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Modelling in Mechanical Engineering and Mechatronics : Towards Autonomous Intelligent Software Models
Modelling in Mechanical Engineering and Mechatronics presents a model-centred approach focusing on distributed development and use of autonomous intelligent software models, particularly the efficiency of the models, and their interaction and integration into distributed autonomous intelligent systems. In order to systematise the available knowledge, a domain ontology is presented; a subset of which is used to create a modelling theory based on knowledge and experience in the areas of software engineering, mechanical engineering and mechatronics. This holistic view of modelling explains the purpose and the essence of modelling, as well as the benefits that are to be expected. It discusses the relations to other branches of engineering and science and as a result, it demonstrates strategies, methods and tools for unleashing the full power of modelling.
Modelling Autonomic Communications Environments ; 3rd IEEE International Workshop, MACE 2008, Samos Island, Greece, September 22-26, 2008. Proceedings
Research and development of autonomics have come a long way, and we are delighted to present the proceedings of the 3rd IEEE International Workshop on Modelling Autonomic Communications Environments (MACE 2008).Asin the last two years, this workshopwasheld aspart of Manweek, the International Week on Management of Networks and Services, which took place on the lovely Island of Samos in Greece .MACE started as anexperimentin2006,andcreatedasmallcommunitythat nowfnds it self attracted backeachyearby afeeling ofexcitement-thatthere is something new going on. Certainly, MACE is not as shiny or practiced as other well-known conferences and workshops, but we consider this a feature of the workshopitself.
Modelling and simulation of discrete-event systems
Allows engineers to study and analyze complex systems. Discrete-event system (DES)-M&S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M&S tools become more powerful and more widely used in solving real-life problems.
Modelling and Optimization of Biotechnological Processes : Artificial Intelligence Approaches
The book begins with a historical introduction to the field of bioprocess control based on artificial intelligence approaches, followed by two chapters covering the optimization of fed-batch culture using genetic algorithms. Online biomass soft-sensors are constructed in Chapter 4 using recurrent neural networks. The bioprocess is then modelled in Chapter 5 by cascading two soft-sensor neural networks. Optimization and validation of the final product are detailed in Chapters 6 and 7. The general conclusions are drawn in Chapter 8.
Modelling and Identification with Rational Orthogonal Basis Functions
Models of dynamical systems are of great importance in almost all fields of science and engineering and specifically in control, signal processing and information science.
Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems : From Analytical to Soft Computing Approaches
This monograph presents a variety of techniques that can be used for designing robust fault diagnosis schemes for non-linear systems. The introductory part of the book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. Subsequently, advanced robust observer structures are presented. Parameter estimation based techniques are discussed as well. A particular attention is drawn to experimental design for fault diagnosis. The book also presents a number of robust soft computing approaches utilizing evolutionary algorithms and neural networks. All approaches described in this book are illustrated by practical applications.
Modelling and Development of Intelligent Systems ; 6th International Conference, MDIS 2019, Sibiu, Romania, October 3–5, 2019, Revised Selected Papers
This volume constitutes the refereed proceedings of the 6th International Conference on Modelling and Development of Intelligent Systems, MDIS 2019, held in Sibiu, Romania, in October 2019. The 13 revised full papers presented in the volume were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on adaptive systems; conceptual modelling; data mining; intelligent systems for decision support; machine learning.
Modelling and Control of Mini-Flying Machines
Modelling and Control of Mini-Flying Machines is an exposition of models developed for various types of mini-aircraft. Modelling and Control of Mini-Flying Machines provides valuable insights to the application of real-time nonlinear techniques in an always challenging area.
Modelling and Control of Dynamical Systems : Numerical Implementation in a Behavioral Framework
This book reviews known topics of the Behavioral Approach and offers new theoretic results with the advantage of including control algorithms implemented numerically in the computer. In addition, issues of numerical analysis are also included. The programs and algorithms are MATLAB based.
Modelling and Analysis of Hybrid Supervisory Systems : A Petri Net Approach
Modelling and Analysis of Hybrid Supervisory Systems introduces a modelling formalism that merges Petri nets, differential equation systems and object-oriented methods; a formalism that is adequate for modelling complex and large-scale systems. To guide the designer and conduct hybrid modelling, the book describes a method that starts from the requirements of a supervisory system and results in a proposal for such a system. The method is mainly based on Unified Modelling Language diagrams, well-known tools in both academia and industry. In order to ensure that the supervisory system will behave as expected under any operational circumstances, a validation procedure that allows verification of the formal properties of the hybrid model is presented.
Modelli Dinamici Discreti = Discrete Dynamic Models
Discrete mathematical modeling is one of the driving factors in modern mathematics research, and has played a role of synthesis between different disciplines, becoming a tool for qualitative and quantitative analysis in applied sciences. This volume provides an introduction to the analysis of discrete dynamic systems, following a modeling approach. An examination of a wide range of examples, models, and motivations drawn from Biology, Demography, Engineering and Economics, is followed by the presentation of the tools for the study of linear and non-linear scalar dynamical systems, with particular attention to stability analysis. The linear difference equations are studied in detail and an elementary introduction to the Z and DFT transforms is provided. One chapter is devoted to the study of bifurcations and chaotic dynamics. One-step vector dynamical systems and the applications of Markov chains are the subject of three chapters.
