Advances in computer power and observing systems has led to the generation and accumulation of large scale weather & climate data begging for exploration and analysis. Pattern Identification and Data Mining in Weather and Climate presents, from different perspectives, most available, novel and conventional, approaches used to analyze multivariate time series in climate science to identify patterns of variability, teleconnections, and reduce dimensionality. The book discusses different methods to identify patterns of spatiotemporal fields. The book also presents machine learning with a particular focus on the main methods used in climate science. Applications to atmospheric and oceanographic data are also presented and discussed in most chapters. To help guide students and beginners in the field of weather & climate data analysis, basic Matlab skeleton codes are given is some chapters, complemented with a list of software links toward the end of the text. A number of technical appendices are also provided, making the text particularly suitable for didactic purposes. The topic of EOFs and associated pattern identification in space-time data sets has gone through an extraordinary fast development, both in terms of new insights and the breadth of applications. We welcome this text by Abdel Hannachi who not only has a deep insight in the field but has himself made several contributions to new developments in the last 15 years. - Huug van den Dool, Climate Prediction Center, NCEP, College Park, MD, U.S.A. Now that weather and climate science is producing ever larger and richer data sets, the topic of pattern extraction and interpretation has become an essential part. This book provides an up to date overview of the latest techniques and developments in this area. - Maarten Ambaum, Department of Meteorology, University of Reading, U.K. This nicely and expertly written book covers a lot of ground, ranging from classical linear pattern identification techniques to more modern machine learning, illustrated with examples from weather & climate science. It will be very valuable both as a tutorial for graduate and postgraduate students and as a reference text for researchers and practitioners in the field. - Frank Kwasniok, College of Engineering, University of Exeter, U.K.
Proceedings of the 4th International Workshop on Climate Informatics
Author: Valliappa Lakshmanan
This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that are increasingly needed in order to understand the climate system, an aspect which in turn has become crucial because of the threat of climate change. There has been a veritable explosion in the amount of data produced by satellites, environmental sensors and climate models that monitor, measure and forecast the earth system. In order to meaningfully pursue knowledge discovery on the basis of such voluminous and diverse datasets, it is necessary to apply machine learning methods, and Climate Informatics lies at the intersection of machine learning and climate science. This book grew out of the fourth workshop on Climate Informatics held in Boulder, Colorado in Sep. 2014.
13th International Conference, Natal, Brazil, August 29-31, 2012, Proceedings
Author: Hujun Yin
This book constitutes the refereed proceedings of the 13th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2012, held in Natal, Brazil, in August 2012. The 100 revised full papers presented were carefully reviewed and selected from more than 200 submissions for inclusion in the book and present the latest theoretical advances and real-world applications in computational intelligence.
5th International Workshop, NFMCP 2016, Held in Conjunction with ECML-PKDD 2016, Riva del Garda, Italy, September 19, 2016, Revised Selected Papers
Author: Annalisa Appice
This book features a collection of revised and significantly extended versions of the papers accepted for presentation at the 5th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2016, held in conjunction with ECML-PKDD 2016 in Riva del Garda, Italy, in September 2016. The book is composed of five parts: feature selection and induction; classification prediction; clustering; pattern discovery; applications.
This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. It goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. Until now, no single book has addressed all these topics in a comprehensive and integrated way. The chapters of this book fall into one of three categories: Fundamental chapters: Data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. These chapters comprehensively discuss a wide variety of methods for these problems. Domain chapters: These chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. Application chapters: These chapters study important applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. The domain chapters also have an applied flavor. Appropriate for both introductory and advanced data mining courses, Data Mining: The Textbook balances mathematical details and intuition. It contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). Numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples. Praise for Data Mining: The Textbook - “As I read through this book, I have already decided to use it in my classes. This is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. The book is complete with theory and practical use cases. It’s a must-have for students and professors alike!" -- Qiang Yang, Chair of Computer Science and Engineering at Hong Kong University of Science and Technology "This is the most amazing and comprehensive text book on data mining. It covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, Web, social network and privacy. It is a great book for graduate students and researchers as well as practitioners." -- Philip S. Yu, UIC Distinguished Professor and Wexler Chair in Information Technology at University of Illinois at Chicago
Applied Mathematics and Omics to Assess Crop Genetic Resources for Climate Change Adaptive Traits focuses on practical means and approaches to further the use of genetic resources for mitigating the effects of climate change and improving crop production. Genetic diversity in crop plants is being further explored to increase yield, disease resistance, and nutritional value by employing recent advances in mathematics and omics technologies to promote the adaptation of crops to changing climatic conditions. This book presents a broad view of biodiversity and genetic resources in agriculture and provides answers to some current problems. It also highlights ways to provide much-needed information to practitioners and innovators engaged in addressing the effects of global climate change on agriculture. The book is divided into sections that cover: The implications of climate change for drylands and farming communities The potential of genetic resources and biodiversity to adapt to and mitigate climate change effects Applications of mathematics and omics technologies Genomics and gene identification We are in the midst of significant changes in global climates, and its effects are already being felt throughout the world. The increasing frequency of droughts and heat waves has had negative impacts on agricultural production, especially in the drylands of the world. This book shares the collective knowledge of leading scientists and practitioners, giving readers a broader appreciation and heightened awareness of the stakes involved in improving and sustaining agricultural production systems in the face of climate change.
