scholarly journals Identifying important nodes from content-associated heterogeneous graph by LeaderRank

2021 ◽  
Vol 2113 (1) ◽  
pp. 012082
Author(s):  
Yulong Dai ◽  
Qiyou Shen ◽  
Xiangqian Xu ◽  
Jun Yang
Keyword(s):  
Real World ◽  
Experimental Analysis ◽  
Differential Information ◽  
World Systems ◽  
Ranking Problem ◽  
Data Set ◽  
Importance Ranking ◽  
Basic Concepts ◽  
Important Nodes ◽  
Graph Nodes

Abstract Most real-world systems consist of a large number of interacting entities of many types. However, most of the current researches on systems are based on the assumption that the type of node or link in the network is unique. In other words, the network is homogeneous, containing the same type of nodes and links. Based on this assumption, differential information between nodes and edges is ignored. This paper firstly introduces the research background, challenges and significance of this research. Secondly, the basic concepts of the model are introduced. Thirdly, a novel type-sensitive LeaderRank algorithm is proposed and combined with distance rule to solve the importance ranking problem of content-associated heterogeneous graph nodes. Finally, the writer influence data set is used for experimental analysis to further prove the validity of the model.

Debt Markets and Investments

2019 ◽  
Keyword(s):  
Real World ◽  
Level Of Detail ◽  
Fixed Income ◽  
Key Concepts ◽  
Debt Markets ◽  
Basic Concepts ◽  
User Friendly ◽  
Distinguishing Features ◽  
Consistent Approach ◽  
Complex Subject

This book provides an objective look into the dynamic world of debt markets, products, valuation, and analysis. It also provides an in-depth understanding about this subject from experts in the field, both practitioners and academics. The coverage extends from discussing basic concepts and their application to increasingly intricate and real-world situations. This volume spans the gamut from theoretical to practical, while attempting to offer a useful balance of detailed and user-friendly coverage. The book has several distinguishing features. It blends the contributions of a global array of scholars and practitioners into a single review of some of the most important topics in this area. The book follows an internally consistent approach in format and style. Hence, it is collectively much more than a compilation of chapters from an array of different authors. It presents theory without unnecessary abstraction, quantitative techniques using basic bond mathematics, and conventions at a useful level of detail. It also incorporates how investment professionals analyze and manage fixed income portfolios. The book emphasizes empirical evidence involving debt securities and markets so it is understandable to a wide array of readers. Each chapter contains discussion questions to help reinforce key concepts. The end of the book contains guideline answers to each question. Readers interested in a broad survey will benefit as will those looking for more in-depth presentations of specific areas within this field of study. In summary, the book provides a fresh look at this intriguing and dynamic but often complex subject.

Phenomenological Modelling

2018 ◽  
Author(s):  
Ray Huffaker ◽  
Marco Bittelli ◽  
Rodolfo Rosa
Keyword(s):  
Nonlinear Dynamics ◽  
Time Series ◽  
Real World ◽  
Biological Diversity ◽  
False Positives ◽  
World Systems ◽  
Economic Activities ◽  
Essential Services ◽  
Low Dimension ◽  
Convergent Cross Mapping

Detecting causal interactions among climatic, environmental, and human forces in complex biophysical systems is essential for understanding how these systems function and how public policies can be devised that protect the flow of essential services to biological diversity, agriculture, and other core economic activities. Convergent Cross Mapping (CCM) detects causal networks in real-world systems diagnosed with deterministic, low-dimension, and nonlinear dynamics. If CCM detects correspondence between phase spaces reconstructed from observed time series variables, then the variables are determined to causally interact in the same dynamic system. CCM can give false positives by misconstruing synchronized variables as causally interactive. Extended (delayed) CCM screens for false positives among synchronized variables.

scholarly journals Higher-order temporal network effects through triplet evolution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Yao ◽  
Bingsheng Chen ◽  
Tim S. Evans ◽  
Kim Christensen
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Higher Order ◽  
Prediction Algorithm ◽  
Interaction Patterns ◽  
Temporal Networks ◽  
World Systems ◽  
Order Interaction ◽  
Space And Time ◽  
Pairwise Interactions

AbstractWe study the evolution of networks through ‘triplets’—three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.