Modeling, Simulation and Optimization of Complex Processes HPSC 2018 ; Proceedings of the 7th International Conference on High Performance Scientific Computing, Hanoi, Vietnam, March 19-23, 2018
The contributions cover a broad, interdisciplinary spectrum of scientific computing and showcase recent advances in theory, methods, and practical applications. Subjects covered include numerical simulation, methods for optimization and control, machine learning, parallel computing and software development, as well as the applications of scientific computing in mechanical engineering, airspace engineering, environmental physics, decision making, hydrogeology, material science and electric circuits.
Modeling, Estimation and Control : Festschrift in Honor of Giorgio Picci on the Occasion of his Sixty-Fifth Birthday
Coefficients of Variations in Analysis of Macro-Policy Effects: An example of two-parameter Poisson-Dirichlet distributions.- How Many Experiments Are Needed to Adapt?- A Mutual Information Based Distance for Multivariate Gaussian Processes.- Differential Forms and Dynamical Systems.- An Algebraic Framework for Bayes Nets of Time Series.- A Birds Eye View on System Identification.- Further Results on the Byrnes-Georgiou-Lindquist Generalized Moment Problem.- Factor Analysis and Alternating Minimization.- Tensored PolynomialModels.- Distances Between Time-Series and Their Autocorrelation Statistics.- Global Identifiability of Complex Models, Constructed from Simple Submodels.- Identification of Hidden MarkovModels - Uniform LLN-s.- Identifiability and Informative Experiments in Open and Closed-Loop Identification.- On Interpolation and the Kimura-Georgiou Parametrization.- The Control of Error in Numerical Methods.- Contour Reconstruction and Matching Using Recursive Smoothing Splines.- Role of LQ Decomposition in Subspace Identification Methods.- Canonical Operators on Graphs.
Modeling, Control and Implementation of Smart Structures : A FEM-State Space Approach
This monograph presents an introductory overview of smart structures, their concepts, their active involvement in the vibration control, their applications and the extensive research work done on it so far. The modelling of flexible beams using two types of beam theories, viz., the Euler-Bernoulli theory and the Timoshenko beam theory is presented, including a new concept of finite element modeling of the flexible structures using Timoshenko beam theory with the inclusion of the shear both in the piezo-patches as well as in the host structure. It presents the design of the periodic output feedback control system for smart structure systems, the design of the FOS controllers for active vibration control and the design of Discrete Sliding Mode controllers using multirate output feedback technique.
Modeling with Itô Stochastic Differential Equations
This modeling procedure is thoroughly explained and illustrated for randomly varying systems in population biology, chemistry, physics, engineering, and finance. Introductory chapters present the fundamental concepts of random variables, stochastic processes, stochastic integration, and stochastic differential equations. These concepts are explained in a Hilbert space setting which unifies and simplifies the presentation. Computer programs, given throughout the text, are useful in solving representative stochastic problems. Analytical and computational exercises are provided in each chapter that complement the material in the text.
Modeling Uncertainty : An Examination of Stochastic Theory, Methods, and Applications
Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends and colleagues of Sid Yakowitz in his honor. Fifty internationally known scholars have collectively contributed 30 papers on modeling uncertainty to this volume. Each of these papers was carefully reviewed and in the majority of cases the original submission was revised before being accepted for publication in the book. The papers cover a great variety of topics in probability, statistics, economics, stochastic optimization, control theory, regression analysis, simulation, stochastic programming, Markov decision process, application in the HIV context, and others. There are papers with a theoretical emphasis and others that focus on applications. A number of papers survey the work in a particular area and in a few papers the authors present their personal view of a topic. It is a book with a considerable number of expository articles, which are accessible to a nonexpert - a graduate student in mathematics, statistics, engineering, and economics departments, or just anyone with some mathematical background who is interested in a preliminary exposition of a particular topic. Many of the papers present the state of the art of a specific area or represent original contributions which advance the present state of knowledge. In sum.
Modeling Solid Oxide Fuel Cells : Methods, Procedures and Techniques
The volume is structured in two parts. Part one presents the basic theory, and the general equations describing SOFC operation phenomena. Part two deals with the application of the theory to practical examples, where different SOFC geometries, configurations (from single cells to hybrid systems), operating conditions (steady-state and dynamic), and different phenomena (e.g. performance, temperature and chemical species, and mechanical stress distribution) are analyzed in detail.
Modeling Solar Radiation at the Earth’s Surface : Recent Advances
Solar radiation data is important for a wide range of applications, e.g. in engineering, agriculture, health sector, and in many fields of the natural sciences. A few examples showing the diversity of applications may include: architecture and building design e.g. air conditioning and cooling systems; solar heating system design and use; solar power generation; weather and climate prediction models; evaporation and irrigation; calculation of water requirements for crops; monitoring plant growth and disease control; skin cancer research.
Modeling Semantic Web Services : The Web Service Modeling Language
In this book, Jos de Bruijn and his coauthors lay the foundations for understanding the requirements that shape the description of the various aspects related to Semantic Web services, such as the static background knowledge in the form of ontologies, the functional description of the service, and the behavioral description of the service. They introduce the Web Service Modeling Language (WSML), which provides means for describing the functionality and behavior of Web services, as well as the underlying business knowledge, in the form of ontologies, with a conceptual grounding in the Web Service Modeling Ontology.
Modeling of metal forming and machining processes : By finite element and soft computing methods
The physics of metal forming and metal removing is normally expressed using non-linear partial differential equations which can be solved using the finite element method (FEM). However, when the process parameters are uncertain and/or the physics of the process is not well understood, soft computing techniques can be used with FEM or alone to model the process.
