Описание: This book gathers cutting-edge papers in the area of Computational Intelligence, presented by specialists, and covering all major trends in the research community in order to provide readers with a rich primer.
Автор: Valliappa Lakshmanan; Eric Gilleland; Amy McGovern Название: Machine Learning and Data Mining Approaches to Climate Science ISBN: 3319172190 ISBN-13(EAN): 9783319172194 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed.
Описание: Machine Learning and Statistical Modeling Approaches to Image Retrieval describes several approaches of integrating machine learning and statistical modeling into an image retrieval and indexing system that demonstrates promising results.
Автор: Bandyopadhyay Mainak, Rout Minakhi, Chandra Satapathy Suresh Название: Machine Learning Approaches for Urban Computing ISBN: 9811609349 ISBN-13(EAN): 9789811609343 Издательство: Springer Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses various machine learning applications and models, developed using heterogeneous data, which helps in a comprehensive prediction, optimization, association analysis, cluster analysis and classification-related applications for various activities in urban area.
Автор: Raschka, Sebastian Mirjalili, Vahid Название: Python machine learning - ISBN: 1787125939 ISBN-13(EAN): 9781787125933 Издательство: Неизвестно Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second edition of Python Machine Learning by Sebastian Raschka is for developers and data scientists looking for a practical approach to machine learning and deep learning. In this updated edition, you`ll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow 1.x.
Автор: Singh Krishna Kant, Singh Akansha, Sharma Sanjay K. Название: Machine Learning Approaches for Convergence of Iot and Blockchain ISBN: 1119761743 ISBN-13(EAN): 9781119761747 Издательство: Wiley Рейтинг: Цена: 25811.00 р. Наличие на складе: Поставка под заказ.
Описание: MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN
The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication.
Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning.
Highlights of the book include:
Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT
Security of the Internet of Things using blockchain and AI
Developing smart cities and transportation systems using machine learning and IoT
Audience
The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Автор: Siddhartha Bhattacharyya; Paramartha Dutta; Susant Название: Hybrid Soft Computing Approaches ISBN: 8132225430 ISBN-13(EAN): 9788132225430 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Hybrid Soft Computing Approaches
Автор: Anna Esposito; Marcos Faudez-Zanuy; Francesco Carl Название: Multidisciplinary Approaches to Neural Computing ISBN: 3319569031 ISBN-13(EAN): 9783319569031 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Redefining Information Processing Through Neural Computing Models.- A Neural Approach for Hybrid Events Discrimination at Stomboli Volcano.- Fully Automatic Multispectral MR Image Segmentation of Prostate Gland Based on the Fuzzy C-Means Clustering Algorithm.- Integrating QuickBundles into a Model-Guided Approach for Extracting "Anatomically-Coherent'' and "Symmetry-Aware'' White Matter Fiber-Bundles.- Accurate Computation of Drude-Lorentz Model Coefficients of Single Negative Magnetic Metamaterials Using a Micro-Genetic Algorithm Approach.- Effective Blind Source Separation Based on the Adam Algorithm.- Depth-based Hand Pose Recognizer Using Learning Vector Quantization.- Correlation Dimension-Based Recognition of Simple Juggling Movements.- Cortical Phase Transitions as an Effect of Topology of Neural Network.- Fall Detection by Using an Innovative Floor Acoustic Sensor.- An improved Hilbert-Huang Transform for Non-Linear and Time-Variant Signals.- Privacy-preserving Data Mining for Distributed Medical Scenarios.- Rule Base Reduction Using Conflicting and Reinforcement Measures.- An Application of Internet Traffic Prediction with Deep Neural Network.- Growing Curvilinear Component Analysis (GCCA) for Dimensionality Reduction of Nonstationary Data.- Convolutional Neural Networks with 3-D Kernels for Voice Activity Detection in a Multiroom Environment.- A Hybrid Variable Selection Approach for NN-Based Classification in Industrial Context.- Advanced Neural Networks Systems for Unbalanced Industrial Datasets.- Quantum-Inspired Evolutionary Multiobjective Optimization for a Dynamic Production Scheduling Approach.- A Neural Network-Based Approach for Steam Turbine Monitoring.- A Predictive Model of Artificial Neural Network for Fuel Consumption in Engine Control System.- SOM-Based Analysis to Relate Non-Uniformities in Magnetic Measurements to Hot Strip Mill Process Conditions.- Vision-Based Mapping and Micro-Localization of Industrial Components in the Fields of Laser Technology.- When Intuitive Decisions Making, Based on Expertise, May Deliver Better Results than a Rational, Deliberate Approach.- Artificial Entities or Moral Agents? How AI is Changing Human Evolution.
Описание: Presents the most innovative systematic and practical facets of fuzzy computing technologies to students, scholars, and academicians, as well as practitioners, engineers, and professionals. This premier reference source focuses on up-to-date theoretical views of fuzzy computing while highlighting empirical approaches useful to real world utilization.
Автор: Anna Esposito; Marcos Faudez-Zanuy; Francesco Carl Название: Multidisciplinary Approaches to Neural Computing ISBN: 3319860313 ISBN-13(EAN): 9783319860312 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Поставка под заказ.
Описание: This book presents a collection of contributions in the field of Artificial Neural Networks (ANNs). The themes addressed are multidisciplinary in nature, and closely connected in their ultimate aim to identify features from dynamic realistic signal exchanges and invariant machine representations that can be exploited to improve the quality of life of their end users.Mathematical tools like ANNs are currently exploited in many scientific domains because of their solid theoretical background and effectiveness in providing solutions to many demanding tasks such as appropriately processing (both for extracting features and recognizing) mono- and bi-dimensional dynamic signals, solving strong nonlinearities in the data and providing general solutions for deep and fully connected architectures. Given the multidisciplinary nature of their use and the interdisciplinary characterization of the problems they are applied to – which range from medicine to psychology, industrial and social robotics, computer vision, and signal processing (among many others) – ANNs may provide a basis for redefining the concept of information processing. These reflections are supported by theoretical models and applications presented in the chapters of this book.This book is of primary importance for: (a) the academic research community, (b) the ICT market, (c) PhD students and early-stage researchers, (d) schools, hospitals, rehabilitation and assisted-living centers, and (e) representatives of multimedia industries and standardization bodies.
Автор: Chi-Bin Cheng; Hsu-Shih Shih; E. Stanley Lee Название: Fuzzy and Multi-Level Decision Making: Soft Computing Approaches ISBN: 3319925245 ISBN-13(EAN): 9783319925240 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.
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