Includes bibliographical references and index.

"We have access to a variety of cutting-edge technologies, thanks to the digital world, which has made life simpler and more intelligent. As a result, in the advancement of the Internet, no one is unreachable and we can now easily share ideas for new innovations and collaborate with people across great distances. The amount of data on the internet is exploding as a result of the extensive research being conducted to advance new technologies. Due to this massive data collection, there is also an increase in the risk of sensitive information being leaked. Therefore, it is necessary to look for methods and equipment to collect, manage, analyse, and store data in a secure manner. Cloud computing, deep learning, machine learning, and big data analysis are the topics of computational intelligence that offer methods for dealing with large amounts of unstructured data, while cyber security and cryptography are the topics, we study to find ways to secure data. In practical situations the data we collect are vague and ambiguous as it depends upon human reasoning. Fuzzy logic-based systems play an important role in making decisions in uncertain environments because their reasoning is similar to human reasoning. This book covers the novel researches based on various computational intelligence topics including deep learning, artificial intelligence, machine learning, neural network, healthcare, solutions of various problems using fuzzy systems and their applications in cryptography, assignment problems, transportation problems, cloud computing, etc. The goal of writing the book is to promote advances in the field of computational intelligence systems and to aid in the dissemination of results concerning recent applications in the areas of computational intelligence system-based applications, its allied branches like artificial intelligence, deep learning, cloud computing, fuzzy system, etc. among working professionals, researchers, and educators. The book will be useful for Data Scientists, web developers, cryptographers, medical researchers, engineers, researchers, and graduate level students in computer science, data science, operations research, and mathematics. It provides novel applications as well as new theoretical developments required to understand current computational intelligence topics such as deep learning, machine learning, fuzzy based systems, and various other relevant fields. Graduate and postgraduate Computer Science, Engineering, Information Technology and Mathematics students, as well as teachers, can use it as a reference book because they can find applications that can be used to clarify specific concepts"-- Provided by publisher.

Intro -- Contents -- Preface -- Chapter 1 -- Automatic Text Summarization -- Abstract -- Introduction -- Background -- Deep Learning -- Sequence-to-Sequence Model -- Encoder -- Decoder -- Interference Phase -- Intuition behind Attention Mechanism -- Implementation Details -- Dataset -- Process for Text Summarization -- Observations -- Conclusion -- Disclaimer -- References -- Chapter 2 -- A Survey and Taxonomy on Energy Efficient Software Techniques in Cloud Environments -- Abstract -- Introduction -- Focus of This Survey -- Energy Saving Strategies through Resource Management Technique

Energy-Aware Resource Consolidation Technique -- Energy-Aware Resource Scheduling -- Energy Saving Strategies through Data Management Technique -- Energy Saving Data Classification Technique -- Energy Saving Data Replication -- Observation of the Energy Efficient Techniques in Cloud Environment -- New Challenges -- Conclusion -- References -- Chapter 3 -- Epidemic Analysis and Prediction of Future Reachability of COVID-19 Using Machine Learning -- Abstract -- 1. Introduction -- 2. Literature Review -- 3. Research Gaps -- 4. Methodology -- 4.1. Dataset Description -- 4.2. Dataset Pre-Processing

4.3. Training and Testing -- 4.4. Classification Method -- 5. Experimental Setup and Implementation -- 6. Results and Discussion -- 6.1. Performance Metrics Evaluation -- 6.1.1. Mean Absolute Error -- 6.1.2. Mean Squared Error -- 6.1.3. Root Mean Squared Error -- 7. Discussion and Future Scope -- References -- Chapter 4 -- Prediction of Indirect Evaporative Cooling System Using Artificial Neural Networks -- Abstract -- Introduction -- Artificial Neural Network -- Performance Prediction of Indirect Evaporative Cooling Using Artificial Neural Network -- Result and Discussion -- Conclusion

Steganography Scheme Using Principal Component Analysis -- Result of Simulation Experiment Using Principal Component Analysis -- Comparison Chart -- Conclusion and Future Work -- Disclaimer -- References -- Chapter 6 -- Can Vaccinations Reduce the Rapid Spread of COVID-19? -- Abstract -- Introduction -- Methods -- Results -- The US -- The UK -- Germany -- Russia -- India -- Oman -- The UAE -- Conclusion -- Disclaimer -- References -- Chapter 7 -- A Comparative Study between Incident Edge Path Algorithm and Dijkstra Algorithm for Finding the Shortest Path for Networks -- Abstract -- Introduction

Description based on online resource; title from digital title page (viewed on April 27, 2023).

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