Heuristic And Optimization For Knowledge Discovery
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Heuristic And Optimization For Knowledge Discovery
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Author :
language : en
Publisher:
Release Date : 2002
Heuristic And Optimization For Knowledge Discovery written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
Heuristic And Optimization For Knowledge Discovery
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Author : Ruhul A. Sarker
language : en
Publisher:
Release Date : 2002
Heuristic And Optimization For Knowledge Discovery written by Ruhul A. Sarker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Combinatorial optimization categories.
Heuristic And Optimization For Knowledge Discovery
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Author : Abbass, Hussein A.
language : en
Publisher: IGI Global
Release Date : 2001-07-01
Heuristic And Optimization For Knowledge Discovery written by Abbass, Hussein A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-01 with Computers categories.
With the large amount of data stored by many organizations, capitalists have observed that this information is an intangible asset. Unfortunately, handling large databases is a very complex process and traditional learning techniques are expensive to use. Heuristic techniques provide much help in this arena, although little is known about heuristic techniques. Heuristic and Optimization for Knowledge Discovery addresses the foundation of this topic, as well as its practical uses, and aims to fill in the gap that exists in current literature.
Data Mining A Heuristic Approach
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Author : Abbass, Hussein A.
language : en
Publisher: IGI Global
Release Date : 2001-07-01
Data Mining A Heuristic Approach written by Abbass, Hussein A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-07-01 with Computers categories.
Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solving methods are no longer capable of handling this level of complexity, heuristic search methods have attracted increasing attention in recent years for solving such problems. Inspired by nature, biology, statistical mechanics, physics and neuroscience, heuristics techniques are used to solve many problems where traditional methods have failed. Data Mining: A Heuristic Approach will be a repository for the applications of these techniques in the area of data mining.
Data Driven Optimization And Knowledge Discovery For An Enterprise Information System
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Author : Qing Duan
language : en
Publisher: Springer
Release Date : 2015-06-13
Data Driven Optimization And Knowledge Discovery For An Enterprise Information System written by Qing Duan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-13 with Technology & Engineering categories.
This book provides a comprehensive set of optimization and prediction techniques for an enterprise information system. Readers with a background in operations research, system engineering, statistics, or data analytics can use this book as a reference to derive insight from data and use this knowledge as guidance for production management. The authors identify the key challenges in enterprise information management and present results that have emerged from leading-edge research in this domain. Coverage includes topics ranging from task scheduling and resource allocation, to workflow optimization, process time and status prediction, order admission policies optimization, and enterprise service-level performance analysis and prediction. With its emphasis on the above topics, this book provides an in-depth look at enterprise information management solutions that are needed for greater automation and reconfigurability-based fault tolerance, as well as to obtain data-driven recommendations for effective decision-making.
Trends And Applications In Knowledge Discovery And Data Mining
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Author : U Kang
language : en
Publisher: Springer
Release Date : 2017-10-07
Trends And Applications In Knowledge Discovery And Data Mining written by U Kang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-07 with Computers categories.
This book constitutes the thoroughly refereed post-workshop proceedings at PAKDD Workshops 2017, held in conjunction with PAKDD, the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining in May 2017 in Jeju, South Korea. The 17 revised papers presented were carefully reviewed and selected from 38 submissions. The workshops affiliated with PAKDD 2017 include: Workshop on Machine Learning for Sensory Data Analysis (MLSDA), Workshop on Biologically Inspired Data Mining Techniques (BDM), Pacific Asia Workshop on Intelligence and Security Informatics (PAISI), and Workshop on Data Mining in Business Process Management (DM-BPM).
Feature Selection For Knowledge Discovery And Data Mining
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Author : Huan Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Feature Selection For Knowledge Discovery And Data Mining written by Huan Liu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.
Soft Computing
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Author : Mangey Ram
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2020-08-24
Soft Computing written by Mangey Ram and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-24 with Technology & Engineering categories.
Soft computing is used where a complex problem is not adequately specified for the use of conventional math and computer techniques. Soft computing has numerous real-world applications in domestic, commercial and industrial situations. This book elaborates on the most recent applications in various fields of engineering.
Advances In Knowledge Discovery And Data Mining
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Author : Joshua Zhexue Huang
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-05-09
Advances In Knowledge Discovery And Data Mining written by Joshua Zhexue Huang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-05-09 with Computers categories.
The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knoweldge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.
Bayesian Heuristic Approach To Discrete And Global Optimization
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Author : Jonas Mockus
language : en
Publisher: Springer
Release Date : 2010-12-07
Bayesian Heuristic Approach To Discrete And Global Optimization written by Jonas Mockus and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-07 with Mathematics categories.
Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This book is the first to demonstrate that this framework is also well suited for the exploitation of heuristic methods in the solution of such problems, especially those of large scale for which exact optimization approaches can be prohibitively costly. The book covers all aspects ranging from the formal presentation of the Bayesian Approach, to its extension to the Bayesian Heuristic Strategy, and its utilization within the informal, interactive Dynamic Visualization strategy. The developed framework is applied in forecasting, in neural network optimization, and in a large number of discrete and continuous optimization problems. Specific application areas which are discussed include scheduling and visualization problems in chemical engineering, manufacturing process control, and epidemiology. Computational results and comparisons with a broad range of test examples are presented. The software required for implementation of the Bayesian Heuristic Approach is included. Although some knowledge of mathematical statistics is necessary in order to fathom the theoretical aspects of the development, no specialized mathematical knowledge is required to understand the application of the approach or to utilize the software which is provided. Audience: The book is of interest to both researchers in operations research, systems engineering, and optimization methods, as well as applications specialists concerned with the solution of large scale discrete and/or nonconvex optimization problems in a broad range of engineering and technological fields. It may be used as supplementary material for graduate level courses.