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Soft Sensors for Monitoring and Control of Industrial Processes
Soft Sensors for Monitoring and Control of Industrial Processes underlines the real usefulness of each approach and the sensitivity of the individual steps in soft-sensor design to the choice of one or the other. Design paths are suggested and readers shown how to evaluate the effects of their choices. All the case studies reported, resulting from collaborations between the authors and a number of industrial partners, raised challenging soft-sensor-design problems. The applications of soft sensors presented in this volume are designed to cope with the whole range from measuring system backup and what-if analysis through real-time prediction for plant control to sensor diagnosis and validation. Some of the soft sensors developed here are implemented on-line at industrial plants.
Soft Computing in Industrial Applications : Recent and Emerging Methods and Techniques
Soft Computing admits approximate reasoning, imprecision, uncertainty and partial truth in order to mimic aspects of the remarkable human capability of making decisions in real-life and ambiguous environments. "Soft Computing in Industrial Applications" contains a collection of papers that were 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 the 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. The book is aimed at researchers and practitioners who are engaged in developing and applying intelligent systems principles to solving real-world problems. It is also suitable as wider reading for science and engineering postgraduate students.
Soft Computing for Knowledge Discovery and Data Mining
The first three parts of this book are devoted to the principal constituents of soft computing: neural networks, evolutionary algorithms and fuzzy logic. The last part compiles the recent advances in soft computing for data mining, such as swarm intelligence, diffusion process and agent technology. This book provides investigators in the fields of information systems, engineering, computer science, operations research, bio-informatics, statistics and management with a profound source for the role of soft computing in data mining.
Soft Computing as Transdisciplinary Science and Technology ; Proceedings of the fourth IEEE International Workshop WSTST´05
Presents the proceedings of the Fourth International Workshop on Soft Computing as Transdisciplinary Science and Technology (WSTST '05), May 25-27, 2005, Muroran, Japan. It brings together the original work of international soft computing/computational intelligence researchers, developers, practitioners, and users. This proceedings provide contributions to all areas of soft computing including intelligent hybrid systems, agent-based systems, intelligent data mining, decision support systems, cognitive and reactive distributed artificial intelligence (AI), internet modelling, human interface, and applications in science and technology.
Soft Computing Applications in Business
Soft computing techniques are widely used in most businesses. This book consists of several important papers on the applications of soft computing techniques for the business field.The soft computing techniques used in this book include (or very closely related to): Bayesian networks, biclustering methods, case-based reasoning, data mining, Dempster-Shafer theory, ensemble learning, evolutionary programming, fuzzy decision trees, hidden Markov models, intelligent agents, k-means clustering, maximum likelihood Hebbian learning, neural networks, opportunistic scheduling, probability distributions combined with Monte Carlo methods, rough sets, self organizing maps, support vector machines, uncertain reasoning, other statistical and machine learning techniques, and combinations of these techniques.
Soft Computing : Methodologies and Applications
This carefully edited book covers a wide range of application areas of soft computing like optimization, data analysis and data mining, fault diagnosis, control as well as traffic and transportation systems. It contains 25 revised contributions from the 8th Online World Conferences on Soft Computing (WSC8). The collected papers show how the major soft computing techniques, fuzzy systems, neural networks and evolutionary algorithms and especially hybrid systems combining methods from these fields, lead to successful industrial applications. The reader will find an interesting, inspiring and wide variety of soft computing techniques and applications in this book.
SOFSEM 2008: Theory and Practice of Computer Science ; 34th Conference on Current Trends in Theory and Practice of Computer Science, Nový Smokovec, Slovakia, January 19-25, 2008. Proceedings
This book is segmented into four topical sections on foundations of computer science; computing by nature; networks, security, and cryptography; and Web technologies.
Social Computing, Behavioral Modeling, and Prediction
Social computing concerns the study of social behavior and context based on computational systems. Behavioral modeling reproduces the social behavior, and allows for experimenting, scenario planning, and deep understanding of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies creates an unprecedented environment where people can share opinions and experiences, exchange ideas, offer suggestions and advice, debate and even conduct experiments. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, anticipation, and prediction. This volume presents material from the first interdisciplinary workshop focused on employing social computing for behavioral modeling and prediction. The book provides a platform for disseminating results and developing new concepts and methodologies aimed at advancing and deepening our understanding of social and behavioral computing to aid critical decision making. The contributions incorporate views from government, industry and academia and they address research problems arising from pressing demands in the real world.
Social Computing with Artificial Intelligence
Provides a comprehensive introduction to the application of artificial intelligence in social computing, from fundamental data processing to advanced social network computing. To broaden readers’ understanding of the topics addressed, it includes extensive data and a large number of charts and references, covering theories, techniques and applications. It particularly focuses on data collection, data mining, artificial intelligence algorithms in social computing, and several key applications of social computing application, and also discusses network propagation mechanisms and dynamic analysis, which provide useful insights into how information is disseminated in online social networks. This book is intended for readers with a basic knowledge of advanced mathematics and computer science.
