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Intelligent Automation in Renewable Energy (Hardcover, 1st ed. 2019): Tetyana Baydyk, Ernst Kussul, Donald C. Wunsch II Intelligent Automation in Renewable Energy (Hardcover, 1st ed. 2019)
Tetyana Baydyk, Ernst Kussul, Donald C. Wunsch II
R4,380 Discovery Miles 43 800 Ships in 10 - 15 working days

After an introduction to renewable energy technologies, the authors present computational intelligence techniques for optimizing the manufacture of related technologies, including solar concentrators. In particular the authors present new applications for their neural classifiers for image and pattern recognition. The book will be of interest to researchers in computational intelligence, in particular in the domain of neural networks, and engineers engaged with renewable energy technologies.

Adaptive Resonance Theory in Social Media Data Clustering - Roles, Methodologies, and Applications (Hardcover, 1st ed. 2019):... Adaptive Resonance Theory in Social Media Data Clustering - Roles, Methodologies, and Applications (Hardcover, 1st ed. 2019)
Lei Meng, Ah-Hwee Tan, Donald C. Wunsch II
R2,879 Discovery Miles 28 790 Ships in 10 - 15 working days

Social media data contains our communication and online sharing, mirroring our daily life. This book looks at how we can use and what we can discover from such big data: Basic knowledge (data & challenges) on social media analytics Clustering as a fundamental technique for unsupervised knowledge discovery and data mining A class of neural inspired algorithms, based on adaptive resonance theory (ART), tackling challenges in big social media data clustering Step-by-step practices of developing unsupervised machine learning algorithms for real-world applications in social media domain Adaptive Resonance Theory in Social Media Data Clustering stands on the fundamental breakthrough in cognitive and neural theory, i.e. adaptive resonance theory, which simulates how a brain processes information to perform memory, learning, recognition, and prediction. It presents initiatives on the mathematical demonstration of ART's learning mechanisms in clustering, and illustrates how to extend the base ART model to handle the complexity and characteristics of social media data and perform associative analytical tasks. Both cutting-edge research and real-world practices on machine learning and social media analytics are included in the book and if you wish to learn the answers to the following questions, this book is for you: How to process big streams of multimedia data? How to analyze social networks with heterogeneous data? How to understand a user's interests by learning from online posts and behaviors? How to create a personalized search engine by automatically indexing and searching multimodal information resources? .

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