Survey On Intelligent Data Repository Using Soft Computing

DOWNLOAD
Download Survey On Intelligent Data Repository Using Soft Computing PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Survey On Intelligent Data Repository Using Soft Computing book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Survey On Intelligent Data Repository Using Soft Computing
DOWNLOAD
Author : A. Prema
language : en
Publisher: Infinite Study
Release Date :
Survey On Intelligent Data Repository Using Soft Computing written by A. Prema and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Data warehouse is one of the components of the overall business intelligence system. An enterprise has one data warehouse, and data marts source has their information from the data warehouse. The Data warehouse is a corporation of all data marts within the enterprise. Information is always accumulated in the dimensional model. In this paper, an intelligent data repository with soft computing is presented. It covers similarity metrics that are commonly used to improve the efficiency of data storages. It also covers multiple decision making methodologies to improve the efficiency of decision making.
Intelligent Data Analysis
DOWNLOAD
Author : Michael R. Berthold
language : en
Publisher: Springer
Release Date : 2007-06-07
Intelligent Data Analysis written by Michael R. Berthold and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-07 with Computers categories.
This monograph is a detailed introductory presentation of the key classes of intelligent data analysis methods. The twelve coherently written chapters by leading experts provide complete coverage of the core issues. The first half of the book is devoted to the discussion of classical statistical issues, ranging from the basic concepts of probability, through general notions of inference, to advanced multivariate and time series methods, as well as a detailed discussion of the increasingly important Bayesian approaches and Support Vector Machines. The following chapters then concentrate on the area of machine learning and artificial intelligence and provide introductions into the topics of rule induction methods, neural networks, fuzzy logic, and stochastic search methods. The book concludes with a chapter on Visualization and a higher-level overview of the IDA processes, which illustrates the breadth of application of the presented ideas.
Intelligent Data Analysis
DOWNLOAD
Author : Deepak Gupta
language : en
Publisher: John Wiley & Sons
Release Date : 2020-04-27
Intelligent Data Analysis written by Deepak Gupta and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-27 with Technology & Engineering categories.
This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.
Meta Learning In Computational Intelligence
DOWNLOAD
Author : Norbert Jankowski
language : en
Publisher: Springer
Release Date : 2011-06-10
Meta Learning In Computational Intelligence written by Norbert Jankowski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-10 with Computers categories.
Computational Intelligence (CI) community has developed hundreds of algorithms for intelligent data analysis, but still many hard problems in computer vision, signal processing or text and multimedia understanding, problems that require deep learning techniques, are open. Modern data mining packages contain numerous modules for data acquisition, pre-processing, feature selection and construction, instance selection, classification, association and approximation methods, optimization techniques, pattern discovery, clusterization, visualization and post-processing. A large data mining package allows for billions of ways in which these modules can be combined. No human expert can claim to explore and understand all possibilities in the knowledge discovery process. This is where algorithms that learn how to learnl come to rescue. Operating in the space of all available data transformations and optimization techniques these algorithms use meta-knowledge about learning processes automatically extracted from experience of solving diverse problems. Inferences about transformations useful in different contexts help to construct learning algorithms that can uncover various aspects of knowledge hidden in the data. Meta-learning shifts the focus of the whole CI field from individual learning algorithms to the higher level of learning how to learn. This book defines and reveals new theoretical and practical trends in meta-learning, inspiring the readers to further research in this exciting field.
Data Science And Data Analytics
DOWNLOAD
Author : Amit Kumar Tyagi
language : en
Publisher: CRC Press
Release Date : 2021-09-22
Data Science And Data Analytics written by Amit Kumar Tyagi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-22 with Computers categories.
Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured (labeled) and unstructured (unlabeled) data. It is the future of Artificial Intelligence (AI) and a necessity of the future to make things easier and more productive. In simple terms, data science is the discovery of data or uncovering hidden patterns (such as complex behaviors, trends, and inferences) from data. Moreover, Big Data analytics/data analytics are the analysis mechanisms used in data science by data scientists. Several tools, such as Hadoop, R, etc., are used to analyze this large amount of data to predict valuable information and for decision-making. Note that structured data can be easily analyzed by efficient (available) business intelligence tools, while most of the data (80% of data by 2020) is in an unstructured form that requires advanced analytics tools. But while analyzing this data, we face several concerns, such as complexity, scalability, privacy leaks, and trust issues. Data science helps us to extract meaningful information or insights from unstructured or complex or large amounts of data (available or stored virtually in the cloud). Data Science and Data Analytics: Opportunities and Challenges covers all possible areas, applications with arising serious concerns, and challenges in this emerging field in detail with a comparative analysis/taxonomy. FEATURES Gives the concept of data science, tools, and algorithms that exist for many useful applications Provides many challenges and opportunities in data science and data analytics that help researchers to identify research gaps or problems Identifies many areas and uses of data science in the smart era Applies data science to agriculture, healthcare, graph mining, education, security, etc. Academicians, data scientists, and stockbrokers from industry/business will find this book useful for designing optimal strategies to enhance their firm’s productivity.
