Network Optimization: An Introduction to the Network Reconstruction Approach: Network Reconstruction Approach to optimization. Elias Munapo, Santosh Kumar, Philimon Nyamugure, Trust Tawanda

Network Optimization: An Introduction to the Network Reconstruction Approach: Network Reconstruction Approach to optimization

Network-Optimization-An.pdf
ISBN: 9788770047425 | 236 pages | 6 Mb

Network Optimization: An Introduction to the Network Reconstruction Approach: Network Reconstruction Approach to optimization
Elias Munapo, Santosh Kumar, Philimon Nyamugure, Trust Tawanda
Page: 236
Format: pdf, ePub, fb2, mobi
ISBN: 9788770047425
Publisher: River Publishers

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For every problem, mathematical or otherwise, there is more than one approach and much depends on the ingenuity of the person concerned. Consider that a person is interested in picking some fruit from a tree and is considering multiple picking options. One possibility is, if one can reach the fruit, just snip it to retrieve it. The second possibility is to alternatively apply force and detach the fruit from the tree. If neither option is possible, the fruit can still be detached from the tree, but how? A third possibility lies in the fact that just holding on to the fruit and turning it in one direction it can be picked. Similarly, many possibilities are seen by keen eyes while solving a mathematical problem. The reconstruction approach applied in this book is like the third possibility of holding a fruit and turning it in one direction until the desired solution is obtained. This book is an introduction to reconstruction concepts and their applications for solving some network optimization problems. Networks are a mathematical abstraction of a given physical situation, which are described by using nodes, links (directed or non-directed) and link weights defining some associated properties of that physical system. Reconstruction ideas exploit the mathematical structure of a particular problem and find ways to reach the required solution. It is hoped that these ideas will be explored for other mathematical structures. The authors have developed many methods to find optimal solutions for these network related problems and they observed that various methods discussed in 8 chapters have a common thread of reconstruction, which unites them, and that aspect motivated authors to develop this book.

An Introduction to the Network Reconstruction Approach (eBook .
This book is an introduction to reconstruction concepts and its applications for solving some network optimization problems. The authors have developed many .
StabJGL: a stability approach to sparsity and similarity selection in .
We compare the network reconstruction ability of stabJGL to that of state-of-the-art methods, including the JGL with the fused penalty (FGL) and group penalty ( .
A machine learning and directed network optimization approach to .
Introduction. Regulation of gene expression is critical to a diverse . Optimization/reconstruction of networks. CARNIVAL uses Mixed .
[PDF] A Passivity and Network Optimization Approach - arXiv
INTRODUCTION. Multi-agent systems have been widely studied . We now present the network reconstruction scheme based on indication vectors.
Network Reconstruction Approach to optimization - 三民網路書店
書名：Network Optimization: An Introduction to the Network Reconstruction Approach：Network Reconstruction Approach to optimization，ISBN：9788770047425， .
[PDF] Statistical and Machine Learning Approaches for Network Analysis.pdf
Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations .
Networks: Foundations in Probability, Optimization and Data Sciences
algorithmic approaches to detection and reconstruction, resource allocation, and computational questions on networks (using tools from applied probability .

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