13 Chapter 14Figure 14.1 Graphical model of model 1.Figure 14.2 Graphical model of model 2.Figure 14.3 Graphical model of ResNet50.Figure 14.4 Graph showing change of accuracy with respect to various parameters.Figure 14.5 Bar graph showing accuracy of different models.Figure 14.6 ROC curve for model 1.Figure 14.7 ROC curve for model 2.Figure 14.8 ROC curve for model 3 (ResNet50).Figure 14.9 MSE curve showing mean square error during training of model 1.Figure 14.10 MSE curve showing mean square error during training of model 2.Figure 14.11 MSE curve showing mean square error during training of model 3 (Res...
14 Chapter 15Figure 15.1 Path generation due to the attraction and repulsion force of goal an...Figure 15.2 Flowchart of firefly algorithm for robot path planning.Figure 15.3 Flowchart of firefly algorithm for robot path planning.Figure 15.4 Pseudocode of firefly algorithm for robot path planning.Figure 15.5 Architecture of dining philosopher controller for solving the confli...Figure 15.6 Architecture of proposed controller for robot path planning.Figure 15.7 Simulation result of robot path planning using FA based APF controll...Figure 15.8 Experimental result of robot path planning using FA-based APF contro...Figure 15.9 Comparison between proposed controller and existing controller based...
15 Chapter 16Figure 16.1 Flow diagram of the proposed system.Figure 16.2 K-Means algorithm on datasets.
16 Chapter 17Figure 17.1 Model of Wavelet Neural Network.Figure 17.2 Hybrid-PSO with WkNN algorithm.Figure 17.3 Algorithm of PHWkNN.Figure 17.4 Predicted with actual CPU workload for PHWkNN algorithm.Figure 17.5 Predicted with actual Memory workload for PHWkNN algorithm.Figure 17.6 Evaluation metrics values for Google CPU workload.Figure 17.7 Evaluation metrics values for Google memory workload.Figure 17.8 Performance Evaluation under CPU workload.Figure 17.9 Performance evaluation under memory workload.
17 Chapter 18Figure 18.1 Architecture of a bankruptcy prediction model.Figure 18.2 Comparison of accuracy and F1-score obtained from Adaboost and XGBoo...Figure 18.3 Comparison of accuracy and F1-score obtained from bagging based mode...Figure 18.4 Comparison of accuracy and F1-score obtained from single classifier ...Figure 18.5 RoC curve obtained by applying RF, DT, NN, MV.Figure 18.6 RoC curve obtained from boosting based ensemble models.Figure 18.7 RoC curve obtained from bagging based ensemble models.Figure 18.8 Roc curve obtained from XGBoosting model.
18 Chapter 19Figure 19.1 Crop yields, World 1961 to 2018. https://ourworldindata.org/grapher/...Figure 19.2 Relationship between AI, ML and deep learning.Figure 19.3 AI in agriculture market. Source:
1 Cover
2 Table of Contents
3 Title Page
4 Copyright
5 Dedication
6 Preface
7 Acknowledgments
8 Begin Reading
9 Index
10 Also of Interest
11 End User License Agreement
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