الصفحة 10
الصفحة 10
img

Mathematical and Computational Models for Congestion Charging

This book presents rigorous treatments of issues related to congestion pricing. The chapters describe recent advances in areas such as mathematical and computational models for predicting traffic congestion, determining when, where, and how much to levy tolls, and analyzing the impact of tolls on transporation systems. The analyses and methodologies developed in this book provide Mechanisms that aid in determining and comparing congestion pricing schemes; Methodologies for evaluating the efficiency of existing and proposed congestion pricing schemes; A means to predict the impact of pricing on urban transporation systems; and Information essential to the financial and political success of congestion pricing programs.

img

Matematica generale con il calcolatore

By introducing mathematical objects, it teaches students how to use a computer to perform numerical and symbolic calculations, define a function and calculate its values, plot and explore graphs, and execute simple algorithms. The course is rich in examples, applications, and models, drawn from economics, physics, biology, statistics, and mathematics itself. The analysis of these models constitutes, in a certain sense, the true purpose of the mathematical theory covered. Automatic calculation tools (mathematics software, spreadsheets) are used extensively to explore and illustrate concepts and properties. Mathcad® software, in particular, was used, both as a calculation tool and as a simple yet powerful programming language. Considerable space is devoted to approximation, emphasizing the distinction between numerical and symbolic calculation; to algorithms as a synthesis of the syntactic and semantic aspects of mathematical objects; and to computer simulation, interpreted as a "physical" experiment and a source of conjecture. The ability to use a calculator marks a sort of "democratization" of mathematics: even complex results, which have always required a broad background of knowledge and laborious calculations, are now quickly accessible to anyone who understands the meaning of mathematical objects and knows how to use the syntax.

img

Masonry Constructions : Mechanical Models and Numerical Applications

This monograph firstly provides a detailed description of the constitutive equation of masonry-like materials, clearly setting out its most important features. It then goes on to provide a numerical procedure to solve the equilibrium problem of masonry solids.

img

Martingale Methods in Financial Modelling

This book provides a comprehensive, self-contained and up-to-date treatment of the main topics in the theory of option pricing. The first part of the text starts with discrete-time models of financial markets, including the Cox-Ross-Rubinstein binomial model. The passage from discrete- to continuous-time models, done in the Black-Scholes model setting, assumes familiarity with basic ideas and results from stochastic calculus. However, an Appendix containing all the necessary results is included. This model setting is later generalized to cover standard and exotic options involving several assets and/or currencies. An outline of the general theory of arbitrage pricing is presented. The second part of the text is devoted to the term structure modelling and the pricing of interest-rate derivatives. The main emphasis is on models that can be made consistent with market pricing practice.

img

Markov Decision Processes with Their Applications

Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters.

img

Markov Chains : Models, Algorithms and Applications

Markov chains are a particularly powerful and widely used tool for analyzing a variety of stochastic (probabilistic) systems over time. This monograph will present a series of Markov models, starting from the basic models and then building up to higher-order models. Included in the higher-order discussions are multivariate models, higher-order multivariate models, and higher-order hidden models. In each case, the focus is on the important kinds of applications that can be made with the class of models being considered in the current chapter. Special attention is given to numerical algorithms that can efficiently solve the models. Therefore, Markov Chains: Models, Algorithms and Applications outlines recent developments of Markov chain models for modeling queueing sequences, Internet, re-manufacturing systems, reverse logistics, inventory systems, bio-informatics, DNA sequences, genetic networks, data mining, and many other practical systems.

img

Marine Geochemistry

Since 1980 a considerable amount of scientific research dealing with geochemical processes in marine sediments has been carried out. This textbook summarizes the state of the art in this field of research. The topics comprise the examination of sedimentological and physical properties of the sedimentary solid phase, of pore water and pore water constituents, organic matter as the driving force of most microbiological processes, biotic and abiotic redox reactions, carbonates and stable isotopes as proxies for paleoclimate reconstruction, metal enrichments in ferromanganese nodules and crusts as well as in hot vents and cold seeps on the seafloor. A new chapter describes properties, occurrence and formation of gas hydrates in marine sediments. The textbook ends with a chapter on model conceptions and computer models to quantify processes of early diagenesis.

img

Marine carbon biogeochemistry : A primer for earth system scientists

This book discusses biogeochemical processes relevant to carbon and aims to provide with insight into the functioning of marine ecosystems. A carbon centric approach has been adopted, but other elements are included where relevant or needed. The book focuses on concepts and quantitative understanding of primary production, organic matter mineralization and sediment biogeochemistry. The impact of biogeochemical processes on inorganic carbon dynamics and organic matter transformation are also discussed.

img

Magnetism in the Solid State : An Introduction

Presents a phenomenological approach to the field of solid state magnetism. After introducing the basic concepts from statistical thermodynamics and electronic structure theory, the first part discusses the standard models for localized moments (Weiss, Heisenberg) and delocalized moments (Stoner). This is followed by a chapter about exchange and correlation in metals, again considering the results for the localized and delocalized limit. The book ends with a chapter about spin fluctuations, which are introduced as an alternative to the finite temperature Stoner theory. A useful reference work for researchers, this book will also be a valuable accompaniment to graduate courses on magnetism and magnetic materials.

