal parameters of TDM using different algorithms for STM6 40-36.Table 27.6 Optimal parameters of TDM using different algorithms for Pro. SW255.Table 27.7 Statistical analysis of error function for TDM.Table 27.8 Wilcoxon rank sum test results for TDM for different PV models.Table 27.9 Corrected p-values for TDM for the Wilcoxon test adding Holm-Bonferro...
23 Chapter 29Table 29.1 ML algorithms for intelligent decision-making in smart irrigation con...Table 29.2 Review of power/energy saving for GIoT–based smart irrigation monitor...Table 29.3 Review of recent GIoT methods to save power/energy for smart agricult...Table 29.4 Review of different edge computing–based smart weather and irrigation...Table 29.5 Specifications of LPWAN techniques.
24 Chapter 30Table 30.1 An example of sentiment term matrix for datasets.Table 30.2 Characteristic of the considered training datasets.Table 30.3 Results with other methods using Sentiment140 Twitter dataset.
25 Chapter 31Table 31.1 Comparison of merits and drawbacks of the present approaches to real-...Table 31.2 Deployment details.Table 31.3 Complexity comparison of data transmission algorithms.
26 Chapter 33Table 33.1 Decision matrix.Table 33.2 Direct relation coefficient matrix.Table 33.3 Normalized matrix (X).Table 33.4 Identity matrix (I).Table 33.5 (I-X) matrix.Table 33.6 (I-X)−1 matrix.Table 33.7 Total relation matrix.Table 33.8 C and S calculation.Table 33.9 C and S matrix.Table 33.10 Ranking based on modified DEMATEL.Table 33.11 Decision matrix.Table 33.12 Weighted sum matrix.Table 33.13 Ranking based on WSM.Table 33.14 Decision matrix.Table 33.15 Weighted product matrix.Table 33.16 Ranking based on WPM.Table 33.17 Ranking based on WASPAS.Table 33.18 Decision matrix.Table 33.19 Normalized decision matrix.Table 33.20 Max and Min values from normalized matrix.Table 33.21 Normalized data.Table 33.22 Deviation sequence matrix.Table 33.23 Delta matrix.Table 33.24 Grey relation coefficient matrix.Table 33.25 Ranking based on GRA.Table 33.26 Decision matrix.Table 33.27 Normalized decision matrix.Table 33.28 Utility calculation.Table 33.29 Ranking based on SMART.Table 33.30 Decision matrix.Table 33.31 Best and worst values.Table 33.32 Normalized matrix.Table 33.33 Correlation matrix.Table 33.34 Criteria weight matrix.Table 33.35 Ranking based on CRITIC method.Table 33.36 Decision matrix.Table 33.37 Normalized matrix.Table 33.38 Entropy matrix.Table 33.39 Ranking based on entropy method.Table 33.40 Decision matrix.Table 33.41 PDA matrix.Table 33.42 NDA matrix.Table 33.43 SPj matrix.Table 33.44 SNj matrix.Table 33.45 Ranking based on EDAS method.Table 33.46 Decision matrix.Table 33.47 Defuzzified score based on sums of square and square root values.Table 33.48 Normalized and defuzzified rating of alternatives.Table 33.49 Ranking based on MOORA method.Table 33.50 Final reachability matrix of factors.Table 33.51 Iteration 1.Table 33.52 Iteration 2.Table 33.53 Iteration 3.Table 33.54 Iteration 4.Table 33.55 Iteration 5.Table 33.56 Iteration 6.Table 33.57 Iteration 7.Table 33.58 Iteration 8.Table 33.59 Iteration 9.Table 33.60 Iteration 10.
27 Chapter 34Table 34.1 Demographic and clinical characteristics of the patients with CAD.Table 34.2 Classical evaluation of gender differences in association of lipid pr...Table 34.3 Bayesian evaluation of gender differences in association of lipid pro...
28 Chapter 35Table 35.1 Quantitative measures of MSE, SSIM, and PSNR of dynamic MRI for diffe...
29 Chapter 36Table 36.1 Average classification accuracy based on Affine hull and wavelet fusi...
30 Chapter 37Table 37.1 Comparative analysis of polyp detection techniques.Table 37.2 Accuracy report of implemented models.Table 37.3 Classification report for new test dataset.
31 Chapter 38Table 38.1 Results of the proposed method at nucleotide (mRNA) level.Table 38.2 Results of the proposed method at exon (mRNA) level.Table 38.3 Results of the proposed method at the nucleotide (coding) level on da...Table 38.4 Results of the proposed method at exon (coding) level on dataset 1.Table 38.5 Results of the proposed method at the nucleotide (coding) level on da...Table 38.6 Results of the proposed method at exon (coding) level on dataset 2.
32 Chapter 39Table 39.1 Ten typical samples.Table 39.2 Estimated result with PLSR and BP-ANN models.
33 Chapter 40Table 40.1 District-wise COVID-19 cases in Gujarat.
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