Data Science and Big Data: An Environment of Computational Intelligence, Witold Pedrycz; Shyi-Ming Chen
Автор: Tshilidzi Marwala; Monica Lagazio Название: Militarized Conflict Modeling Using Computational Intelligence ISBN: 1447127013 ISBN-13(EAN): 9781447127017 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume offers a scientific approach to manage inter-country conflict. Readers will find that through simultaneous control of four specific aspects (democracy, dependency, allies and capacity), predicted dispute outcomes can be avoided.
Автор: D.P. Acharjya; Satchidananda Dehuri; Sugata Sanyal Название: Computational Intelligence for Big Data Analysis ISBN: 3319362003 ISBN-13(EAN): 9783319362007 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing.
Описание: Blending theory with practice, this book brings together a variety of next-generation data technologies used to capture, integrate, analyze, mine, annotate and visualize distributed data in a manner that is meaningful and collaborative for the organization.
Автор: Himansu Sekhar Behera; Durga Prasad Mohapatra Название: Computational Intelligence in Data Mining—Volume 1 ISBN: 8132227328 ISBN-13(EAN): 9788132227328 Издательство: Springer Рейтинг: Цена: 26122.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book is a collection of high-quality peer-reviewed research papers presented in the Second International Conference on Computational Intelligence in Data Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India during 5 - 6 December 2015.
Автор: Witold Pedrycz; Shyi-Ming Chen Название: Information Granularity, Big Data, and Computational Intelligence ISBN: 3319082531 ISBN-13(EAN): 9783319082530 Издательство: Springer Рейтинг: Цена: 20896.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Nearest Neighbor Queries on Big Data.- Information Mining for Big Information.- Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression Analysis.- How to Understand Connections Based on Big Data: From Cliques to Flexible Granules.- Maintain 'Omics: When e-Maintenance Enters the Big Data Era.- Incrementally Mining Frequent Patterns for Large Database.- Improved Latent Semantic Indexing-based Data Mining Methods and An Application to Big.- The Property of Different Granule and Granular Methods Based on Quotient Space.- Towards An Optimal Task-Driven Information Granulation.- Unified Framework for Construction of Rule Based Classification Systems.- Multi-granular Evaluation Model through Fuzzy Random Regression to Improve Information.- Building Fuzzy Robust Regression Model Based on Granularity and Possibility Distribution.- The Role of Cloud Computing Architectures in Big Data.- Big Data Storage Techniques for Spatial Databases: Implications of Big Data Architecture on Spatial Query Processing.- The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases.- Customer Relationship Management and Big Data Mining.- Performance Competition for ISCIFCM and Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.-PEI Models under Uncontrolled Circumstances.- Rough Set Model based Knowledge Acquisition of Market Movements from Economic Data.- Deep Neural Network Modeling for Big Data Weather Forecast.- Current Knowledge and Future Challenge for Visibility Forecasting by Computational Intelligence.- Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.
Автор: D.P. Acharjya; Satchidananda Dehuri; Sugata Sanyal Название: Computational Intelligence for Big Data Analysis ISBN: 3319165976 ISBN-13(EAN): 9783319165974 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The work presented in this book is a combination of theoretical advancements of big data analysis, cloud computing, and their potential applications in scientific computing. The book discusses major issues pertaining to big data analysis using computational intelligence techniques and some issues of cloud computing.
Автор: Witold Pedrycz; Shyi-Ming Chen Название: Information Granularity, Big Data, and Computational Intelligence ISBN: 331938161X ISBN-13(EAN): 9783319381619 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Nearest Neighbor Queries on Big Data.- Information Mining for Big Information.- Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression Analysis.- How to Understand Connections Based on Big Data: From Cliques to Flexible Granules.- Maintain 'Omics: When e-Maintenance Enters the Big Data Era.- Incrementally Mining Frequent Patterns for Large Database.- Improved Latent Semantic Indexing-based Data Mining Methods and An Application to Big.- The Property of Different Granule and Granular Methods Based on Quotient Space.- Towards An Optimal Task-Driven Information Granulation.- Unified Framework for Construction of Rule Based Classification Systems.- Multi-granular Evaluation Model through Fuzzy Random Regression to Improve Information.- Building Fuzzy Robust Regression Model Based on Granularity and Possibility Distribution.- The Role of Cloud Computing Architectures in Big Data.- Big Data Storage Techniques for Spatial Databases: Implications of Big Data Architecture on Spatial Query Processing.- The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases.- Customer Relationship Management and Big Data Mining.- Performance Competition for ISCIFCM and Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.-PEI Models under Uncontrolled Circumstances.- Rough Set Model based Knowledge Acquisition of Market Movements from Economic Data.- Deep Neural Network Modeling for Big Data Weather Forecast.- Current Knowledge and Future Challenge for Visibility Forecasting by Computational Intelligence.- Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.
Автор: Himansu Sekhar Behera; Durga Prasad Mohapatra Название: Computational Intelligence in Data Mining ISBN: 9811038732 ISBN-13(EAN): 9789811038730 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 - 11, 2016.
Автор: Adam E Gaw?da; Janusz Kacprzyk; Leszek Rutkowski; Название: Advances in Data Analysis with Computational Intelligence Methods ISBN: 3319679457 ISBN-13(EAN): 9783319679457 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book is a tribute to Professor Jacek Żurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Żurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few.
At the same time, the book recognizes and honors Professor Żurada's dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world's largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields.
The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.
Описание: Preface.- List of Reviewers.- Program Committee.- About the Editors.- Table of Contents.- 30 Chapters.- Author Index.
Автор: Christian Moewes; Andreas N?rnberger Название: Computational Intelligence in Intelligent Data Analysis ISBN: 3642430856 ISBN-13(EAN): 9783642430855 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Complex systems and their phenomena are ubiquitous as they can befound in biology, finance, the humanities, management sciences,medicine, physics and similar fields.For many problems in these fields, there are no conventional ways tomathematically or analytically solve them completely at low cost.
Автор: Lipo Wang; Xiuju Fu Название: Data Mining with Computational Intelligence ISBN: 364206387X ISBN-13(EAN): 9783642063879 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: MLP Neural Networks for Time-Series Prediction and Classification.- Fuzzy Neural Networks for Bioinformatics.- An Improved RBF Neural Network Classifier.- Attribute Importance Ranking for Data Dimensionality Reduction.- Genetic Algorithms for Class-Dependent Feature Selection.- Rule Extraction from RBF Neural Networks.- A Hybrid Neural Network For Protein Secondary Structure Prediction.- Support Vector Machines for Prediction.- Rule Extraction from Support Vector Machines.
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