img

Magnetic Control of Tokamak Plasmas

The main topic of Magnetic Control of Tokamak Plasmas is the design of feedback control systems guaranteeing the stability of plasma equilibrium inside a tokamak and the regulation of the plasma position and shape during plasma pulses. Modelling and control details are presented, allowing the non-expert to understand the control problem. Starting from equations of magneto-hydro-dynamics, all the steps needed for the derivation of plasma state-space models are enumerated. The basics of electromagnetics are frequently recalled. The control problem is then described beginning with control of current and position – vertical and radial – and progressing to the more challenging shape control. The solutions proposed vary from simple PIDs to more sophisticated MIMO controllers.

img

Low-Frequency Noise in Advanced MOS Devices

Low-Frequency Noise in Advanced CMOS Devices begins with an introduction to noise, describing the fundamental noise sources and basic circuit analysis. The characterization of low-frequency noise is discussed in detail and useful practical advice is given. The various theoretical and compact low-frequency (1/f) noise models in MOS transistors are treated extensively providing an in-depth understanding of the low-frequency noise mechanisms and the potential sources of the noise in MOS transistors. Advanced CMOS technology including nanometer scaled devices, strained Si, SiGe, SOI, high-k gate dielectrics, multiple gates and metal gates are discussed from a low-frequency noise point of view. Some of the most recent publications and conference presentations are included in order to give the very latest view on the topics. The book ends with an introduction to noise in analog/RF circuits and describes how the low-frequency noise can affect these circuits.

img

LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay

A fuzzy system is, in a very broad sense, any fuzzy logic-based system where fuzzy logic can be used either asthebasisfor the representation of different forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse fields of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem’s behavior and build useful mathematical models. Different types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems.

img

Linkage in Evolutionary Computation

The whole volume consisting of 19 chapters is divided into 3 parts: Models and Theories; Operators and Frameworks; Applications. This edited volume will serve as a useful guide and reference for researchers who are currently working in the area of linkage. For postgraduate research students, this volume will serve as a good source of reference. It is also suitable as a text for a graduate level course focusing on linkage issues.

img

Linearization Methods for Stochastic Dynamic Systems

The aim of this book is to give a systematic introduction to and overview of the relatively simple and popular linearization methods available. The scope is limited to models with continous external and parametric excitations, yet these cover the majority of known approaches. The book contains an application chapter with emphasis on vibration analysis of stochastic mechanical structures as well as a chapter devoted to the assessment of the accuracy of the theoretical methods presented, both with respect to numerical and to experimental studies.

img

Linear Optimization Problems with Inexact Data

Linear programming attracted the interest of mathematicians during and after World War II when the first computers were constructed and methods for solving large linear programming problems were sought in connection with specific practical problems—for example, providing logistical support for the U.S. Armed Forces or modeling national economies. Early attempts to apply linear programming methods to solve practical problems failed to satisfy expectations. There were various reasons for the failure. One of them, which is the central topic of this book, was the inexactness of the data used to create the models. This phenomenon, inherent in most pratical problems, has been dealt with in several ways. At first, linear programming models used "average” values of inherently vague coefficients, but the optimal solutions of these models were not always optimal for the original problem itself. Later researchers developed the stochastic linear programming approach, but this too has its limitations. Recently, interest has been given to linear programming problems with data given as intervals, convex sets and/or fuzzy sets. The individual results of these studies have been promising, but the literature has not presented a unified theory. Linear Optimization Problems with Inexact Data attempts to present a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.

img

Linear Models for Optimal Test Design

Begins with a reflection on the history of test design--the core activity of all educational and psychological testing. It then presents a standard language for modeling test design problems as instances of multi-objective constrained optimization. The main portion of the book discusses test design models for a large variety of problems from the daily practice of testing, and illustrates their use with the help of numerous empirical examples. The presentation includes models for the assembly of tests to an absolute or relative target for their information functions, classical test assembly, test equating problems, item matching, test splitting, simultaneous assembly of multiple tests, tests with item sets, multidimensional tests, and adaptive test assembly. Two separate chapters are devoted to the questions of how to design item banks for optimal support of programs with fixed and adaptive tests. Linear Models for Optimal Test Design, which does not require any specific mathematical background, has been written to be a helpful resource on the desk of any test specialist.

img

Linear Models and Generalizations : Least Squares and Alternatives

Gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results aboutthe de?niteness ofmatrices,especially forthe di?erences ofmatrices, which enable superiority comparisons of two biased estimates to be made for the ?rst time. We have attempted to provide a uni?ed theory of inference from linear models with minimal assumptions

img

Linear and Generalized Linear Mixed Models and Their Applications

This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models.

img

Lewis Fry Richardson : His Intellectual Legacy and Influence in the Social Sciences

A pioneer in meteorology and peace research and remains a towering presence in both fields. This edited volume reviews his work and assesses its influence in the social sciences, notably his work on arms races and their consequences, mathematical models, the size distribution of wars, and geographical features of conflict

img

Level Crossing Methods in Stochastic Models

Since its inception in 1974, the level crossing approach for analyzing a large class of stochastic models has become increasingly popular among researchers. This volume traces the evolution of level crossing theory for obtaining probability distributions of state variables and demonstrates solution methods in a variety of stochastic models including: queues, inventories, dams, renewal models, counter models, pharmacokinetics, and the natural sciences. Results for both steady-state and transient distributions are given, and numerous examples help the reader apply the method to solve problems faster, more easily, and more intuitively.

عدد النتائج بكل صفحة