Автор: Rajshree Srivastava, Pradeep Kumar Mallick, Siddha Название: Computational Intelligence for Machine Learning and Healthcare Informatics ISBN: 3110647826 ISBN-13(EAN): 9783110647822 Издательство: Walter de Gruyter Цена: 136310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Автор: Das, S.K., Das, S.P., Dey, N., Hassanien, A.-E. Название: Machine Learning Algorithms for Industrial Applications ISBN: 3030506401 ISBN-13(EAN): 9783030506407 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics.
Название: Subjective Logic: A Formalism for Reasoning Under Uncertainty (Artificial Intelligence: Foundations, Theory, and Algorithms) 1st ed. 2016 Edition, Kindle Edition by Audun J?sang (Author) ISBN: 3319825550 ISBN-13(EAN): 9783319825557 Издательство: Springer Рейтинг: Цена: 167700.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is the first comprehensive treatment of subjective logic and all its operations. The author developed the approach, and in this book he first explains subjective opinions, opinion representation, and decision-making under vagueness and uncertainty, and he then offers a full definition of subjective logic, harmonising the key notations and formalisms, concluding with chapters on trust networks and subjective Bayesian networks, which when combined form general subjective networks. The author shows how real-world situations can be realistically modelled with regard to how situations are perceived, with conclusions that more correctly reflect the ignorance and uncertainties that result from partially uncertain input arguments.
The book will help researchers and practitioners to advance, improve and apply subjective logic to build powerful artificial reasoning models and tools for solving real-world problems. A good grounding in discrete mathematics is a prerequisite.
Автор: Fong, Simon James, Millham, Richard C Название: Bio-inspired Algorithms for Data Streaming and Visualization, Big Data Management, and Fog Computing ISBN: 9811566941 ISBN-13(EAN): 9789811566943 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases.
Автор: Solomon, Justin Название: Numerical Algorithms ISBN: 1482251884 ISBN-13(EAN): 9781482251883 Издательство: Taylor&Francis Рейтинг: Цена: 84710.00 T Наличие на складе: Невозможна поставка. Описание:
Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills.
The book covers a wide range of topics--from numerical linear algebra to optimization and differential equations--focusing on real-world motivation and unifying themes. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students' intuition while introducing extensions of the basic material.
The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background.
Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and clusters. Learn how to test your ML code and dive into even more advanced topics. If you are a beginner-to-intermediate programmer keen to understand machine learning, this book is for you.
Discover machine learning algorithms using a handful of self-contained recipes. Build a repertoire of algorithms, discovering terms and approaches that apply generally. Bake intelligence into your algorithms, guiding them to discover good solutions to problems.
In this book, you will:
Use heuristics and design fitness functions.
Build genetic algorithms.
Make nature-inspired swarms with ants, bees and particles.
Create Monte Carlo simulations.
Investigate cellular automata.
Find minima and maxima, using hill climbing and simulated annealing.
Try selection methods, including tournament and roulette wheels.
Learn about heuristics, fitness functions, metrics, and clusters.
Test your code and get inspired to try new problems. Work through scenarios to code your way out of a paper bag; an important skill for any competent programmer. See how the algorithms explore and learn by creating visualizations of each problem. Get inspired to design your own machine learning projects and become familiar with the jargon.
What You Need:
Code in C++ (>= C++11), Python (2.x or 3.x) and JavaScript (using the HTML5 canvas). Also uses matplotlib and some open source libraries, including SFML, Catch and Cosmic-Ray. These plotting and testing libraries are not required but their use will give you a fuller experience. Armed with just a text editor and compiler/interpreter for your language of choice you can still code along from the general algorithm descriptions.
Автор: Thomas S. Parker; Leon Chua Название: Practical Numerical Algorithms for Chaotic Systems ISBN: 1461281210 ISBN-13(EAN): 9781461281214 Издательство: Springer Рейтинг: Цена: 97820.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: One of the basic tenets of science is that deterministic systems are completely predictable-given the initial condition and the equations describing a system, the behavior of the system can be predicted 1 for all time.
Автор: Youssef Hamadi Название: Combinatorial Search: From Algorithms to Systems ISBN: 366251429X ISBN-13(EAN): 9783662514290 Издательство: Springer Рейтинг: Цена: 88500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book details key techniques in constraint networks, dealing in particular with constraint satisfaction, search, satisfiability, and applications in machine learning and constraint programming. Includes case studies.
Автор: Sujatha R., Aarthy S. L., Vettriselvan R. Название: Integrating Deep Learning Algorithms to Overcome Challenges in Big Data Analytics ISBN: 0367466635 ISBN-13(EAN): 9780367466633 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data science revolves around two giants, which are big data analytics and deep learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of big data along with deep learning systems.
Автор: Jun Sun, Choi-Hong Lai, Xiao-Jun Wu Название: Particle Swarm Optimisation: Classical and Quantum Perspectives ISBN: 1439835764 ISBN-13(EAN): 9781439835760 Издательство: Taylor&Francis Рейтинг: Цена: 183750.00 T Наличие на складе: Нет в наличии. Описание: Helping readers numerically solve optimization problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. The authors develop their novel QPSO algorithm, a PSO variant motivated from quantum mechanics, and show how to implement it in real-world applications, including inverse problems, digital filter d
Автор: Silhavy Название: Cybernetics and Algorithms in Intelligent Systems ISBN: 3319911910 ISBN-13(EAN): 9783319911915 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents recent research on Software Engineering and Algorithms in Intelligent SystemsProceedings of the 7th Computer Science On-line Conference 2018 (CSOC2018)The proceedings are divided in three volumes Volume 1: Software Engineering and Algorithms in Intelligent Systems, Volume 2: Artificial Intelligence and Algorithms in Intelligent Systems, Volume 3: Cybernetics and Algorithms in Intelligent Systems
Автор: Albert Benveniste; S.S. Wilson; Michel Metivier; P Название: Adaptive Algorithms and Stochastic Approximations ISBN: 3642758967 ISBN-13(EAN): 9783642758966 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Adaptive systems are widely encountered in many applications ranging through adaptive filtering and more generally adaptive signal processing, systems identification and adaptive control, to pattern recognition and machine intelligence: adaptation is now recognised as keystone of "intelligence" within computerised systems.
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