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الصفحة 7
الصفحة 7
Bio-inspired credit risk analysis : Computational intelligence with support vector machines
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
Artificial markets modeling : Methods and applications
Agent-based computational modeling with its intrinsic multidisciplinary approach is gaining increasing recognition in the social sciences, particularly in economics, business and finance. This volume is devoted to recent contributions to the field from both the social sciences and computer sciences.
Artificial economics : Agent-based methods in finance, game theory and their applications
The purpose of this book is to give an up-to date view of the scientific production in the fields of Agent-based Computational Economics (mainly in Market Finance and Game Theory). Based on communications given at AE'2005 (Lille, USTL, France), this book offers a wide panorama of recent advances in ACE (both theoretical and methodological) that will interest academics as well as practitioners.
Applications of simulation methods in environmental and resource economics
Simulation methods are revolutionizing the practice of applied economic analysis. This volume collects eighteen chapters written by leading researchers from prestigious research institutions the world over. The common denominator of the papers is their relevance for applied research in environmental and resource economics. The topics range from discrete choice modeling with heterogeneity of preferences, to Bayesian estimation, to Monte Carlo experiments, to structural estimation of Kuhn-Tucker demand systems, to evaluation of simulation noise in maximum simulated likelihood estimates, to dynamic natural resource modeling. Empirical cases are used to show the practical use and the results brought forth by the different methods.
Applications of computational intelligence in data-driven trading
The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry.
Agent-based computational modelling : Applications in demography, social, economic and environmental sciences
The present book describes the methodology to set up agent-based models and to study emerging patterns in complex adaptive systems resulting from multi-agent interaction. It offers the application of agent-based models in demography, social and economic sciences and environmental sciences. It presents and combines different approaches how to implement agent-based computational models and tools in an integrative manner that can be extended to other cases.
Advanced REIT Portfolio Optimization : Innovative Tools for Risk Management
This book provides an investor-friendly presentation of the premises and applications of the quantitative finance models governing investment in one asset class of publicly traded stocks, specifically real estate investment trusts (REITs). The models provide highly advanced analytics for REIT investment, including: portfolio optimization using both historic and predictive return estimation; model backtesting; a complete spectrum of risk assessment and management tools with an emphasis on early warning systems, risk budgeting, estimating tail risk, and factor analysis; derivative valuation; and incorporating ESG ratings into REIT investment.
Landscape Performance Modeling Using Rhino and Grasshopper
A guidebook for landscape architects to learn the fundamental practices and use of the computational software Rhino 3D and the plugin Grasshopper for parametric modeling, landscape inventory, and performative analysis. This process visually connects intangible and abstract information with physical and spatial relationships to signify the impact ecological, climate, and cultural factors have on landscape performance and decision making.
Architectonics and parametric thinking : computational modeling for beginning design
Architectonics and Parametric Thinking begins by clearly positioning the potentials of parametric design through a series of chapters written by leaders in their respective industries. This helps to situate the vast potential of parametric softwares, allowing the reader to understand the full range of what is made possible by working computationally. Following this theoretical introduction, the book presents a manual that walks readers through the step-by-step construction of parametric modeling scripts built through an architectonic lens using clear, compelling diagrams.
Architecture and design for industry 4.0 : Theory and practice
The book is structured into three sections (research, practice, and technologies), with the goal of creating a new framework useful for widespread awareness necessary to initiate technology transfer processes for the benefit of the public sector, universities, research centers, and innovative companies, and a new professional figure capable of controlling the entire process is essential. Thus, the book chapters arouse a series of relevant topics such as computational and parametric design, performance-based architecture, data-driven design strategies, parametric environmental design and analysis, computational and parametric structural design and analysis
Mathematical Models for Registration and Applications to Medical Imaging
Image registration is an emerging topic in image processing with many applications in medical imaging, picture and movie processing. The classical problem of image registration is concerned with ?nding an appropriate transformation between two data sets. This fuzzy de?nition of registration requires a mathematical modeling and in particular a mathematical speci?cation of the terms appropriate transformations and correlation between data sets. Depending on the type of application, typically Euler, rigid, plastic, elastic deformations are considered. The variety of similarity p measures ranges from a simpleL distance between the pixel values of the data to mutual information or entropy distances. This goal of this book is to highlight by some experts in industry and medicine relevant and emerging image registration applications and to show new emerging mathematical technologies in these areas. Currently, many registration application are solved based on variational prin- ple requiring sophisticated analysis, such as calculus of variations and the theory of partial differential equations, to name but a few. Due to the numerical compl- ity of registration problems ef?cient numerical realization are required. Concepts like multi-level solver for partial differential equations, non-convex optimization, and so on play an important role. Mathematical and numerical issues in the area of registration are discussed by some of the experts in this volume.
