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Recent Advances on Soft Computing and Data Mining by Rozaida Ghazali,Mustafa Mat Deris,Nazri Mohd Nawi,Jemal H. Abawajy Pdf
This book offers a systematic overview of the concepts and practical techniques that readers need to get the most out of their large-scale data mining projects and research studies. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. Presenting the outcomes of International Conference on Soft Computing and Data Mining (SCDM-2017), held in Johor, Malaysia on February 6–8, 2018, it provides a well-balanced integration of soft computing and data mining techniques. The two constituents are brought together in various combinations of applications and practices. To thrive in these data-driven ecosystems, researchers, engineers, data analysts, practitioners, and managers must understand the design choice and options of soft computing and data mining techniques, and as such this book is a valuable resource, helping readers solve complex benchmark problems and better appreciate the concepts, tools, and techniques employed.
Recent Advances on Soft Computing and Data Mining by Tutut Herawan,Rozaida Ghazali,Nazri Mohd Nawi,Mustafa Mat Deris Pdf
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.
Recent Advances on Soft Computing and Data Mining by Rozaida Ghazali,Nazri Mohd Nawi,Mustafa Mat Deris,Jemal H. Abawajy Pdf
This book provides an introduction to data science and offers a practical overview of the concepts and techniques that readers need to get the most out of their large-scale data mining projects and research studies. It discusses data-analytical thinking, which is essential to extract useful knowledge and obtain commercial value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad interdisciplinary range of scientific methods and processes. The book provides readers with sufficient knowledge to tackle a wide range of issues in complex systems, bringing together the scopes that integrate soft computing and data mining in various combinations of applications and practices, since to thrive in these data-driven ecosystems, researchers, data analysts and practitioners must understand the design choice and options of these approaches. This book helps readers to solve complex benchmark problems and to better appreciate the concepts, tools and techniques used.
Recent Advances in Soft Computing and Data Mining by Rozaida Ghazali,Nazri Mohd Nawi,Mustafa Mat Deris,Jemal H. Abawajy,Nureize Arbaiy Pdf
This book unfolds ways to transform data into innovative solutions perceived as new remarkable and meaningful value. It offers practical views of the concepts and techniques readers need to get the most out of their large-scale research and data mining projects. It strides them through the data-analytical thinking, circumvents the difficulty in deciphering complex data systems and obtaining commercialization value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad spectrum, an interdisciplinary field of scientific methods and processes. The book, Recent Advances in Soft Computing and Data Mining, delivers sufficient knowledge to tackle a wide range of issues seen in complex systems. This is done by exploring a vast combination of practices and applications by incorporating these two domains. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must choose the best design to approach the problem with the most efficient tools and techniques. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must understand the design choice and options of these approaches, thus to better appreciate the concepts, tools, and techniques used.
Soft Computing for Knowledge Discovery and Data Mining by Oded Maimon,Lior Rokach Pdf
Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.
Recent Advances on Soft Computing and Data Mining by Tutut Herawan,Rozaida Ghazali,Mustafa Mat Deris Pdf
This book constitutes the refereed proceedings of the First International Conference on Soft Computing and Data Mining, SCDM 2014, held in Universiti Tun Hussein Onn Malaysia, in June 16th-18th, 2014. The 65 revised full papers presented in this book were carefully reviewed and selected from 145 submissions, and organized into two main topical sections; Data Mining and Soft Computing. The goal of this book is to provide both theoretical concepts and, especially, practical techniques on these exciting fields of soft computing and data mining, ready to be applied in real-world applications. The exchanges of views pertaining future research directions to be taken in this field and the resultant dissemination of the latest research findings makes this work of immense value to all those having an interest in the topics covered.
Foundations and Advances in Data Mining by Wesley Chu,Tsau Young Lin Pdf
With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
Recent Advances in Soft Computing and Data Mining by Rozaida Ghazali,Nazri Mohd Nawi,Mustafa Mat Deris,Jemal H. Abawajy,Nureize Arbaiy Pdf
This book unfolds ways to transform data into innovative solutions perceived as new remarkable and meaningful value. It offers practical views of the concepts and techniques readers need to get the most out of their large-scale research and data mining projects. It strides them through the data-analytical thinking, circumvents the difficulty in deciphering complex data systems and obtaining commercialization value from the data. Also known as data-driven science, soft computing and data mining disciplines cover a broad spectrum, an interdisciplinary field of scientific methods and processes. The book, Recent Advances in Soft Computing and Data Mining, delivers sufficient knowledge to tackle a wide range of issues seen in complex systems. This is done by exploring a vast combination of practices and applications by incorporating these two domains. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must choose the best design to approach the problem with the most efficient tools and techniques. To thrive in these data-driven ecosystems, researchers, data analysts, and practitioners must understand the design choice and options of these approaches, thus to better appreciate the concepts, tools, and techniques used.
