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Graphs As Structural Models


Graphs As Structural Models
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Graphs As Structural Models


Graphs As Structural Models
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Author : Erhard Godehardt
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Graphs As Structural Models written by Erhard Godehardt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.


The advent of the high-speed computer with its enormous storage capabilities enabled statisticians as well as researchers from the different topics of life sciences to apply mul tivariate statistical procedures to large data sets to explore their structures. More and more, methods of graphical representation and data analysis are used for investigations. These methods belong to a topic of growing popUlarity, known as "exploratory data analysis" or EDA. In many applications, there is reason to believe that a set of objects can be clus tered into subgroups that differ in meaningful ways. Extensive data sets, for example, are stored in clinical cancer registers. In large data sets like these, nobody would ex pect the objects to be homogeneous. The most commonly used terms for the class of procedures that seek to separate the component data into groups are "cluster analysis" or "numerical taxonomy". The origins of cluster analysis can be found in biology and anthropology at the beginning of the century. The first systematic investigations in cluster analysis are those of K. Pearson in 1894. The search for classifications or ty pologies of objects or persons, however, is indigenous not only to biology but to a wide variety of disciplines. Thus, in recent years, a growing interest in classification and related areas has taken place. Today, we see applications of cluster analysis not only to. biology but also to such diverse areas as psychology, regional analysis, marketing research, chemistry, archaeology and medicine.



Structural Models


Structural Models
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Author : Frank Harary
language : en
Publisher:
Release Date : 1965

Structural Models written by Frank Harary and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1965 with Directed graphs categories.




Structural Models In Anthropology


Structural Models In Anthropology
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Author : Per Hage
language : en
Publisher:
Release Date : 1983

Structural Models In Anthropology written by Per Hage and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Mathematics categories.


Structural analysis in the social sciences has an extensive history. Frequently, however, it has been undertaken largely on the basis of intuition and common sense alone. In this book Per Hage and Frank Harary reveal the deeper insights into social and cultural structures that can be obtained through the application of graph theory.



Graphs As Structural Models


Graphs As Structural Models
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Author : Erhard Godehardt
language : en
Publisher:
Release Date : 2014-01-15

Graphs As Structural Models written by Erhard Godehardt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.




P Graphs For Process Systems Engineering


P Graphs For Process Systems Engineering
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Author : Ferenc Friedler
language : en
Publisher: Springer Nature
Release Date : 2022-02-03

P Graphs For Process Systems Engineering written by Ferenc Friedler and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-03 with Science categories.


This book discusses the P-graph framework for developing and understanding effective design tools for process systems engineering, and addresses the current state of its theory and applications. The book details the new philosophy of the axioms-based mathematical modelling of processing systems, the basic algorithms, areas of application, future directions, and the proofs of theorems and algorithms. Because of the rigorous foundation of the theory, the framework provides a firm basis for future research in mathematical modelling, optimization, and design of complex engineering systems. The various P-graph applications discussed include process network synthesis, reliability engineering, and systems resilience. The framework opens new avenues for research in complex systems including redundant operations for critical infrastructure, systems sustainability, and modelling tools for disaster engineering. Demonstration software is provided to facilitate the understanding of the theory. The book will be of interest to institutions, companies, and individuals performing research and R&D in process systems engineering.



Modern Methods For Epidemiology


Modern Methods For Epidemiology
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Author : Yu-Kang Tu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-05-22

Modern Methods For Epidemiology written by Yu-Kang Tu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-05-22 with Medical categories.


Routine applications of advanced statistical methods on real data have become possible in the last ten years because desktop computers have become much more powerful and cheaper. However, proper understanding of the challenging statistical theory behind those methods remains essential for correct application and interpretation, and rarely seen in the medical literature. Modern Methods for Epidemiology provides a concise introduction to recent development in statistical methodologies for epidemiological and biomedical researchers. Many of these methods have become indispensible tools for researchers working in epidemiology and medicine but are rarely discussed in details by standard textbooks of biostatistics or epidemiology. Contributors of this book are experienced researchers and experts in their respective fields. This textbook provides a solid starting point for those who are new to epidemiology, and for those looking for guidance in more modern statistical approaches to observational epidemiology. Epidemiological and biomedical researchers who wish to overcome the mathematical barrier of applying those methods to their research will find this book an accessible and helpful reference for self-learning and research. This book is also a good source for teaching postgraduate students in medical statistics or epidemiology.



