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Proceedings of International Conference on Big Data, Machine Learning and their Applications, 1st ed. 2021 ICBMA 2019 Lecture Notes in Networks and Systems Series, Vol. 150

Langue : Anglais

Coordonnateurs : Tiwari Shailesh, Suryani Erma, Ng Andrew Keong, Mishra K. K., Singh Nitin

Couverture de l’ouvrage Proceedings of International Conference on Big Data, Machine Learning and their Applications

This book contains high-quality peer-reviewed papers of the International Conference on Big Data, Machine Learning and their Applications (ICBMA 2019) held at Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India, during 29?31 May 2020. The book provides significant contributions in a structured way so that prospective readers can understand how these techniques are used in finding solutions to complex engineering problems. The book covers the areas of big data, machine learning, bio-inspired algorithms, artificial intelligence and their applications.

​Chapter 1. Analysis of Efficiency of Fractional order Technique in a Controller for a complex Non-Linear Control Process.- Chapter 2. NWP models combined with Ensemble Models for Hourly Estimation of Global Solar Irradiance.- Chapter 3. Literature Review on Agricultural Internet of Things.- Chapter 4. Deep Learning approach based Network Intrusion Detection System for fog assisted IoT.- Chapter 5. Improving Prediction Accuracy for Debonding Quantification in Stiffened Plate by Meta Learning Model.- Chapter 6. The Need of Advanced Assisting Devices for Blind People.- Chapter 7. A Noval Fuzzy based Artificial Bee Colony Algorithm for Medical Records Classification.- Chapter 8. A comparative study: Glaucoma detection using deep neural networks.- Chapter 9. Security Risks and Challenges in IoT Based Applications.- Chapter 10. An Assessment of Type-2 Diabetes Risk Prediction using Machine Learning- A Review.- Chapter 11. Comparative Study of Different Reduced Precision Techniques in Deep Neural Network.- Chapter 12. A study of Predictive Measures in Neural Network Architectures for Plant Disease Detection.- Chapter 13. Design and Analysis of Smart Automatic Street Light System.- Chapter 14. Combating DDoS attack on OpenStack using Hypervisor based intrusion detection system with the help of machine learning.- Chapter 15. Exploring Honeycomb Interconnection Networks.

Prof. Shailesh Tiwari, Ph.D. currently works as a Director, ABES Engineering College, Ghaziabad, UP, India. He is an alumnus of Motilal Nehru National Institute of Technology Allahabad, India and having more than 20 years of experience in Teaching, Research and Administration. His primary areas of research are software testing, implementation of optimization algorithms and machine learning techniques in various engineering problems. He has published more than 90 publications in International Journals and in Proceedings of International Conferences of repute. He has edited special issues of several SCOPUS, SCIE and E-SCI-indexed journals. He has also edited several books published by Springer Nature. He has published 4 Indian patents as IPRs. He has organized several international conferences under the banner of IEEE, ACM and Springer. He is a Senior Member of IEEE, member of IEEE Computer Society, Fellow of Institution of Engineers (FIE). He is also a member of IEEE ComputerSociety- TCCC, TCSE, TCDE, TCSysE, IEEE Computer Society Test Technology Technical Council.

Dr. Andrew Keong Ng is an Associate Professor with Singapore Institute of Technology. He is the Deputy Programme Director of the BEng (Honours) and MEngTech programmes in Sustainable Infrastructure Engineering (Land), which focus on railway engineering and total preventive maintenance. He is a Chartered Engineer with the UK Engineering Council and serves on the committees of various local and international professional engineering institutions, such as Institute of Electrical and Electronics Engineers (IEEE), Institution of Engineers Singapore (IES), Institution of Engineering and Technology (IET), and Institution of Railway Signal Engineers (IRSE). He is a Senior Member of IEEE and IES, as well as a Consultant and Advisor to startups and multinational corporations. In addition, Dr. Ng is a Principal Investigator of several grants amounting to more than SGD 500,000. He holds one internatio

Presents selected works by active researchers in the field of big data and machine learning Discusses results of ICBMA 2019 Serves as a reference for researchers and practitioners in academia and industry

Date de parution :

Ouvrage de 409 p.

15.5x23.5 cm

Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).

158,24 €

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