Snowflake Essentials : Getting Started with Big Data in the Cloud
Understand the essentials of the Snowflake Database and the overall Snowflake Data Cloud. This book covers how Snowflake’s architecture is different from prior on-premises and cloud databases. The authors also discuss, from an insider perspective, how Snowflake grew so fast to become the largest software IPO of all time. You will learn : Run analytics in the Snowflake Data Cloud / Create users and roles in Snowflake / Set up security in Snowflake / Set up resource monitors in Snowflake / Set up and optimize Snowflake Compute / Load, unload, and query structured and unstructured data (JSON, XML) within Snowflake / Use Snowflake Data Sharing to share data / Set up a Snowflake Data Exchange / Use the Snowflake Data Marketplace
Smart Sensing and Context ; 3rd European Conference, EuroSSC 2008, Zurich, Switzerland, October 29-31, 2008. Proceedings
This book is organized in topical sections on smart objects, spatial and human context inference, context processing and quality of context, as well as context-aware interaction and case studies.
Smart Homes and Health Telematics ; 6th International Conference, ICOST 2008 Ames, IA, USA, June 28-July 2, 2008 Proceedings
The book is organized in topical sections on assistive technology to improve quality of life for older adults and their caregivers; context awareness / autonomous computing; devices, systems and algorithms for vision / hearing / cognitive / communication impairments; home health monitoring and intervention; human-machine interface and ambient intelligence; modeling of physical and conceptual information in intelligent environments; real world deployments and experiences in smart homes, hospitals, and living communities; and social/privacy/security issues.
Simplifying data engineering and analytics with delta : Create analytics-ready data that fuels artificial intelligence and business intelligence
Data engineers, data scientists, ML practitioners, BI analysts, or anyone in the data domain working with big data will be able to put their knowledge to work with this practical guide to executing pipelines and supporting diverse use cases using the Delta protocol. Basic knowledge of SQL, Python programming, and Spark is required to get the most out of this book.
Similarity Search and Applications ; 13th International Conference, SISAP 2020, Copenhagen, Denmark, September 30 – October 2, 2020, Proceedings
Constitutes the refereed proceedings of the 13th International Conference on Similarity Search and Applications, SISAP 2020, held in Copenhagen, Denmark, in September/October 2020. The conference was held virtually due to the COVID-19 pandemic. The 19 full papers presented together with 12 short and 2 doctoral symposium papers were carefully reviewed and selected from 50 submissions. The papers are organized in topical sections named: scalable similarity search; similarity measures, search, and indexing; high-dimensional data and intrinsic dimensionality; clustering; artificial intelligence and similarity;
Sharing Data, Information and Knowledge ; 25th British National Conference on Databases, BNCOD 25, Cardiff, UK, July 7-10, 2008. Proceedings
The book are organized in topical sections on data mining and privacy, data integration, stream and event data processing, and query processing and optimisation. The volume in addition contains 5 invited papers by leading researchers from the International Colloquium on Advances in Database Research and the two best papers from the workshop on Biodiversity Informatics: Challenges in Modelling and Managing Biodiversity Knowledge.
Service-Oriented Computing ; Agents, Semantics, and Engineering ; AAMAS 2008 International Workshop, SOCASE 2008, Estoril, Portugal, May 12, 2008 Proceedings
The book address a range of topics at the intersection of service-oriented computing, semantic technology, and intelligent multiagent systems, such as: service description and discovery; planning, composition and negotiation; semantic processes and service agents; and applications.
Service-Oriented Computing : Agents, Semantics, and Engineering ; AAMAS 2007 International Workshop, SOCASE 2007, Honolulu, HI, USA, May 14, 2007, Proceedings
This book constitutes the refereed proceedings of the International Workshop on Service-Oriented Computing: Agents, Semantics, and Engineering, SOCASE 2007, held in Honolulu, HI, USA as an associated event of AAMAS 2007.
Sequence Data Mining
Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place.
Semantics, Web and Mining ; Joint International Workshop, EWMF 2005 and KDO 2005, Porto, Portugal, October 3-7, 2005, Revised Selected Papers
Finding knowledge – or meaning – in data is the goal of every knowledge d- covery e?ort. Subsequent goals and questions regarding this knowledge differ among knowledge discovery (KD) projects and approaches. One central question is whether and to what extent the meaning extracted from the data is expressed in a formal way that allows not only humans but also machines to understand and re-use it, i. e. , whether the semantics are formal semantics. Conversely, the input to KD processes di?ers between KD projects and approaches. One central question is whether the background knowledge, business understanding, etc. that the analyst employs to improve the results of KD is a set of natural-language statements, a theory in a formal language, or somewhere in between.
Semantics in Data and Knowledge Bases ; 3rd International Workshop, SDKB 2008, Nantes, France, March 29, 2008, Revised Selected Papers
This book presented original contributions demonstrating the use of logic, discrete mathematics, combinatorics, domain theory and other mathematical theories of semantics for database and knowledge bases, computational linguistics and semiotics, and information and knowledge-based systems.
