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    1. Naturvetenskap och teknik
    2. Matematik och naturvetenskap
    3. Matematik
    4. Tillämpad matematik

    Applied Mathematics in Engineering and Reliability

    Proceedings of the 1st International Conference on Applied Mathematics in Engineering and Reliability (Ho Chi Minh City, Vietnam, 4-6 May 2016)

    AvRadim Bris,Václav Snášel

    Inbunden, Engelska, 2016

    2 942 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    Applied Mathematics in Engineering and Reliability contains papers presented at the International Conference on Applied Mathematics in Engineering and Reliability (ICAMER 2016, Ho Chi Minh City, Viet Nam, 4-6 May 2016). The book covers a wide range of topics within mathematics applied in reliability, risk and engineering, including:- Risk and Reliability Analysis Methods- Maintenance Optimization- Bayesian Methods- Monte Carlo Methods for Parallel Computing of Reliability and Risk- Advanced Mathematical Methods in Engineering- Methods for solutions of Nonlinear Partial Differential Equations- Statistics and Applied Statistics, etc. The application areas range from Nuclear, Mechanical and Electrical Engineering to Information Technology and Communication, Safety Engineering, Environmental Engineering, Finance or Health and Medicine. The papers cover both theory and applications, which are focused to a wide range of sectors and problem areas. Integral demonstrations of the use of reliability and engineering mathematics are provided in many practical applications concerning major technological systems and structures.

    Produktinformation

    • Utgivningsdatum:2016-04-12
    • Mått:174 x 246 x undefined mm
    • Vikt:748 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:336
    • Förlag:Taylor & Francis Ltd
    • ISBN:9781138029286

    Utforska kategorier

    • Tillämpad matematik inom Naturvetenskap och teknik
    • Matematisk statistik inom Naturvetenskap och teknik

    Mer om författaren

    Radim Briš is research worker and university professor in applied mathematics and technical cybernetics in the Faculty of Engineering and Computer Science of the VŠB-Technical University of Ostrava, Czech Republic. He is also senior researcher in applied statistics and operational research at the Centrum Excelence IT4Innovations at the same university, and team leader for the Stochastic reliability modelling and risk management group. Dr. Briš recently became Vice-President of European Safety and Reliability Association, and is a member of ESRA Management Board. Previously, he spent one year as invited research professor at the Laboratoire de modélisation et de Sureté des Systemes, at the Université de Technologie de Troyes, France. He also spent 5 years in the position of Vice-Dean of the Faculty of Electrical Engineering and Computer Science, VŠB TU Ostrava.

    Innehållsförteckning

    • I - Applied Mathematics in Reliability Engineering; Bayesian methods, Bayesian reliability: A conjugate prior distribution for Bayesian analysis of the Power-Law Process; Bayesian approach to estimate the mixture of failure rate model; Cost oriented statistical decision problem in acceptance sampling and quality control; High-dimensional simulation experiments with particle filter and ensemble Kalman filter; The prior probability in classifying two populations by Bayesian method; Efficient Methods to Solve Optimization Problems; Estimation of parameters of Rikitake systems by SOMA; Clustering for probability density functions based on Genetic Algorithm; Optimization of truss structures with reliability-based frequency constraints under uncertainties of loadings and material properties; Optimum revenue calculation method to generate competitive hydroelectric power on Hua Na hydropower; Maintenance Modelling and Optimization; Network and Wireless Network Reliability; Risk and Hazard Analysis; System Reliability Analysis; II - Advanced Mathematical Methods for Engineering; Advanced Methods to Solve Partial Differential Equations; Inverse Problems; Advanced Numerical Methods; Statistics and Applied Statistics.