scholarly journals Asymmetry underlies stability in power grids

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ferenc Molnar ◽  
Takashi Nishikawa ◽  
Adilson E. Motter
Keyword(s):  
Symmetry Breaking ◽  
Real World ◽  
Power Grids ◽  
Stable Operation ◽  
World Systems ◽  
Symmetric State ◽  
Network Systems ◽  
Additional Improvement ◽  
The Stability ◽  
General Method

AbstractBehavioral homogeneity is often critical for the functioning of network systems of interacting entities. In power grids, whose stable operation requires generator frequencies to be synchronized—and thus homogeneous—across the network, previous work suggests that the stability of synchronous states can be improved by making the generators homogeneous. Here, we show that a substantial additional improvement is possible by instead making the generators suitably heterogeneous. We develop a general method for attributing this counterintuitive effect to converse symmetry breaking, a recently established phenomenon in which the system must be asymmetric to maintain a stable symmetric state. These findings constitute the first demonstration of converse symmetry breaking in real-world systems, and our method promises to enable identification of this phenomenon in other networks whose functions rely on behavioral homogeneity.

An experimental analysis of the cooling constant computation

2021 ◽  
Vol 57 (2) ◽  
pp. 025001
Author(s):  
J E M Perea Martins
Keyword(s):  
Experimental Data ◽  
Water Temperature ◽  
Experimental Analysis ◽  
Electronic System ◽  
Water Cooling ◽  
Cooling Process ◽  
Data Set ◽  
Theoretical Methods ◽  
Electronic Instrumentation

Abstract This work presents the design of an inexpensive electronic system to measure water temperature and generate an experimental data set used to verify the fitting between experimental and theoretical curves of a water-cooling process. The cooling constant is computed with three different theoretical methods to check their efficiency and this approach allows the association of theoretical and experimental aspects of physics, mathematics and electronic instrumentation, which can motivate interesting discussions in the classroom.

scholarly journals Modeling and simulation of economic processes

2010 ◽  
Author(s):  
Bogdan Brumar
Keyword(s):  
Decision Analysis ◽  
Modeling And Simulation ◽  
Real World ◽  
Analytical Methods ◽  
Simulation Experiment ◽  
Management Decision ◽  
Economic Systems ◽  
World Systems ◽  
Simulation Techniques ◽  
Laborious Work

In general, any activity requires a longer action often characterized by a degree of uncertainty, insecurity, in terms of size of the objective pursued. Because of the complexity of real economic systems, the stochastic dependencies between different variables and parameters considered, not all systems can be adequately represented by a model that can be solved by analytical methods and covering all issues for management decision analysis-economic horizon real. Often in such cases, it is considered that the simulation technique is the only alternative available. Using simulation techniques to study real-world systems often requires a laborious work. Making a simulation experiment is a process that takes place in several stages.

scholarly journals Analysis on Present Mathematical Model for Predicting the Crop Production

2020 ◽  
Vol 9 (12) ◽  
pp. 168-170
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Real World ◽  
Crop Production ◽  
Ghg Emissions ◽  
Data Set ◽  
Factors Affecting ◽  
The Government ◽  
The Mathematical Model ◽  
Government Website

India is a worldwide agriculture business powerhouse. Future of agriculture-based products depends on the crop production. A mathematical model might be characterized as a lot of equations that speak to the conduct of a framework. By using mathematical model in agriculture field, we can predict the production of crop in particular area. There are various factors affecting crops such as Rainfall, GHG Emissions, Temperature, Urbanization, climate, humidity etc. A mathematical model is a simplified representation of a real-world system. It forms the system using mathematical principles in the form of a condition or a set of conditions. Suppose we need to increase the crop production, at that time the mathematical model plays a major role and our work can be easier, more significant by using the mathematical model. Through the mathematical model we predict the crop production in upcoming years. .AI, ML, IOT play a major role to predict the future of agriculture, but without mathematical models it is not possible to predict crop production accurately. To solve the real-world agriculture problem, mathematical models play a major role for accurate results. Correlation Analysis, Multiple Regression analysis and fuzzy logic simulation standards have been utilized for building a grain production benefit depending model from crop production. Prediction of crop is beneficiary to the farmer to analyze the crop management. By using the present agriculture data set which is available on the government website, we can build a mathematical model.

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