Intelligent Techniques for Predictive Data Analytics

Dr. Neha Singh is an Assistant Professor in the Electronics & Communication Engineering Department at Manipal University Jaipur, India. Dr. Shilpi Birla is an Associate Professor in the Electronics & Communication Department at Manipal University Jaipur, India. Dr. Mohd Dilshad Ansari is an Associate Professor in the Computer Science & Engineering Department at SRM University Delhi-NCR, Sonepat, Haryana, India. Dr. Neeraj Kumar Shukla is an Associate Professor in the Electrical Engineering Department at King Khalid University, Saudi Arabia.

• About the Editors xiiiList of Contributors xvPreface xixAcknowledgments xxi1 Data Mining for Predictive Analytics 1Prakash Kuppuswamy, Mohd Dilshad Ansari, M. Mohan, and Sayed Q.Y. Al Khalidi1.1 Introduction 11.2 Background Study 31.3 Applications of Data Mining 41.4 Challenges of Data Analytics in Data Mining 71.5 Significance of Data Analytics Tools for Data Mining 71.6 Life Cycle of Data Analytics 81.7 Predictive Analytics Model 111.8 Data Analytics Tools 141.9 Benefits of Predictive Analytics Techniques 181.10 Applications of Predictive Analytics Model 181.11 Conclusion 202 Challenges in Building Predictive Models 25Rakesh Nayak, Ch. Rajaramesh, and Umashankar Ghugar2.1 Introduction 252.2 Literature Survey 302.3 Few Suggestions to Overcome the Above Challenges 422.4 Conclusion and Future Directions 443 AI-driven Digital Twin and Resource Optimization in Industry 4.0 Ecosystem 47Pankaj Bhambri, Sita Rani, and Alex Khang3.1 Introduction 473.2 Digital Twin Technology 503.3 Industry 4.0 Ecosystem 533.4 AI in Digital Twins 563.5 Resource Optimization 573.6 AI-driven Resource Allocation 593.7 Challenges and Consideration 623.8 Future Trends 623.9 Conclusion 634 Predictive Analytics in Healthcare 71N. Venkateswarulu, P. Pavan Kumar, and O. Obulesu4.1 Predictive Analytics 714.2 Predictive Analysis in Medical Imaging 734.3 Predictive Analytics in the Pharmaceutical Industry 754.4 Predictive Analytics in Clinical Research 784.5 AI for Disease Prediction 814.6 Medical Image Classification for Disease Prediction 835 A Review of Automated Sleep Stage Scoring Using Machine Learning Techniques Based on Physiological Signals 89Santosh Kumar Satapathy, Poojan Agrawal, Namra Shah, Ranjit Panigrahi, Bidita Khandelwal, Paolo Barsocchi, and Akash Kumar Bhoi5.1 Introduction 895.2 Review of Related Works 915.3 Methodology 985.4 Conclusion 1055.5 Future Work 1056 Predictive Analytics for Marketing and Sales of Products Using Smart Trolley with Automated Billing System in Shopping Malls Using LBPH and Faster R-CNN 111Balla Adi Narayana Raju, Deepika Ghai, Suman Lata Tripathi, Sunpreet Kaur Nanda, and Sardar M.N. Islam6.1 Introduction 1116.2 Major Contributions 1126.3 Related Work 1136.4 Proposed Methodology 1196.5 Experimental Results and Discussions 1266.6 Conclusion 1307 Enhancing Stock Market Predictions Through Predictive Analytics 135Ameya Patil, Shantanu Saha, and Rajeev Sengupta7.1 Introduction 1357.2 Factors Influencing Stock Prices 1377.3 Can Markets Be Predicted? 1387.4 Using Predictive Analytics for Stock Prediction 1407.5 Neural Networks 1417.6 Conclusion 1468 Predictive Analytics and Cybersecurity 151Mohammed Sayeeduddin Habeeb8.1 Introduction 1518.2 Cybersecurity and Predictive Analysis 1528.3 Machine Learning 1538.4 Proactive Cybersecurity and Real-Time Threat Detection 1568.5 Network Security Analytics 1598.6 Cyber Risk Analytics 1608.7 Impact of Predictive Analytics on the Cybersecurity Landscape 1628.8 Challenges in Applying Predictive Analytics to Cybersecurity 1628.9 Conclusion 1649 Precision Agriculture and Predictive Analytics: Enhancing Agricultural Efficiency and Yield 171Nafees Akhter Farooqui, Mohd. Haleem, Wasim Khan, and Mohammad Ishrat9.1 Introduction 1719.2 Background 1739.3 Precision Agriculture Technologies and Methods 1789.4 Smart Agriculture Cultivation Recommender System 1839.5 Conclusion 18410 A Simple Way to Comprehend the Difference and the Significance of Artificial Intelligence in Agriculture 189Karan Aggarwal, Ruchi Doshi, Maad M. Mijwil, Kamal Kant Hiran, Murat Gök, and Indu Bala10.1 Introduction 18910.2 Machine Learning 19110.3 Deep Learning 19210.4 Data Science 19310.5 AI in the Agriculture Industry 19410.6 Conclusions 19811 An Overview of Predictive Maintenance and Load Forecasting 203Nand Kishor Gupta, Vivek Upadhyaya, and Vijay Gali11.1 Introduction 20311.2 PdM: Revolutionizing Asset Management 20411.3 Load Forecasting: Illuminating the Path Ahead 21611.4 Synergies and Future Prospects 22211.5 Conclusion 22512 Predictive Analytics: A Tool for Strategic Decision of Employee Turnover 231SMD Azash, Potala Venkata Subbaiah, and Lucia Vilcekova12.1 Introduction 23112.2 Literature Review 23212.3 Need and Importance of the Study 23312.4 Objectives of the Study 23512.5 Hypothesis of the Study 23512.6 Research Method 23512.7 Data Analysis Procedures and Discussion 23612.8 Recommendations 24012.9 Conclusion 241References 242Index 245