Автор: Jacques Janssen; Christos H. Skiadas; Constantin Z Название: Advances in Stochastic Modelling and Data Analysis ISBN: 9048145740 ISBN-13(EAN): 9789048145744 Издательство: Springer Рейтинг: Цена: 111760.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Audience: A wide readership drawn from theoretical and applied mathematicians, such as operations researchers, management scientists, statisticians, computer scientists, bankers, marketing managers, forecasters, and scientific societies such as EURO and TIMS.
Автор: Chris Harris; Xia Hong; Qiang Gan Название: Adaptive Modelling, Estimation and Fusion from Data ISBN: 3642621198 ISBN-13(EAN): 9783642621192 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book brings together for the first time the complete theory of data based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. The book aims at researchers and advanced professionals in time series modelling, empirical data modelling, knowledge discovery, data mining and data fusion.
Автор: Zhang Tsinghua University Press Liyi Название: Blind Equalization in Neural Networks ISBN: 3110449625 ISBN-13(EAN): 9783110449624 Издательство: Walter de Gruyter Цена: 123910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms in recurrent networks, fuzzy networks and other frequently-studied neural networks. Each algorithm is accompanied by derivation, modeling and simulation, making the book an essential reference for electrical engineers, computer intelligence researchers and neural scientists.
Автор: Huynh Название: Integrated Uncertainty in Knowledge Modelling and Decision Making ISBN: 3319754289 ISBN-13(EAN): 9783319754284 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 6th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2018, held in Hanoi, Vietnam, in March 2018.The 39 revised full papers presented in this book were carefully reviewed and selected from 76 initial submissions.
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Want to predict what your customers want to buy without them having to tell you? Want to accurately forecast sales trends for your marketing team better than any employee could ever do? Then keep reading.
You've heard it before. The rise of artificial intelligence and how it will soon replace human beings and take away our jobs. What exactly is it capable of and how does this impact me? The real question you should be asking yourself is how can I use this to my advantage? How can I use machine learning to benefit my business and surpass my business goals? This book has the answer.
Designed for the tech novice, this book will break down the fundamentals of machine learning and what it truly means. You will learn to leverage neural networks, predictive modelling, and data mining algorithms, illustrated with real-world applications for finance, business and marketing.
Machine learning isn't just for scientists or engineers anymore. It's become accessible to anyone, and you can discover it's benefits for your business.
In Machine Learning for Beginners 2019, we will reveal:
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I know you might be overwhelmed at this point, but I assure you this book has been designed for absolute beginners. Everything is in plain English. There is no code, so no coding experience is required. You won't walk away a machine learning god, but you will walk away with key strategies you can implement right away to improve your business.
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Автор: Li Название: Artificial Intelligence with Uncertainty ISBN: 1584889985 ISBN-13(EAN): 9781584889984 Издательство: Taylor&Francis Рейтинг: Цена: 117390.00 T Наличие на складе: Нет в наличии. Описание: Through mathematical theories, models, and experimental computations, this book explores the uncertainties of knowledge and intelligence that occur during the cognitive processes of human beings. It describes the cloud model, its uncertainties of randomness and fuzziness, and the correlation between them. The book also centers on other physical methods for data mining, such as the data field and knowledge discovery state space. In addition, it presents an inverted pendulum example to discuss reasoning and control with uncertain knowledge as well as provides a cognitive physics model to visualize human thinking with hierarchy.
Автор: Van-Nam Huynh; Masahiro Inuiguchi; Bac Le; Nguyen Название: Integrated Uncertainty in Knowledge Modelling and Decision Making ISBN: 3319490451 ISBN-13(EAN): 9783319490458 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 5th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2016, held in Da Nang, Vietnam, in November/December 2016.
The IUKM symposia aim to provide a forum for exchanges of research results and ideas, and experience of application among researchers and practitioners involved with all aspects of uncertainty modelling and management.
Автор: Zengchang Qin; Van-Nam Huynh Название: Integrated Uncertainty in Knowledge Modelling and Decision Making ISBN: 3642395147 ISBN-13(EAN): 9783642395147 Издательство: Springer Рейтинг: Цена: 42860.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the International Symposium on Integrated Uncertainty in Knowledge Modeling and Decision Making, IUKM 2013, held in Beijing China, in July 2013. The papers provide a wealth of new ideas and report both theoretical and applied research on integrated uncertainty modeling and management.
Автор: Christian Servin; Vladik Kreinovich Название: Propagation of Interval and Probabilistic Uncertainty in Cyberinfrastructure-related Data Processing and Data Fusion ISBN: 3319385879 ISBN-13(EAN): 9783319385877 Издательство: Springer Рейтинг: Цена: 87060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: On various examples ranging from geosciences to environmental sciences, thisbook explains how to generate an adequate description of uncertainty, how to justifysemiheuristic algorithms for processing uncertainty, and how to make these algorithmsmore computationally efficient.
Автор: P?kala Название: Uncertainty Data in Interval-Valued Fuzzy Set Theory ISBN: 3319939092 ISBN-13(EAN): 9783319939094 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov`s intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information.
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