Mathematical Modeling of Complex Biological Systems : A Kinetic Theory Approach
This book describes the evolution of several socio-biological systems using mathematical kinetic theory. Specifically, it deals with modeling and simulations of biological systems—comprised of large populations of interacting cells—whose dynamics follow the rules of mechanics as well as rules governed by their own ability to organize movement and biological functions. The authors propose a new biological model for the analysis of competition between cells of an aggressive host and cells of a corresponding immune system.Because the microscopic description of a biological system is far more complex than that of a physical system of inert matter, a higher level of analysis is needed to deal with such complexity. Mathematical models using kinetic theory may represent a way to deal with such complexity, allowing for an understanding of phenomena of nonequilibrium statistical mechanics not described by the traditional macroscopic approach. The proposed models are related to the generalized Boltzmann equation and describe the population dynamics of several interacting elements (kinetic population models).The particular models proposed by the authors are based on a framework related to a system of integro-differential equations, defining the evolution of the distribution function over the microscopic state of each element in a given system. Macroscopic information on the behavior of the system is obtained from suitable moments of the distribution function over the microscopic states of the elements involved. The book follows a classical research approach applied to modeling real systems, linking the observation of biological phenomena, collection of experimental data, modeling, and computational simulations to validate the proposed models. Qualitative analysis techniques are used to identify the prediction ability of specific models.
Mathematical Modeling of Biological Systems ; Vol. II : Epidemiology, Evolution and Ecology,Immunology, Neural Systems and the Brain, and Innovative Mathematical Methods
This two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout both works are mathematical and computational approaches to examine central problems in the life sciences, ranging from the organizational principles of individual cells to the dynamics of large populations.
Mathematical Modeling of Biological Systems ; Vol. I : Cellular Biophysics, Regulatory Networks, Development, Biomedicine, and Data Analysis
This two-volume, interdisciplinary work is a unified presentation of a broad range of state-of-the-art topics in the rapidly growing field of mathematical modeling in the biological sciences. Highlighted throughout both works are mathematical and computational approaches to examine central problems in the life sciences, ranging from the organizational principles of individual cells to the dynamics of large populations.
Mathematical Methods for Engineers and Geoscientists
This book introduces and explains classical and modern mathematical procedures as applied to the real problems confronting engineers and geoscientists. Written in a manner that is understandable for students across the breadth of their studies, it lays out the foundations for mastering difficult and sometimes confusing mathematical methods.
Mathematical Control Theory and Finance
This book highlights recent developments in mathematical control theory and its applications to finance. It presents a collection of original contributions by distinguished scholars, addressing a large spectrum of problems and techniques. Control theory provides a large set of theoretical and computational tools with applications in a wide range of fields, ranging from "pure" areas of mathematics up to applied sciences like finance. Stochastic optimal control is a well established and important tool of mathematical finance. Other branches of control theory have found comparatively less applications to financial problems, but the exchange of ideas and methods has intensified in recent years. This volume should contribute to establish bridges between these separate fields. The diversity of topics covered as well as the large array of techniques and ideas brought in to obtain the results make this volume a valuable resource for advanced students and researchers.
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.
Manipulating Quantum Coherence in Solid State Systems
Presents a fundamental introduction to three solid-state approaches to achieving quantum computation: semiconductor spin-based, semiconductor charge-based, and superconducting approaches.
Logical Foundations for Rule-Based Systems
Presents logical foundations for rule-based systems, as seen by the Author. An attempt has been made to provide an in-depth discussion of logical and other aspects of such systems, including languages for knowledge representation, inference mechanisms, inference control, design and verification.
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.
