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Author: Christopher V. Jones Publisher: Springer Science & Business Media ISBN: 1461541212 Category : Business & Economics Languages : en Pages : 436
Book Description
This book arose out of an invited feature article on visualization and opti mization that appeared in the ORSA Journal on Computing in 1994. That article briefly surveyed the current state of the art in visualization as it ap plied to optimization. In writing the feature article, it became clear that there was much more to say. Apparently others agreed, and thus this book was born. The book is targeted primarily towards the optimization community rather than the visualization community. Although both optimization and visualization both seek to help people understand complex problems, prac titioners in one field are generally unaware of work in the other field. Given the common goals of the respective fields, it seemed fruitful to consider how each can contribute to the other. One might argue that this book should not be focused specifically on optimization but on decision making in general. Perhaps, but it seems that there is sufficient material to create a book targeted specifically to optimization. Certainly many of the ideas presented in the book are appli cable to other areas, including computer simulation, decision theory and stochastic modeling. Another book could discuss the use of visualization in these areas.
Author: Christopher V. Jones Publisher: Springer Science & Business Media ISBN: 1461541212 Category : Business & Economics Languages : en Pages : 436
Book Description
This book arose out of an invited feature article on visualization and opti mization that appeared in the ORSA Journal on Computing in 1994. That article briefly surveyed the current state of the art in visualization as it ap plied to optimization. In writing the feature article, it became clear that there was much more to say. Apparently others agreed, and thus this book was born. The book is targeted primarily towards the optimization community rather than the visualization community. Although both optimization and visualization both seek to help people understand complex problems, prac titioners in one field are generally unaware of work in the other field. Given the common goals of the respective fields, it seemed fruitful to consider how each can contribute to the other. One might argue that this book should not be focused specifically on optimization but on decision making in general. Perhaps, but it seems that there is sufficient material to create a book targeted specifically to optimization. Certainly many of the ideas presented in the book are appli cable to other areas, including computer simulation, decision theory and stochastic modeling. Another book could discuss the use of visualization in these areas.
Author: Gintautas Dzemyda Publisher: Springer Science & Business Media ISBN: 1441902368 Category : Mathematics Languages : en Pages : 262
Book Description
This book highlights recent developments in multidimensional data visualization, presenting both new methods and modifications on classic techniques. Throughout the book, various applications of multidimensional data visualization are presented including its uses in social sciences (economy, education, politics, psychology), environmetrics, and medicine (ophthalmology, sport medicine, pharmacology, sleep medicine). The book provides recent research results in optimization-based visualization. Evolutionary algorithms and a two-level optimization method, based on combinatorial optimization and quadratic programming, are analyzed in detail. The performance of these algorithms and the development of parallel versions are discussed. The utilization of new visualization techniques to improve the capabilies of artificial neural networks (self-organizing maps, feed-forward networks) is also discussed. The book includes over 100 detailed images presenting examples of the many different visualization techniques that the book presents. This book is intended for scientists and researchers in any field of study where complex and multidimensional data must be represented visually.
Author: Dean Vucinic Publisher: Springer Nature ISBN: 9811398062 Category : Technology & Engineering Languages : en Pages : 356
Book Description
This volume presents several multidisciplinary approaches to the visual representation of data acquired from experiments. As an expansion of these approaches, it is also possible to include data examination generated by mathematical-physical modeling. Imaging Systems encompass any subject related to digital images, from fundamental requirements for a correct image acquisition to computational algorithms that make it possible to obtain relevant information for image analysis. In this context, the book presents selected contributions of a special session at the Conference on Advanced Computational Engineering and Experimenting (ACE-X) 2016.
Author: Pranav Ramkrishnan Publisher: ISBN: Category : Languages : en Pages : 83
Book Description
In the first part of this thesis, I present a portfolio of web-based visualizations that illustrate different data-driven ideas about urban environments. These visualizations are intended to provide the user with unique perspectives about cities and the way they function. I detail the conceptualization, data aspects, and implementation of each of these map visualizations. In the second part of this thesis, I describe an interesting optimization problem of placing entities such as trees or shops within a city. The location of these placements needs to conform to certain constraints enforced by spatial distributions of variables such as population, income, travel times, etc. I then present a heuristic-based optimization strategy, that combines some aspects of Gradient-ascent and Simulated Annealing, to address this problem and attempt to generalize this approach to finding the optimal placements of any entity within a given city. I present some initial results of my optimization algorithm and discuss ways in which it can be further improved.
Author: Alexander V. Lotov Publisher: Springer Science & Business Media ISBN: 1441988513 Category : Mathematics Languages : en Pages : 324
Book Description
Since the volume may be of interest to a broad variety of people, it is arranged in parts that require different levels of mathematical background. Part I can be assessed by those interested in the application of visualization methods in decision making. In Part II computational methods are introduced in a relatively simple form. Part III is written for readers in applied mathematics interested in the theoretical basis of modern optimization.
Author: E. Wes Bethel Publisher: CRC Press ISBN: 1439875731 Category : Computers Languages : en Pages : 520
Book Description
Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms. High Performance Visualization: Enabling Extreme-Scale Scientific Insight focuses on the subset of scientifi
Author: Jonas Mockus Publisher: Springer Science & Business Media ISBN: 1475726279 Category : Mathematics Languages : en Pages : 394
Book Description
Bayesian decision theory is known to provide an effective framework for the practical solution of discrete and nonconvex optimization problems. This book is the first to demonstrate that this framework is also well suited for the exploitation of heuristic methods in the solution of such problems, especially those of large scale for which exact optimization approaches can be prohibitively costly. The book covers all aspects ranging from the formal presentation of the Bayesian Approach, to its extension to the Bayesian Heuristic Strategy, and its utilization within the informal, interactive Dynamic Visualization strategy. The developed framework is applied in forecasting, in neural network optimization, and in a large number of discrete and continuous optimization problems. Specific application areas which are discussed include scheduling and visualization problems in chemical engineering, manufacturing process control, and epidemiology. Computational results and comparisons with a broad range of test examples are presented. The software required for implementation of the Bayesian Heuristic Approach is included. Although some knowledge of mathematical statistics is necessary in order to fathom the theoretical aspects of the development, no specialized mathematical knowledge is required to understand the application of the approach or to utilize the software which is provided. Audience: The book is of interest to both researchers in operations research, systems engineering, and optimization methods, as well as applications specialists concerned with the solution of large scale discrete and/or nonconvex optimization problems in a broad range of engineering and technological fields. It may be used as supplementary material for graduate level courses.
Author: Christopher V. Jones
Author: Christopher V. Jones
Author: Gintautas Dzemyda
Author: Dean Vucinic
Author: 
Author: Pranav Ramkrishnan
Author: Martin G. Wolkenstein
Author: Alexander V. Lotov
Author: E. Wes Bethel
Author: Rongjian Lai
Author: Jonas Mockus