Machine Learning Hybridization and Optimization for Intelligent Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning Hybridization and Optimization for Intelligent Applications write by Tanvir Habib Sardar. This book was released on 2024-10-08. Machine Learning Hybridization and Optimization for Intelligent Applications available in PDF, EPUB and Kindle. This book discusses state-of-the-art reviews of the existing machine-learning techniques and algorithms including hybridizations and optimizations. It is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.
Machine Learning Hybridization and Optimization for Intelligent Applications
Machine Learning Hybridization and Optimization for Intelligent Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning Hybridization and Optimization for Intelligent Applications write by Tanvir Habib Sardar. This book was released on 2024-10-28. Machine Learning Hybridization and Optimization for Intelligent Applications available in PDF, EPUB and Kindle. This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation. Features: • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised, and reinforcement learning using case study-based applications. • Covers the latest machine learning applications in as diverse domains as the Internet of Things, data science, cloud computing, and distributed and parallel computing. • Explains computing models using real-world examples and dataset-based experiments. • Includes case study-based explanations and usage for machine learning technologies and applications. This book is aimed at graduate students and researchers in machine learning, artificial intelligence, and electrical engineering.
Advances in Hybridization of Intelligent Methods
Advances in Hybridization of Intelligent Methods - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Advances in Hybridization of Intelligent Methods write by Ioannis Hatzilygeroudis. This book was released on 2017-10-13. Advances in Hybridization of Intelligent Methods available in PDF, EPUB and Kindle. This book presents recent research on the hybridization of intelligent methods, which refers to combining methods to solve complex problems. It discusses hybrid approaches covering different areas of intelligent methods and technologies, such as neural networks, swarm intelligence, machine learning, reinforcement learning, deep learning, agent-based approaches, knowledge-based system and image processing. The book includes extended and revised versions of invited papers presented at the 6th International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2016), held in The Hague, Holland, in August 2016. The book is intended for researchers and practitioners from academia and industry interested in using hybrid methods for solving complex problems.
Innovations in Hybrid Intelligent Systems
Innovations in Hybrid Intelligent Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Innovations in Hybrid Intelligent Systems write by Emilio Corchado. This book was released on 2007-12-22. Innovations in Hybrid Intelligent Systems available in PDF, EPUB and Kindle. This carefully edited book combines symbolic and sub-symbolic techniques to construct more robust and reliable problem solving models. This volume focused on "Hybrid Artificial Intelligence Systems" contains a collection of papers that were presented at the 2nd International Workshop on Hybrid Artificial Intelligence Systems, held in 12 - 13 November, 2007, Salamanca, Spain.
Machine Learning and Optimization Models for Optimization in Cloud
Machine Learning and Optimization Models for Optimization in Cloud - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Machine Learning and Optimization Models for Optimization in Cloud write by Punit Gupta. This book was released on 2022-02-27. Machine Learning and Optimization Models for Optimization in Cloud available in PDF, EPUB and Kindle. Machine Learning and Models for Optimization in Cloud’s main aim is to meet the user requirement with high quality of service, least time for computation and high reliability. With increase in services migrating over cloud providers, the load over the cloud increases resulting in fault and various security failure in the system results in decreasing reliability. To fulfill this requirement cloud system uses intelligent metaheuristic and prediction algorithm to provide resources to the user in an efficient manner to manage the performance of the system and plan for upcoming requests. Intelligent algorithm helps the system to predict and find a suitable resource for a cloud environment in real time with least computational complexity taking into mind the system performance in under loaded and over loaded condition. This book discusses the future improvements and possible intelligent optimization models using artificial intelligence, deep learning techniques and other hybrid models to improve the performance of cloud. Various methods to enhance the directivity of cloud services have been presented which would enable cloud to provide better services, performance and quality of service to user. It talks about the next generation intelligent optimization and fault model to improve security and reliability of cloud. Key Features · Comprehensive introduction to cloud architecture and its service models. · Vulnerability and issues in cloud SAAS, PAAS and IAAS · Fundamental issues related to optimizing the performance in Cloud Computing using meta-heuristic, AI and ML models · Detailed study of optimization techniques, and fault management techniques in multi layered cloud. · Methods to improve reliability and fault in cloud using nature inspired algorithms and artificial neural network. · Advanced study of algorithms using artificial intelligence for optimization in cloud · Method for power efficient virtual machine placement using neural network in cloud · Method for task scheduling using metaheuristic algorithms. · A study of machine learning and deep learning inspired resource allocation algorithm for cloud in fault aware environment. This book aims to create a research interest & motivation for graduates degree or post-graduates. It aims to present a study on optimization algorithms in cloud for researchers to provide them with a glimpse of future of cloud computing in the era of artificial intelligence.