Data Mining and Computational Intelligence by Abraham Kandel,Mark Last,Horst Bunke Pdf
Many business decisions are made in the absence of complete information about the decision consequences. Credit lines are approved without knowing the future behavior of the customers; stocks are bought and sold without knowing their future prices; parts are manufactured without knowing all the factors affecting their final quality; etc. All these cases can be categorized as decision making under uncertainty. Decision makers (human or automated) can handle uncertainty in different ways. Deferring the decision due to the lack of sufficient information may not be an option, especially in real-time systems. Sometimes expert rules, based on experience and intuition, are used. Decision tree is a popular form of representing a set of mutually exclusive rules. An example of a two-branch tree is: if a credit applicant is a student, approve; otherwise, decline. Expert rules are usually based on some hidden assumptions, which are trying to predict the decision consequences. A hidden assumption of the last rule set is: a student will be a profitable customer. Since the direct predictions of the future may not be accurate, a decision maker can consider using some information from the past. The idea is to utilize the potential similarity between the patterns of the past (e.g., "most students used to be profitable") and the patterns of the future (e.g., "students will be profitable").
Advanced Soft Computing Techniques in Data Science, IoT and Cloud Computing by Sujata Dash,Subhendu Kumar Pani,Ajith Abraham,Yulan Liang Pdf
This book plays a significant role in improvising human life to a great extent. The new applications of soft computing can be regarded as an emerging field in computer science, automatic control engineering, medicine, biology application, natural environmental engineering, and pattern recognition. Now, the exemplar model for soft computing is human brain. The use of various techniques of soft computing is nowadays successfully implemented in many domestic, commercial, and industrial applications due to the low-cost and very high-performance digital processors and also the decline price of the memory chips. This is the main reason behind the wider expansion of soft computing techniques and its application areas. These computing methods also play a significant role in the design and optimization in diverse engineering disciplines. With the influence and the development of the Internet of things (IoT) concept, the need for using soft computing techniques has become more significant than ever. In general, soft computing methods are closely similar to biological processes than traditional techniques, which are mostly based on formal logical systems, such as sentential logic and predicate logic, or rely heavily on computer-aided numerical analysis. Soft computing techniques are anticipated to complement each other. The aim of these techniques is to accept imprecision, uncertainties, and approximations to get a rapid solution. However, recent advancements in representation soft computing algorithms (fuzzy logic,evolutionary computation, machine learning, and probabilistic reasoning) generate a more intelligent and robust system providing a human interpretable, low-cost, approximate solution. Soft computing-based algorithms have demonstrated great performance to a variety of areas including multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, biomedical and health informatics, etc. Soft computing approaches such as genetic programming (GP), support vector machine–firefly algorithm (SVM-FFA), artificial neural network (ANN), and support vector machine–wavelet (SVM–Wavelet) have emerged as powerful computational models. These have also shown significant success in dealing with massive data analysis for large number of applications. All the researchers and practitioners will be highly benefited those who are working in field of computer engineering, medicine, biology application, signal processing, and mechanical engineering. This book is a good collection of state-of-the-art approaches for soft computing-based applications to various engineering fields. It is very beneficial for the new researchers and practitioners working in the field to quickly know the best performing methods. They would be able to compare different approaches and can carry forward their research in the most important area of research which has direct impact on betterment of the human life and health. This book is very useful because there is no book in the market which provides a good collection of state-of-the-art methods of soft computing-based models for multimedia retrieval, fault tolerance, system modelling, network architecture, Web semantics, big data analytics, time series, and biomedical and health informatics.
Recent Advances in Data Mining of Enterprise Data by Thunshun Warren Liao,Evangelos Triantaphyllou Pdf
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as ?enterprise data?. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making.
Applications and Science in Soft Computing by Ahmad Lotfi,Jonathan M. Garibaldi Pdf
Soft computing techniques have reached a significant level of recognition and - ceptance from both the academic and industrial communities. The papers collected in this volume illustrate the depth of the current theoretical research trends and the breadth of the application areas in which soft computing methods are making c- tributions. This volume consists of forty six selected papers presented at the Fourth Inter- tional Conference on Recent Advances in Soft Computing, which was held in N- th th tingham, United Kingdom on 12 and 13 December 2002 at Nottingham Trent University. This volume is organized in five parts. The first four parts address mainly the f- damental and theoretical advances in soft computing, namely Artificial Neural Networks, Evolutionary Computing, Fuzzy Systems and Hybrid Systems. The fifth part of this volume presents papers that deal with practical issues and ind- trial applications of soft computing techniques. We would like to express our sincere gratitude to all the authors who submitted contributions for inclusion. We are also indebted to Janusz Kacprzyk for his - vices related to this volume. We hope you find the volume an interesting refl- tion of current theoretical and application based soft computing research.
Modern Technologies for Big Data Classification and Clustering by Seetha, Hari,Murty, M. Narasimha,Tripathy, B. K. Pdf
Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage. Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.
Soft Computing in Industrial Applications by Ashraf Saad,Erel Avineri,Keshav Dahal,Muhammad Sarfraz,Rajkumar Roy Pdf
Here is a collection of papers presented at the 11th On-line World Conference on Soft Computing in Industrial Applications, held in September-October 2006. This carefully edited book provides a comprehensive overview of recent advances in the industrial applications of soft computing and covers a wide range of application areas, including data analysis and data mining, computer graphics, intelligent control, systems, pattern recognition, classifiers, as well as modeling optimization.
First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining Discusses principles and classical algorithms on string matching and their role in data mining
