UID:
almahu_9949482364402882
Umfang:
XIV, 663 p. 325 illus., 244 illus. in color.
,
online resource.
Ausgabe:
1st ed. 2023.
ISBN:
9789811970412
Serie:
Algorithms for Intelligent Systems,
Inhalt:
This book gathers outstanding research papers presented in the 3rd International Conference on Artificial Intelligence: Advances and Application (ICAIAA 2022), held in Poornima College of Engineering, Jaipur, India, during April 23-24, 2022. This book covers research works carried out by various students such as bachelor, master and doctoral scholars, faculty and industry persons in the area of artificial intelligence, machine learning, deep learning applications in health care, agriculture, and business, security. It also covers research in core concepts of computer networks, intelligent system design and deployment, real-time systems, WSN, sensors and sensor nodes, SDN, NFV, etc.
Anmerkung:
Prediction of Polycystic Ovary Syndrome (PCOS) using Optimized Machine Learning Classifiers -- Literature Review: A Comparative Study of Software Defect Prediction Techniques -- Crop Recommendation using Machine Learning Algorithms and Soil Attributes Data -- Application of Machine Learning Models to Improve the Accuracy of Earnings Management Prediction -- Ensemble of Parametrized Quantum LSTM Neural Networks for Multimodal Stress Monitoring -- Evolutionary Algorithms for Marine Dynamical Systems: Towards Sustainable Renewable Energy Harvesting from Offshore Environment -- Comparison of Different Swarm Based Nature Inspired Algorithm for solution of Optimization Problem -- Assessment of Firm's Performance by Employing Text Mining Techniques -- Decisions Prediction Techniques using Language Processing and Learning Algorithms -- Machine Learning-based Tool to Classify Online Toxic Comments.
In:
Springer Nature eBook
Weitere Ausg.:
Printed edition: ISBN 9789811970405
Weitere Ausg.:
Printed edition: ISBN 9789811970429
Weitere Ausg.:
Printed edition: ISBN 9789811970436
Sprache:
Englisch
DOI:
10.1007/978-981-19-7041-2
URL:
https://doi.org/10.1007/978-981-19-7041-2
URL:
Volltext
(URL des Erstveröffentlichers)
