Part I. Innovative Trends in Computational Intelligence.- Chapter 1. Data Mining in Healthcare and Prediction Model Using Data-Mining Technique on Covid-19.- Chapter 2. Computational Intelligence in Intelligent Transportation Systems: An Overview.- Chapter 3. Insights to Computational Intelligence Techniques for Computer Vision.- Chapter 4. A two-stage multi-feature selection method to predict healthcare data using neural network.- Chapter 5. Computational Approaches for Detection and Classification of Crop Diseases.- Chapter 6. Three-Layer Multimodal Biometric Fusion Using SIFT and SURF Descriptors for Improved Accuracy of Authentication of Human Identity.- Chapter 7. Applying Computation Intelligence for Improved Computer Vision Capabilities.- Chapter 8. ECG Feature Extraction.- Chapter 9. Computational Intelligence in Web Min.- Chapter 10. A Review on Cognitive Computational Neuroscience: Overview, Models and Applications.- Chapter 11. Artificial Neural Network: Models, Applications and Challenges.- Chapter 12. Proportional and Multi-Stimulations Haptic Device for Active Upper Limbs Prosthetics Control.
Ravi Tomar is currently working in the capacity of Assistant Professor (Selection Grade) in School of Computer Science at University of Petroleum & Energy Studies, Dehradun, India. He is an experienced academician with a demonstrated history of working in the higher education industry. Skilled in Programming, Computer Networking, Stream processing, Python, Oracle Database, C++, Core Java, J2EE, RPA and CorDApp. His research interests include Wireless Sensor networks, Image Processing, Data Mining and Warehousing, Computer Networks, big data tehnologies and VANET. He has authored 51+ papers in different research areas, filled two Indian patent,edited 2 books and have authored 4 books. He has delivered Trainings to corporates nationally and Internationally on Confluent Apache Kafka, Stream Processing, RPA, CordaApp, J2EE and IoT to clients like Keybank, Accenture, Union Bank of Philippines, Ernst and Young and Deloitte. Dr Tomar is officaly recognised Instructor for Confluent and CordApp. He has conducted various International conferences in India, France and Nepal. He has been awarded as Young researcher in Computer Science and Engineering by RedInno, India in 2018
Manolo Dulva Hina is an Associate Professor in Computer Science in ECE Paris School of Engineering. He is an accomplished educator and researcher. He previously taught in Concordia University, and Vanier College in Canada; AMA International University – Bahrain, and Bahrain Polytechnic in Bahrain; and in University of Versailles Paris-Saclay, and recently in ECE Paris in France. He has supervised several Master and Ph.D. students. He has also authored several book chapters, journal papers and international conference papers, some of which were adjudged “Best Paper” of many conferences. He previously worked in two international projects, namely “CASA (Car Safety App)” involving several French and German industrial companies, and “European Union Lifelong Programme: Future Education and Training in Computing” in formulating the European framework in computing education and training in which he collaborated with several academicians representing 32 European countries. He was also the Dean of the College of Computer Studies of AMA International University – Bahrain when its Computer Science programme was first accredited by ABET (Accreditation Board for Engineering and Technology).
Rafik Zitouni is currently associate professor in computer science at ECE Paris-Graduate School of Engineering. He has co-edited several books on emerging technologies for developing countries. He also serves as a reviewer in ranked journals and outstanding international conferences. He was involved in three research projects with industrial partners (AIRBUS GROUP, EIFFAGE and VEDECOM). His research interests span areas of wireless networks and cyber security with digital signal processing. Software defined radio and machine learning as backgrounds. Application fields are the Internet of Things (IoT), Smart Cities and Wireless Vehicular Networks (VANET and LTE-V).
Amar Ramdane-Cherif received his Ph.D. degree from Pierre and Marie Curie University in Paris in 1998. In 2007, he obtained his HDR degree from University of Versailles. From 2000 to 2007, he was an Associate Professor at the University of Versailles and worked in PRISM Laboratory. Since 2008, he is a Full Professor at University of Versailles – Paris Saclay wherein he works in the LISV laboratory. His research interests include ambient intelligence, semantic representation of knowledge, modelling of the ambient environment, multimodal interaction between person/machine and machine/environment, system of fusion and fission of events, ambient assistance, software architecture, software quality, quality evaluation methods, functional and non-functional measurement of real-time, reactive and software embedded systems. He has already written 7 book chapters, 50 international journal papers and about 200 international conference articles. He has already supervised 20 PhD theses and reviewed 30 PhD theses. He has managed several projects and made several national and intentional collaborations. Currently, he is a member in the board council of the Graduate School of Computer Science of the University of Paris-Saclay.
This book addresses the key problems that computational intelligence aims to solve, including (i) the involved computational process might be too complex for mathematical reasoning; (ii) it might contain some uncertainties during the process, or (iii) by nature, the computational process is a randomly determined one (heuristic). The contributors make use of methods that are close to the human's way of reasoning, that is, available information might be inexact or incomplete, yet it would be able to produce controlled actions in an adaptive way. Approaches presented in the book include swarm intelligence, artificial immune systems, image processing, data mining, natural language processing, text mining, and other solutions involving artificial intelligence methodologies.
Addresses key computational issues that can be solved by computational intelligence;
Introduces various application domains by which computational intelligence is the preferred solution;
Includes approaches such as swam intelligence, data mining, and artificial intelligence.