Informatics Networking And Intelligent Computing
DOWNLOAD
Author : Jiaxing Zhang
language : en
Publisher: CRC Press
Release Date : 2015-05-06
Informatics Networking And Intelligent Computing written by Jiaxing Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-06 with Computers categories.
This proceedings volume contains selected papers presented at the 2014 International Conference on Informatics, Networking and Intelligent Computing, held in Shenzhen, China. Contributions cover the latest developments and advances in the field of Informatics, Networking and Intelligent Computing.
Intelligent Data Engineering And Analytics
DOWNLOAD
Author : Suresh Chandra Satapathy
language : en
Publisher: Springer Nature
Release Date : 2020-08-29
Intelligent Data Engineering And Analytics written by Suresh Chandra Satapathy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-29 with Technology & Engineering categories.
This book gathers the proceedings of the 8th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2020), held at NIT Surathkal, Karnataka, India, on 4–5 January 2020. In these proceedings, researchers, scientists, engineers and practitioners share new ideas and lessons learned in the field of intelligent computing theories with prospective applications in various engineering disciplines. The respective papers cover broad areas of the information and decision sciences, and explore both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. Given its scope, the book offers a valuable resource for graduate students in various engineering disciplines.
Recent Advances On Soft Computing And Data Mining
DOWNLOAD
Author : Tutut Herawan
language : en
Publisher: Springer
Release Date : 2016-12-27
Recent Advances On Soft Computing And Data Mining written by Tutut Herawan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-27 with Technology & Engineering categories.
This book provides a comprehensive introduction and practical look at the concepts and techniques readers need to get the most out of their data in real-world, large-scale data mining projects. It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. The book is based on the Soft Computing and Data Mining (SCDM-16) conference, which was held in Bandung, Indonesia on August 18th–20th 2016 to discuss the state of the art in soft computing techniques, and offer participants sufficient knowledge to tackle a wide range of complex systems. The scope of the conference is reflected in the book, which presents a balance of soft computing techniques and data mining approaches. The two constituents are introduced to the reader systematically and brought together using different combinations of applications and practices. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techniques employed, and as such enables them to better understand the design choice and options of soft computing techniques and data mining approaches that are necessary to thrive in this data-driven ecosystem.
Intelligent Data Engineering And Automated Learning Ideal 2014
DOWNLOAD
Author : Emilio Corchado
language : en
Publisher: Springer
Release Date : 2014-08-13
Intelligent Data Engineering And Automated Learning Ideal 2014 written by Emilio Corchado and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-13 with Computers categories.
This book constitutes the refereed proceedings of the 15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014, held in Salamanca, Spain, in September 2014. The 60 revised full papers presented were carefully reviewed and selected from about 120 submissions. These papers provided a valuable collection of recent research outcomes in data engineering and automated learning, from methodologies, frameworks, and techniques to applications. In addition the conference provided a good sample of current topics from methodologies, frameworks, and techniques to applications and case studies. The techniques include computational intelligence, big data analytics, social media techniques, multi-objective optimization, regression, classification, clustering, biological data processing, text processing, and image/video analysis.
Intelligent Data Engineering And Automated Learning Ideal 2010
DOWNLOAD
Author : Colin Fyfe
language : en
Publisher: Springer
Release Date : 2010-08-21
Intelligent Data Engineering And Automated Learning Ideal 2010 written by Colin Fyfe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-21 with Computers categories.
The IDEAL conference has become a unique, established and broad interdisciplinary forum for experts, researchers and practitioners in many fields to interact with each other and with leading academics and industries in the areas of machine learning, information processing, data mining, knowledge management, bio-informatics, neu- informatics, bio-inspired models, agents and distributed systems, and hybrid systems. This volume contains the papers presented at the 11th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2010), which was held September 1–3, 2010 in the University of the West of Scotland, on its Paisley campus, 15 kilometres from the city of Glasgow, Scotland. All submissions were strictly pe- reviewed by the Programme Committee and only the papers judged with sufficient quality and novelty were accepted and included in the proceedings. The IDEAL conferences continue to evolve and this year’s conference was no exc- tion. The conference papers cover a wide variety of topics which can be classified by technique, aim or application. The techniques include evolutionary algorithms, artificial neural networks, association rules, probabilistic modelling, agent modelling, particle swarm optimization and kernel methods. The aims include regression, classification, clustering and generic data mining. The applications include biological information processing, text processing, physical systems control, video analysis and time series analysis.