Page 29
Page 29
Modelling Environmental Dynamics : Advances in Geomatic Solutions
Modelling environmental dynamics is critical to understanding and predicting the evolution of the environment in response to the large number of influences including urbanisation, climate change and deforestation. Simulation and modelling provide support for decision making in environmental management.
Modelling Critical and Catastrophic Phenomena in Geoscience : A Statistical Physics Approach
This book presents a broad survey of models for critical and catastrophic phenomena in the geosciences, with strong emphasis on earthquakes. It assumes the perspective of statistical physics, which provides the theoretical frame for dealing with complex systems in general. This volume addresses graduate students wishing to specialize in the field and researchers working or interested in the field having a background in the physics, geosciences or applied mathematics.
Modelling community structure in freshwater ecosystems
"The book presents approaches and methodologies for predicting the structure and diversity of key aquatic communities (namely diatoms, benthic macroinvertebrates and fish), under natural conditions and under man-made disturbance. Such an approach will make it possible to: 1) set up procedures for robust and sensitive ecosystem evaluation, based on the prediction of the excepted community structure; 2) model community structure in disturbed ecosystems, taking into account all the relevant ecological variables; 3) test ecosystem sensitivity to natural and anthropic disturbance; and 4) explore specific actions to be taken for the restoration of ecosystem integrity."--Jacket.
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 Reasoning with Vague Concepts
This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark 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 Monitoring of Coastal Marine Processes
Although numerous books have been written on both monitoring and modelling of coastal oceans, there is a practical need for an introductory multi-disciplinary volume to non-specialists in this field. The articles commisioned for this book, organized into four major themes, are written by experts in their disciplines while the text is intended for scientists who do not have extensive training in marine sciences and coastal zone management. As such, the articles in this monograph can be a valuable reference for practicing professionals.
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 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 Matematici in Biologia = Mathematical Models in Biology
This text is addressed first of all to the students of the Specialist Degrees in Biology of the Universities, but it will also be of interest to students of Natural Sciences and Medicine. The topics covered include the most classic mathematical models of biological phenomena (population dynamics, spread of infectious diseases, simple physiology models), but a relevant part of the text is dedicated to the mathematical approach to the theory of natural evolution. The only prerequisites required of the reader are those provided by the basic courses of Mathematics of the Bachelor's Degree in Biology, Natural Sciences or Medicine.
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.
Modélisation et statistique spatiales = Spatial modeling and statistics
Spatial statistics are undergoing significant development due to their use in many fields: earth sciences, environment and climatology, epidemiology, econometrics, image analysis, etc. This book presents the main spatial models used as well as their statistics for the three types of data: geostatistics (observation on a continuous domain), data on a discrete network, point data. The objective is to present in a concise but mathematically complete way the most classical models (second order and variogram; software model and Gibbs-Markov field; point processes) as well as their simulation by MCMC algorithm. Then comes the presentation of statistical tools useful for their study.
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 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 Theory in Science Education
The book focuses as much on course content as on instruction and learning methodology, and presents practical aspects that have repeatedly demonstrated their value in fostering meaningful and equitable learning of physics and other science courses at the secondary school and college levels.The author shows how a scientific theory that is the object of a given science course can be organized around a limited set of basic models. Special tools are introduced, including modeling schemata, for students to meaningfully construct models and required conceptions, and for teachers to efficiently plan instruction and assess and regulate student learning and teaching practice. A scientific model is conceived to represent a particular pattern in the structure or behavior of physical realities and to explore and reify the pattern in specific ways. The author further shows how to engage students in modeling activities through structured learning cycles.
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 of Soft Matter
Soft matter plays a role in a wide variety of important processes and application. For example, gel swelling and dynamics are an essential part of many biological and individual processes, such as motility mechanisms in bacteria and the transport and absorption of drugs. Ferroelectrics, liquid crystals, and elastomers are being used to design ever faster switching devices. Experimental studies, such as scattering, optical and electron microscopy, have provided a great deal of detailed information on structures. But the integration of mathematical modeling and analysis with experimental approaches promises to greatly increase our understanding of structure-property relationships and constitutive equations. The workshop on Modeling of Soft Matter has taken such an integrated approach.
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.
