This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters most and suggests pathways for minimizing the risk in strategic and...
Modeling problems in this book are addressed mainly from the computational viewpoint. The primary concerns are how to define an objective function for the optimal solution to a image analysis or computer vision problem and how to find the optimal solution. The solution is defined in an optimization sense because the perfect solution is...
Explains for the first time how "computing with words" can aidin making subjective judgments
Lotfi Zadeh, the father of fuzzy logic, coined the phrase"computing with words" (CWW) to describe a methodology in which theobjects of computation are words and propositions drawn from anatural language....
Policy-makers and the public, it has famously been said, are more interested in the possibility of non-linear dislocations and surprises in the behaviour of the environment than in smooth extrapolations of current trends. The International Task Force in Forecasting Environmental Change (1993-1998) dedicated its work to developing procedures...
The book that looks at mercury's impact on the planet today
Recent research by the EPA has concluded that one in six women of childbearing age have unsafe levels of mercury in their bodies, which puts 630,000 newborn babies each year at risk of neurological impairment. Mercury poses severe risks to the health of animals and...
This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering systems is inevitable. Representative methods for...
This book advocates a fresh approach to planning that anticipates, rather than reacts to, the changes in climate currently in process. Today’s spatial planning procedures rely on historical evidence instead of preparing for factors that by definition lie in the future, yet which are relatively uncontroversial: shortages of water, sea...
Surfaces are a central to geographical analysis. Their generation and manipulation are a key component of geographical information systems (GISs). However, geographical surface data is often not precise. When surfaces are used to model geographical entities, the data inherently contains uncertainty in terms of both position and attribute....
Optimization of adaptive signal processing algorithms for wireless communications is based on a model of the underlying propagation channel. In practice, this model is never known perfectly. For example, its parameters have to be estimated and are only known with significant errors.
In this book, a systematic treatment of this practical design...
The World Wide Web is growing in size at a remarkable rate. It is a huge evolving system and its data are rife with uncertainties. Probability and statistics are the fundamental mathematical tools that enable us to model, reason and infer meaningful results from such data. Modelling the Internet and the Web covers the...
Reliability-based design is the only engineering methodology currently available which can ensure self-consistency in both physical and probabilistic terms. It is also uniquely compatible with the theoretical basis underlying other disciplines such as structural design. It is especially relevant as geotechnical design becomes subject to...
This monograph covers theoretical aspects of simultaneous localization and map building for mobile robots, such as estimation stability, nonlinear models for the propagation of uncertainties, temporal landmark compatibility, as well as issues pertaining the coupling of control and SLAM. One of the most relevant topics covered in this monograph is...
