Anand a jose (307 risultati)

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Condizione: New. 1st edition NO-PA16APR2015-KAP.

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Paperback. Condizione: New. Predictive Analysis in Smart Agricultureexplores computational engineering techniques and applications in agriculture development. Recent technologies such as cloud computing, IoT, big data, and machine learning are focused on for smart agricultural engineering. The book also provides a case-oriented approach for IoT-based agricultural systems.This book deals with all aspects of smart agriculture with state-of-the-art predictive analysis in the complete 360-degree view spectrum. The book includes the concepts of urban and vertical farming using Agro IoT systems and renewable energy sources for modern agriculture trends. It discusses the real-world challenges, complexities in Agro IoT, and advantages of incorporating smart technology. It also presents the rapid advancement of the technologies in the existing Agri model by applying the various techniques. Novel architectural solutions in smart agricultural engineering are the core aspects of this book. Several predictive analysis tools and smart agriculture are also incorporated.This book can be used as a textbook for students in predictive analysis, agriculture engineering, precision farming, and smart agriculture. It can also be a reference book for practicing professionals in cloud computing, IoT, big data, machine learning, and deep learning working on smart agriculture applications.…

Paperback. Condizione: New. Mobile, wearable, and self-driving telephones are just a few examples of modern distributed networks that generate enormous amount of information every day. Due to the growing computing capacity of these devices as well as concerns over the transfer of private information, it has become important to process the part of the data locally by moving the learning methods and computing to the border of devices. Federated learning has developed as a model of education in these situations. Federated learning (FL) is an expert form of decentralized machine learning (ML). It is essential in areas like privacy, large-scale machine education and distribution. It is also based on the current stage of ICT and new hardware technology and is the next generation of artificial intelligence (AI). In FL, central ML model is built with all the data available in a centralised environment in the traditional machine learning. It works without problems when the predictions can be served by a central server. Users require fast responses in mobile computing, but the model processing happens at the sight of the server, thus taking too long. The model can be placed in the end-user device, but continuous learning is a challenge to overcome, as models are programmed in a complete dataset and the end-user device lacks access to the entire data package. Another challenge with traditional machine learning is that user data is aggregated at a central location where it violates local privacy policies laws and make the data more vulnerable to data violation. This book provides a comprehensive approach in federated learning for various aspects.…

hardcover. Condizione: Fine.

Paperback. Condizione: Brand New. 272 pages. 6.14x0.60x9.21 inches. In Stock.

Paperback. Condizione: Brand New. 312 pages. 9.18x6.12x9.21 inches. In Stock.

Paperback. Condizione: Brand New. 324 pages. 6.14x0.69x9.21 inches. In Stock.

Paperback. Condizione: Brand New. 362 pages. 9.18x6.12x9.21 inches. In Stock.

Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condizione: New. A. Jose Anand is a Professor at the Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, India. He has presented several papers in prominent conferences, has published several papers in reputed journals, and.

Condizione: New. Saravanan Krishnan is an Associate Professor, Department of Computer Science &amp Engineering at College of Engineering, Guindy, Anna University, Chennai, India. His research interest includes Cloud Computing, Software Engineering, Inte.