Confederated International Workshops and Posters, EI2N+NSF ICE, ICSP+INBAST, ISDE, ORM, OTMA, SWWS+MONET+SeDeS, and VADER 2011, Hersonissos, Crete, Greece, October 17-21, 2011, Proceedings
Author: Robert Meersman
This volume constitutes the refereed proceedings of nine international workshops, EI2N+NSF ICE, ICSP, INBAST, ISDE, MONET, ORM, SeDeS, SWWS, and VADER 2011, held as part of OTM 2011 in Hersonissos on the island of Crete, Greece, in October 2011. The 64 revised full papers presented were carefully reviewed and selected from a total of 104 submissions. The volume also includes three papers from the On the Move Academy (OTMA) 2011 and five ODBASE 2011 poster papers. Topics of the workshop papers are enterprise integration and semantics, information centric engineering, interoperability, industrial and business applications of semantic Web applications, information systems in distributed environments, process management in distributed information system development, distributed information systems: implementation issues and applications, industrial applications of fact-oriented modeling, data warehouse modeling, extensions to fact-oriented modeling, model validation procedures, schema transformations and mapping, semantic Web and Web semantics, ontology development, deployment and interoperability, data access and efficient computation, efficient information processing, exchange and knowledge synthesis algorithms, mobile and networking technologies for social applications, semantic and decision support, variability in software architecture, and dynamic and adaptive architectures.
4th International Visual Informatics Conference, IVIC 2015, Bangi, Malaysia, November 17-19, 2015, Proceedings
Author: Halimah Badioze Zaman
This book constitutes the refereed proceedings of the Fourth International Conference on Advances in Visual Informatics, IVIC 2015, held in Bangi, Malaysia, in November 2015. The five keynotes and 45 papers presented were carefully reviewed and selected from 82 initial submissions. The papers are organized in four tracks on visualization and big data; machine learning and computer vision; computer graphics; as well as virtual reality.
Multi-agent system (MAS) is an expanding field in science and engineering. It merges classical fields like game theory with modern ones like machine learning and computer science. This book provides a succinct introduction to the subject, covering the theoretical fundamentals as well as the latter developments in a coherent and clear manner. The book is centred on practical applications rather than introductory topics. Although it occasionally makes reference to the concepts involved, it will do so primarily to clarify real-world applications. The inner chapters cover a wide spectrum of issues related to MAS uses, which include collision avoidance, automotive applications, evacuation simulation, emergence analyses, cooperative control, context awareness, data (image) mining, resilience enhancement and the management of a single-user multi-robot.
Due to changes in the learning and research environment, changes in the behavior of library users, and unique global disruptions such as the COVID-19 pandemic, libraries have had to adapt and evolve to remain up-to-date and responsive to their users. Thus, libraries are adding new, digital resources and services while maintaining most of the old, traditional resources and services. New areas of research and inquiry in the field of library and information science explore the applications of machine learning, artificial intelligence, and other technologies to better serve and expand the library community. The Handbook of Research on Knowledge and Organization Systems in Library and Information Science examines new technologies and systems and their application and adoption within libraries. This handbook provides a global perspective on current and future trends concerning library and information science. Covering topics such as machine learning, library management, ICTs, blockchain technology, social media, and augmented reality, this book is essential for librarians, library directors, library technicians, media specialists, data specialists, catalogers, information resource officers, administrators, IT consultants and specialists, academicians, and students.