تحسين النتائح
ترتيب حسب
من
الى
الصفحة 2
الصفحة 2
Logic, Thought and Action
Contribute to our understanding of this dynamic process by clearly presenting and discussing the most important hypotheses, issues and theories in philosophical and logical study of language, thought and action. Among the fundamental issues discussed are the rationality and freedom of agents, theoretical and practical reasoning, individual and collective attitudes and actions, the nature of cooperation and communication, the construction and conditions of adequacy of scientific theories, propositional contents and their truth conditions, illocutionary force, time, aspect and presupposition in meaning, speech acts within dialogue, the dialogical approach to logic and the structure of dialogues and other language games, as well as formal methods needed in logic or artificial intelligence to account for choice, paradoxes, uncertainty and imprecision.
Iterative Learning Control : Robustness and Monotonic Convergence for Interval Systems
This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. Two key problems with the fundamentals of iterative learning control (ILC) design as treated by existing work are: first, many ILC design strategies assume nominal knowledge of the system to be controlled and; second, it is well-known that many ILC algorithms do not produce monotonic convergence, though in applications monotonic convergence is often essential. Iterative Learning Control takes account of the recently-developed comprehensive approach to robust ILC analysis and design established to handle the situation where the plant model is uncertain. Considering ILC in the iteration domain, it presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty.
Complex decision making : Theory and practice
The increasingly complex environment of today's world, characterized by technological innovation and global communication, generates myriads of possible and actual interactions while limited physical and intellectual resources severely impinge on decision makers, be it in the public or private domains. At the core of the decision-making process is the need for quality information that allows the decision maker to better assess the impact of decisions in terms of outcomes, nonlinear feedback processes and time delays on the performance of the complex system invoked.
Classification and Clustering for Knowledge Discovery
This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. In its first part the book provides a collection of recent research on distributed clustering, self organizing maps and their recent extensions. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees. Therefore this book presents a collection of important methods of supervised data analysis. "Classification and Clustering for Knowledge Discovery" also includes variety of applications of knowledge discovery in health, safety, commerce, mechatronics, sensor networks, and telecommunications.
Classic Works on the Dempster-Shafer Theory of Belief Functions
This book brings together a collection of classic research papers on the Dempster-Shafer theory of belief functions. By bridging fuzzy logic and probabilistic reasoning, the theory of belief functions has become a primary tool for knowledge representation and uncertainty reasoning in expert systems.
Childlessness in Europe : Contexts, Causes, and Consequences
This open access book provides an overview of childlessness throughout Europe. It offers a collection of papers written by leading demographers and sociologists that examine contexts, causes, and consequences of childlessness in countries throughout the region.The book features data from all over Europe. It specifically highlights patterns of childlessness in Germany, France, the United Kingdom, Finland, Sweden, Austria and Switzerland. An additional chapter on childlessness in the United States puts the European experience in perspective.
Chemical Youth : Navigating Uncertainty in Search of the Good Life
This book explores how young people engage with chemical substances in their everyday lives. It builds upon and supplements a large body of literature on young people’s use of drugs and alcohol to highlight the subjectivities and socialities that chemical use enables across diverse socio-cultural settings, illustrating how young people seek to avoid harm, while harnessing the beneficial effects of chemical use.
Chance Discoveries in Real World Decision Making : Data-based Interaction of Human intelligence and Artificial Intelligence
For this book, the editors invited and called for contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000. From respective research areas as artificial intelligence, mathematics, cognitive science, medical science, risk management, methodologies for design and communication, the invited and selected authors in this book present their particular approaches to chance discovery. The chapters here show contributions to identifying rare or hidden events and explaining their significance, predicting future trends, communications for scenario development in marketing and design, identification effects and side-effects of medicines, etc.
Catalogue of risks : Natural, technical, social and health risks
The book clearly shows the interdependence of risk measures. Safety and risks cannot be discussed only by looking at specific problems, since increasing safety in individual fields might lead to a decrease of safety over the entire society.
Branch-and-Bound Applications in Combinatorial Data Analysis
There are a variety of combinatorial optimization problems that are relevant to the examination of statistical data. Combinatorial problems arise in the clustering of a collection of objects, the seriation (sequencing or ordering) of objects, and the selection of variables for subsequent multivariate statistical analysis such as regression. The options for choosing a solution strategy in combinatorial data analysis can be overwhelming. Because some problems are too large or intractable for an optimal solution strategy, many researchers develop an over-reliance on heuristic methods to solve all combinatorial problems. However, with increasingly accessible computer power and ever-improving methodologies, optimal solution strategies have gained popularity for their ability to reduce unnecessary uncertainty. In this monograph, optimality is attained for nontrivially sized problems via the branch-and-bound paradigm.
Bioeconomic modelling and valuation of exploited marine ecosystems
This book offers an environmental-economic analysis of exploited ecosystems with a clear policy orientation. The study tries to move beyond traditional economic fishery analysis in two respects. First, several theoretical and numerical models are offered that combine economic and ecological descriptions of fisheries. These models give special attention to spatial processes as well as to combining exploitation and conservation objectives. Second, valuation and stakeholder concerns are addressed in empirical analyses employing both qualitative and quantitative approaches. The latter is done by using advanced methods of monetary valuation. In addition, the first part of the book presents short, introductory overviews of integrated assessment, economic modeling of fishery management, and incorporating uncertainty in fisheries analysis.