Graph Based Representation And Reasoning


Graph Based Representation And Reasoning
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Author : Manuel Ojeda-Aciego
language : en
Publisher: Springer Nature
Release Date : 2023-08-15

Graph Based Representation And Reasoning written by Manuel Ojeda-Aciego and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-15 with Computers categories.


This book constitutes the refereed deadline proceedings of the 28th International Conference on Graph-Based Representation and Reasoning, ICCS 2023, held in Berlin, Germany, during September 11–13, 2023. The 9 full papers, 5 short papers and 4 Posters are included in this book were carefully reviewed and selected from 32 submissions. They were organized in topical sections as follows: Complexity and Database Theory, Formal Concept Analysis: Theoretical Advances, Formal Concept Analysis: Applications, Modelling and Explanation, Semantic Web and Graphs, Posters.



Graph Based Modelling In Engineering


Graph Based Modelling In Engineering
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Author : Stanisław Zawiślak
language : en
Publisher: Springer
Release Date : 2016-10-11

Graph Based Modelling In Engineering written by Stanisław Zawiślak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-11 with Technology & Engineering categories.


This book presents versatile, modern and creative applications of graph theory in mechanical engineering, robotics and computer networks. Topics related to mechanical engineering include e.g. machine and mechanism science, mechatronics, robotics, gearing and transmissions, design theory and production processes. The graphs treated are simple graphs, weighted and mixed graphs, bond graphs, Petri nets, logical trees etc. The authors represent several countries in Europe and America, and their contributions show how different, elegant, useful and fruitful the utilization of graphs in modelling of engineering systems can be.



Graph Data Modeling In Python


Graph Data Modeling In Python
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Author : Gary Hutson
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-06-30

Graph Data Modeling In Python written by Gary Hutson and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-30 with Computers categories.


Learn how to transform, store, evolve, refactor, model, and create graph projections using the Python programming language Purchase of the print or Kindle book includes a free PDF eBook Key Features Transform relational data models into graph data model while learning key applications along the way Discover common challenges in graph modeling and analysis, and learn how to overcome them Practice real-world use cases of community detection, knowledge graph, and recommendation network Book Description Graphs have become increasingly integral to powering the products and services we use in our daily lives, driving social media, online shopping recommendations, and even fraud detection. With this book, you'll see how a good graph data model can help enhance efficiency and unlock hidden insights through complex network analysis. Graph Data Modeling in Python will guide you through designing, implementing, and harnessing a variety of graph data models using the popular open source Python libraries NetworkX and igraph. Following practical use cases and examples, you'll find out how to design optimal graph models capable of supporting a wide range of queries and features. Moreover, you'll seamlessly transition from traditional relational databases and tabular data to the dynamic world of graph data structures that allow powerful, path-based analyses. As well as learning how to manage a persistent graph database using Neo4j, you'll also get to grips with adapting your network model to evolving data requirements. By the end of this book, you'll be able to transform tabular data into powerful graph data models. In essence, you'll build your knowledge from beginner to advanced-level practitioner in no time. What you will learn Design graph data models and master schema design best practices Work with the NetworkX and igraph frameworks in Python Store, query, ingest, and refactor graph data Store your graphs in memory with Neo4j Build and work with projections and put them into practice Refactor schemas and learn tactics for managing an evolved graph data model Who this book is for If you are a data analyst or database developer interested in learning graph databases and how to curate and extract data from them, this is the book for you. It is also beneficial for data scientists and Python developers looking to get started with graph data modeling. Although knowledge of Python is assumed, no prior experience in graph data modeling theory and techniques is required.



Advanced Intelligent Computing Technology And Applications


Advanced Intelligent Computing Technology And Applications
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Author : De-Shuang Huang
language : en
Publisher: Springer Nature
Release Date : 2024-08-01

Advanced Intelligent Computing Technology And Applications written by De-Shuang Huang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Computers categories.


This 13-volume set LNCS 14862-14874 constitutes - in conjunction with the 6-volume set LNAI 14875-14880 and the two-volume set LNBI 14881-14882 - the refereed proceedings of the 20th International Conference on Intelligent Computing, ICIC 2024, held in Tianjin, China, during August 5-8, 2024. The total of 863 regular papers were carefully reviewed and selected from 2189 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications". Papers that focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.