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Intelligent Quality Systems
Although the tenn quality does not have a precise and universally accepted definition, its meaning is generally well understood: quality is what makes the difference between success and failure in a competitive world. Given the importance of quality, there is a need for effective quality systems to ensure that the highest quality is achieved within given constraints on human, material or financial resources. This book discusses Intelligent Quality Systems, that is quality systems employing techniques from the field of Artificial Intelligence (AI). The book focuses on two popular AI techniques, expert or knowledge-based systems and neural networks. Expert systems encapsulate human expertise f...
Advanced Computational Methods for Knowledge Engineering
These proceedings consist of 19 papers, which have been peer-reviewed by international program committee and selected for the 5th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2017), which was held on June 30–July 1, 2017 in Berlin, Germany. The respective chapters discuss both theoretical and practical issues in connection with computational methods and optimization methods for knowledge engineering. The broad range of application areas discussed includes network computing, simulation, intelligent and adaptive e-learning, information retrieval, sentiment analysis, autonomous underwater vehicles, social media analysis, natural language processing, biomimetics in organizations, and cash management. In addition to pure content, the book offers many inspiring ideas and suggests new research directions, making it a valuable resource for graduate students, Ph.D. students, and researchers in Computer Science and Applied Mathematics alike.
Advanced Computational Methods for Knowledge Engineering
This proceedings book contains 37 papers selected from the submissions to the 6th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2019), which was held on 19–20 December, 2019, in Hanoi, Vietnam. The book covers theoretical and algorithmic as well as practical issues connected with several domains of Applied Mathematics and Computer Science, especially Optimization and Data Science. The content is divided into four major sections: Nonconvex Optimization, DC Programming & DCA, and Applications; Data Mining and Data Processing; Machine Learning Methods and Applications; and Knowledge Information and Engineering Systems. Researchers and practitioners in related areas will find a wealth of inspiring ideas and useful tools & techniques for their own work.
Advanced Computational Methods for Knowledge Engineering
The book consists of 29 extended chapters which have been selected and invited from the submissions to the 1st International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2013) held on 9-10 May, 2013 in Warsaw, Poland. The book is organized into five parts, which are: Advanced Optimization Methods and Their Applications, Queuing Theory and Applications, Computational Methods for Knowledge Engineering, Knowledge Engineering with Cloud and Grid Computing, and Logic Based Methods for Decision Making and Data Mining, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering.
Modelling, Computation and Optimization in Information Systems and Management Sciences
This proceedings set contains 85 selected full papers presentedat the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2015, held on May 11–13, 2015 at Lorraine University, France. The present part II of the 2 volume set includes articles devoted to Data analysis and Data mining, Heuristic / Meta heuristic methods for operational research applications, Optimization applied to surveillance and threat detection, Maintenance and Scheduling, Post Crises banking and eco-finance modelling, Transportation, as well as Technologies and methods for multi-stakeholder decision analysis in public settings.
5th International Conference on Digital Enterprise Technology
Digital Enterprise Technology (DET) is more than a concept. Companies arc facing new challenges in a context where the references are mostly numerical. Nowadays, digital methods and tools arc widely generalized. DET 2008 allowed excellent exchanges about "the collection of systems and methods for the digital modelling and analysis of the global product development and realisation process, in the context of lifecycle management". This book of proceedings gives a short vices of the keynotes and proposes the text of the papers that have been presented during DET 2008. This gives a clear view of the actual state of the art and of the industrial needs. This book of proceedings is organized with respect to the topics that were addressed during the conference.
Manufacturing and Supply Systems Management
In order to compete in an increasingly demanding market, many manufacturing companies have to redesign or restructure their manufacturing systems so that a set of coherent manufacturing strategies can be supported. So this book aims to provide a comprehensive treatment of manufacturing strategy analysis (MSA) and manufacturing systems design (MSD). The strategic concerns of manufacturing are linked to subsequent manufacturing systems design activities through the use of an effective MSA/MSD interface. Topics include: A structured approach to formulating manufacturing strategies; A set of linking processes to translate MSA concerns into relevant MSD action plans; Case studies. This book is intended to help graduates and industry-based professionals to make more informed decisions when working on system-design or redesign projects.
Intelligent Manufacturing and Mechatronics
This book presents the proceedings of SympoSIMM 2020, the 3rd edition of the Symposium on Intelligent Manufacturing and Mechatronics. Focusing on “Strengthening Innovations Towards Industry 4.0”, the book presents studies on the details of Industry 4.0’s current trends. Divided into five parts covering various areas of manufacturing engineering and mechatronics stream, namely, artificial intelligence, instrumentation and controls, intelligent manufacturing, modelling and simulation, and robotics, the book will be a valuable resource for readers wishing to embrace the new era of Industry 4.0.
Artificial Intelligence in Design ’92
Design has now become an important research topic in engineering and architecture. Design is one of the keystones to economic competitiveness and the fundamental precursor to manufacturing. The development of computational models founded on the artificial intelligence paradigm has provided an impetus for current design research. This volume contains contributions from the Second International Conference on Artificial Intelligence in Design held in June 1992 in Pittsburgh. They represent the state-of-the-art and the cutting edge of research and development in this field. They are of particular interest to researchers, developers and users of computer systems in design. This volume demonstrates both the breadth and depth of artificial intelligence in design and points the way forward for our understanding of design as a process and for the development of computer-based tools to aiddesigners.
AI-Powered IoT in the Energy Industry
AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems looks at opportunities to employ cutting-edge applications of artificial intelligence (AI), the Internet of Things (IoT), and Machine Learning (ML) in designing and modeling energy and renewable energy systems. The book's main objectives are to demonstrate how big data can help with energy efficiency and demand reduction, increase the usage of renewable energy sources, and assist in transitioning from a centralized system to a distributed, efficient, and embedded energy system. Contributions cover the fundamentals of the renewable energy sector, including solar, wind, biomass, and hydrogen, as well as building services and power generation systems. Chapters also examine renewable energy property prediction methods and discuss AI and IoT prediction models for biomass thermal properties. Covers renewable energy sector fundamentals; Explains the application of big data in distributed energy domains; Discusses AI and IoT prediction methods and models.