Average-Cost Control of Stochastic Manufacturing Systems
This book is concerned with hierarchical control of manufacturing systems under uncertainty. It focuses on system performance measured in long-run average cost criteria, exploring the relationship between control problems with a discounted cost and that with a long-run average cost in connection with hierarchical control. A new theory is articulated that shows that hierarchical decision making in the context of a goal-seeking manufacturing system can lead to a near optimization of its objective. The approach in the book considers manufacturing systems in which events occur at different time scales.
Autonomous Navigation in Dynamic Environments
The purpose of this book is to address the challenging problem of Autonomous Navigation in Dynamic Environments, and to present new ideas and approaches in this newly emerging technical domain. The book surveys the state-of-the-art, discusses in detail various related challenging technical aspects, and addresses upcoming technologies in this field. The aim of the book is to establish a foundation for a broad class of mobile robot mapping and navigation methodologies for indoor, outdoor, and exploratory missions.Three main topics located on the cutting edge of the state of the art are addressed, from both the theoretical and technological point of views: Dynamic world understanding and modelling for safe navigation, Obstacle avoidance and motion planning in dynamic environments, and Human-robot physical interactions. Several models and approaches are proposed for solving problems such as Simultaneous Localization and Mapping (SLAM) in dynamic environments, Mobile obstacle detection and tracking, World state estimation and motion prediction, Safe navigation in dynamic environments, Motion planning in dynamic environments, Robust decision making under uncertainty, and Human-Robot physical interactions.
Automatic Differentiation : Applications, Theory, and Implementations
This collection covers the state of the art in automatic differentiation theory and practice. Practitioners and students will learn about advances in automatic differentiation techniques and strategies for the implementation of robust and powerful tools. Computational scientists and engineers will benefit from the discussion of applications, which provide insight into effective strategies for using automatic differentiation for design optimization, sensitivity analysis, and uncertainty quantification.
Assessment and future directions of nonlinear model predictive control
Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods must be employed. This is one of the reasons why nonlinear model predictive control (NMPC) has - joyed signi?cant attention over the past years,with a number of recent advances on both the theoretical and application frontier. Additionally, the widespread availability and steadily increasing power of today’s computers, as well as the development of specially tailored numerical solution methods for NMPC, bring thepracticalapplicabilityofNMPCwithinreachevenforveryfastsystems.This has led to a series of new, exciting developments, along with new challenges in the area of NMPC.
Analyzing uncertainty in civil engineering
This volume addresses the issue of uncertainty in civil engineering from design to construction. Failures do occur in practice. Attributing them to a residual system risk or a faulty execution of the project does not properly cover the range of causes. A closer scrutiny of the adopted design, the engineering model, the data, the soil-construction-interaction and the model assumptions is required. Usually, the uncertainties in initial and boundary conditions are abundant. Current engineering practice often leaves these issues aside, despite the fact that new scientific tools have been developed in the past decades that allow a rational description of uncertainties of all kinds, from model uncertainty to data uncertainty. It is the aim of this volume to have a critical look at current engineering risk concepts in order to raise awareness of uncertainty in numerical computations, shortcomings of a strictly probabilistic safety concept, geotechnical models of failure mechanisms and their implications for construction management, execution, and the juristic question of responsibility. In addition, a number of the new procedures for modelling uncertainty are explained.
Advances in Variable Structure and Sliding Mode Control
Sliding Mode Control is recognized as an efficient tool to design controllers which are robust with respect to uncertainty. The resulting controllers have low sensitivity to plant parameters and perturbations and allow the possibility of decoupling the original plant system into two components of lower dimension. In addition many controllers ensure finite time convergence to the switching surface and can be straightforwardly implemented. However, in addition to this traditional area of exploitation, sliding mode concepts are being increasingly deployed for the design of observers for estimation and identification.
Advances in Unmanned Aerial Vehicles : State of the Art and the Road to Autonomy
There has been tremendous emphasis in unmanned aerial vehicles, both of fixed (airplanes) and rotary wing (vertical take off and landing, helicopters) types over the past ten years. Applications span both civilian and military domains, the latter being the most important at this stage. This edited book provides a solid and diversified reference source related to basic, applied research and development on small and miniature unmanned aerial vehicles, both fixed and rotary wing. As such, the book offers background information on the evolution of such vehicles over the years, followed by modeling and control fundamentals that are of paramount importance due to unmanned aerial vehicle model complexity, nonlinearity, coupling, inhirent instability and parameter values uncertainty. Aspects of navigation, including visual-based navigation and target tracking are discussed, followed by applications to attitude estimation on micro unmanned aerial vehicles, autonomous solar unmanned aerial vehicle, biomimetic sensing for autonomous flights in near-earth environments, localization of air-ground wireless sensor networks, decentralized formation tracking, design of an unmanned aerial vehicle for volcanic gas sampling and design of an on-board processing controller for miniature helicopters.
Advances in Probabilistic Graphical Models
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
Advances in Digital Terrain Analysis
Terrain analysis has been an active study field for years and attracted research studies from geographers, surveyors, engineers and computer scientists. With the rapid growth of Geographical Information System (GIS) technology, particularly the establishment of high resolution Digital Elevation Models (DEM) at national level, the challenge is now focused on delivering justifiable socio-economical and environmental benefits. The contributions in this book represent the state of the art of terrain analysis methods and techniques in areas of digital representation, morphological and hydrological models, uncertainty and applications of terrain analysis.
