The book discusses the designing of new AI algorithms used to convert general applications to AI-based applications. It highlights different Machine Learning and Deep Learning models for various applications used in healthcare and wellness, agriculture, and automobiles.
Artificial Intelligence and Knowledge Processing play a vital role in various automation industries and their functioning in converting traditional industries to AI-based factories. This book acts as a guide and blends the basics of Artificial Intelligence in various domains, which include Machine Learning, Deep Learning, Artificial Neural Networks, and Expert Systems, and extends their application in all sectors.
Artificial Intelligence and Knowledge Processing: Improved Decision-Making and Prediction, discusses the designing of new AI algorithms used to convert general applications to AI-based applications. It highlights different Machine Learning and Deep Learning models for various applications used in healthcare and wellness, agriculture, and automobiles. The book offers an overview of the rapidly growing and developing field of AI applications, along with Knowledge of Engineering, and Business Analytics. Real-time case studies are included across several different fields such as Image Processing, Text Mining, Healthcare, Finance, Digital Marketing, and HR Analytics. The book also introduces a statistical background and probabilistic framework to enhance the understanding of continuous distributions. Topics such as Ensemble Models, Deep Learning Models, Artificial Neural Networks, Expert Systems, and Decision-Based Systems round out the offerings of this book.
This multi-contributed book is a valuable source for researchers, academics, technologists, industrialists, practitioners, and all those who wish to explore the applications of AI, Knowledge Processing, Deep Learning, and Machine Learning.
Chapter
1. Introduction to Artificial Intelligence.
Chapter
2. AI and
Human Cognizance.
Chapter
3. Integration of Artificial Intelligence with IoT
for Smarter Systems: A Review.
Chapter
4. Influence of Artificial
intelligence in Robotics.
Chapter
5. A Review on Applications of Artificial
Intelligence and Robotics in Medical and Healthcare Sector.
Chapter
6. Impact
of the AI-INDUCED APP BABYLON in the healthcare industry.
Chapter
7.
Identification & Prediction of Pneumonia From CXR Images Using Deep Learning.
Chapter
8. Pulmonary cancer detection using deep convolutional networks.
Chapter
9. Breast Cancer prophecy Using Machine Learning algorithm (Random
forest, Decision Tree, Logistic Regression Techniques).
Chapter
10. Breast
cancer histopathological images classification using deep learning.
Chapter
11. Machine Learning And Signal Processing Methodologies To Diagnose The
Human Knee Joint Disorders A Computational Analysis.
Chapter
12.
Diagnostics and Treatment help to patients at Remote location using Edge and
Fog Computing Techniques (EFCT).
Chapter
13. Image Denoising Using
Autoencoders.
Chapter
14. Genetic Disorder Prediction using Machine Learning
Techniques.
Chapter
15. Bayesian Models in Cognitive Neuroscience.
Chapter
16. Knowledge Representation in AI.
Chapter
17. ANN Model for Analytics.
Chapter
18. AI and Real Time Business Intelligence.
Chapter
19. Introduction
to statistics and probability.
Chapter
20. Real Impacts of Machine Learning
in Business.
Chapter
21. A study on application of Natural Language
Processing (NLP) technique used in business analytics for better management
decisions: a Literature Review.
Chapter
22. Detection of Polarity in the
Native-Language Comments of Social Media Networks.
Chapter
23. Machine
Learning Techniques for Detecting and Analyzing Online Fake Reviews.
Chapter
24. A Study On Application Of Expert System As A Support System For Business
Decisions: A Literature Review.
Chapter
25. Applications of Artificial
Intelligence on Customer Experience and Service Quality of the Banking
Sector: An Overview.
Chapter
26. Prediction of Terrorist Attacks over the
Globe Using the Global Terrorism Database: A Comparative Analysis of Machine
Learning Prediction Algorithms.
Chapter
27. Deep Learning Approach for
Identifying the Bird Species.
Chapter
28. AI in Energy Sector.
Chapter
29.
Artificial Intelligence in the Fashion Design and IPRS.
Chapter
30.
Artificial intelligence in education: A Critic on English Language Teaching.
Chapter
31. Review of Learning Analytics Techniques and its Limitations in
the Higher Education: A 21st century paradigm
Hemachandran K is currently working as a Professor in the Department of Analytics and Artificial Intelligence at the School of Business, Woxsen University, Hyderabad, Telangana, India. He is a passionate teacher with 14 years of teaching experience and 5 years of research experience. His research interest are Machine Learning, Deep Learning, Computer Vision, NLP, Knowledge Engineering and Decision Support Systems. He has three patents to his credentials. He has more than 20 journals and international conference publications to his credit and has served as a resource person at various national and international scientific conferences.
Raul Villamarin Rodriguez is the Professor, School of Business, Woxsen University, Hyderabad, Telangana, India. He holds a Ph.D. in Artificial Intelligence and Robotics Process Automation applications in Human Resources. Fmr. Co-CEO at Irians Research Institute. His areas of expertise and interest are Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Robotic Process Automation, Multi-agent Systems, Knowledge Engineering, and Quantum Artificial Intelligence. He has co-authored two reference books and has more than 70 publications to his credit.
Umashankar Subramaniam is an Associate Professor in Electrical Engineering at the College of Engineering, Prince Sultan University, Riyadh Saudi Arabia. Previously he has worked as an Associate Professor and Head of the Department of Energy, VIT, Vellore. He has more than, 15 years of teaching, research, and industrial R&D experience. He has published more than 250 research papers in national and international journals and prestigious conferences. He is an Editor of IEEE Access, Heliyon, and other high-impact journals.
Valentina E. Balas is a Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, Aurel Vlaicu University of Arad, Romania. She holds a Ph.D. Cum Laude, in Applied Electronics and Telecommunications from the Polytechnic University of Timisoara. Dr. Balas is the author of more than 350 research papers in refereed journals and international conferences. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling, and Simulation. She is the Editor-in-Chief to the International Journal of Advanced Intelligence Paradigms (IJAIP) and to the International Journal of Computational Systems Engineering (IJCSysE).
