|
Showing 1 - 4 of
4 matches in All Departments
This volume is a collection of research surveys on the Distance
Geometry Problem (DGP) and its applications. It will be divided
into three parts: Theory, Methods and Applications. Each part will
contain at least one survey and several research papers. The first
part, Theory, will deal with theoretical aspects of the DGP,
including a new class of problems and the study of its complexities
as well as the relation between DGP and other related topics, such
as: distance matrix theory, Euclidean distance matrix completion
problem, multispherical structure of distance matrices, distance
geometry and geometric algebra, algebraic distance geometry theory,
visualization of K-dimensional structures in the plane, graph
rigidity, and theory of discretizable DGP: symmetry and complexity.
The second part, Methods, will discuss mathematical and
computational properties of methods developed to the problems
considered in the first chapter including continuous methods (based
on Gaussian and hyperbolic smoothing, difference of convex
functions, semidefinite programming, branch-and-bound), discrete
methods (based on branch-and-prune, geometric build-up, graph
rigidity), and also heuristics methods (based on simulated
annealing, genetic algorithms, tabu search, variable neighborhood
search). Applications will comprise the third part and will
consider applications of DGP to NMR structure calculation, rational
drug design, molecular dynamics simulations, graph drawing and
sensor network localization. This volume will be the first edited
book on distance geometry and applications. The editors are in
correspondence with the major contributors to the field of distance
geometry, including important research centers in molecular biology
such as Institut Pasteur in Paris.
This volume is a collection of research surveys on the Distance
Geometry Problem (DGP) and its applications. It will be divided
into three parts: Theory, Methods and Applications. Each part will
contain at least one survey and several research papers. The first
part, Theory, will deal with theoretical aspects of the DGP,
including a new class of problems and the study of its complexities
as well as the relation between DGP and other related topics, such
as: distance matrix theory, Euclidean distance matrix completion
problem, multispherical structure of distance matrices, distance
geometry and geometric algebra, algebraic distance geometry theory,
visualization of K-dimensional structures in the plane, graph
rigidity, and theory of discretizable DGP: symmetry and complexity.
The second part, Methods, will discuss mathematical and
computational properties of methods developed to the problems
considered in the first chapter including continuous methods (based
on Gaussian and hyperbolic smoothing, difference of convex
functions, semidefinite programming, branch-and-bound), discrete
methods (based on branch-and-prune, geometric build-up, graph
rigidity), and also heuristics methods (based on simulated
annealing, genetic algorithms, tabu search, variable neighborhood
search). Applications will comprise the third part and will
consider applications of DGP to NMR structure calculation, rational
drug design, molecular dynamics simulations, graph drawing and
sensor network localization. This volume will be the first edited
book on distance geometry and applications. The editors are in
correspondence with the major contributors to the field of distance
geometry, including important research centers in molecular biology
such as Institut Pasteur in Paris.
Data Mining in Agriculture represents a comprehensive effort to
provide graduate students and researchers with an analytical text
on data mining techniques applied to agriculture and environmental
related fields. This book presents both theoretical and practical
insights with a focus on presenting the context of each data mining
technique rather intuitively with ample concrete examples
represented graphically and with algorithms written in
MATLAB(r).
Data Mining in Agriculture represents a comprehensive effort to
provide graduate students and researchers with an analytical text
on data mining techniques applied to agriculture and environmental
related fields. This book presents both theoretical and practical
insights with a focus on presenting the context of each data mining
technique rather intuitively with ample concrete examples
represented graphically and with algorithms written in Matlab(r).
Examples and exercises with solutions are provided at the end of
each chapter to facilitate the comprehension of the material. For
each data mining technique described in the book variants and
improvements of the basic algorithm are also given.
|
|