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IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks

Patricia Wollstadt, Joseph Lizier, Raul Vicente, Conor Finn, Mario Martinez-Zarzuela, Pedro Mediano, Leonardo Novelli, Michael Wibral
2019 Journal of Open Source Software  
The Information Dynamics Toolkit xl (IDTxl) is a comprehensive software package for efficient inference of networks and their node dynamics from multivariate time series data using information theory.  ...  IDTxl provides functionality to estimate the following measures: 1) For network inference: multivariate transfer entropy (TE)/Granger causality (GC), multivariate mutual information (MI), bivariate TE/  ...  problems that arise in multivariate TE estimation.  ... 
doi:10.21105/joss.01081 fatcat:urir4jdszvchtjy4waognaoxim

Temporal Multivariate Networks [chapter]

Daniel Archambault, James Abello, Jessie Kennedy, Stephen Kobourov, Kwan-Liu Ma, Silvia Miksch, Chris Muelder, Alexandru C. Telea
2014 Lecture Notes in Computer Science  
In this chapter, we characterize and survey methods for visualizing temporal multivariate networks.  ...  In a multivariate scenario, however, attributes play an important role and can also evolve over time.  ...  Applications to Software Engineering Temporal multivariate networks play a key role in many aspects of software engineering (SE).  ... 
doi:10.1007/978-3-319-06793-3_8 fatcat:fdvjfwg4jvathcj2mxchrotv6y

Interpreting The Out-Of-Control Signals Of Multivariate Control Charts Employing Neural Networks

Francisco Aparisi, José Sanz
2010 Zenodo  
In this paper neural networks are designed to interpret the out-of-control signal of the MEWMA chart, and the percentage of correct classifications is studied for different cases.  ...  Multivariate quality control charts show some advantages to monitor several variables in comparison with the simultaneous use of univariate charts, nevertheless, there are some disadvantages.  ...  The software QNET2000 has been utilized to train the neural networks.  ... 
doi:10.5281/zenodo.1071567 fatcat:yjz5b5bk7vgo3ddbblfzgwwi7y

Normality Testing for Vectors on Perceptron Layers

Youmna Shawki Karaki, Halina Kaubasa, Nick Ivanov
2020 European Journal of Engineering Research and Science  
Multivariate Normality Analysis methods are widespread in contemporary applied mathematics.  ...  Designing optimal topology of network graph is one of the most prevalent issues in neural network applications.  ...  PROBLEM, MATERIALS AND SOFTWARE The problem under consideration lies in the domain of neural network hyperparameters optimization.  ... 
doi:10.24018/ejers.2020.5.9.2090 fatcat:yvyqxj7krfamtoeyerzfjra4ey

Book Announcements

1992 Journal of Guidance Control and Dynamics  
., Neural Networks and Fuzzy Systems, Prentice- Hall, Englewood Cliffs, NJ, 1992, 449 pages. Purpose: This book presents neural networks and fuzzy theory from a unified engineering perspective.  ...  processes; parame- ter-optimized multivariable control systems; multivariable ma- trix polynomial control systems; multivariable state control systems; state estimation; adaptive control systems; on-line  ... 
doi:10.2514/3.56568 fatcat:xgdb24qnardvxlx6husadcjgrm

Software Tools For System Identification And Control Using Neural Networks In Process Engineering

J. Fernandez De Canete, S. Gonzalez-Perez, P. Del Saz-Orozco
2008 Zenodo  
The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field.  ...  Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering.  ...  using Neural Networks in Process Engineering J.  ... 
doi:10.5281/zenodo.1328035 fatcat:bdw2xhmbsff2fgsfjenxoyxoxa

SAILS: Spectral Analysis In Linear Systems

Andrew Quinn, Mark Hymers
2020 Journal of Open Source Software  
These approaches are fundamental in a wide range of science and engineering fields and still undergoing active development.  ...  SAILS (Spectral Analysis in Linear Systems) is a python package which implements such methods and provides a basis for both the straightforward fitting of AR models as well as exploration and development  ...  A biomedical engineer analysing M/EEG data may be interested in the spectral connectivity metrics for quantifying how oscillatory synchrony in brain networks changes between clinical populations.  ... 
doi:10.21105/joss.01982 fatcat:xzy7s6nfb5denfyyh5dn55mvqu

The Network Lens: Interactive Exploration of Multivariate Networks Using Visual Filtering

Ilir Jusufi, Yang Dingjie, Andreas Kerren
2010 2010 14th International Conference Information Visualisation  
Moreover, real-life network data sets usually represent objects with a large number of additional attributes that need to be visualized, such as in software engineering, social network analysis, or biochemistry  ...  In this paper, we present a novel approach, called Network Lens, to visualize such attributes in context of the underlying network.  ...  In addition, we could compute different measurements (software metrics) for such elements that are important to maintain and to improve the software engineering processes.  ... 
doi:10.1109/iv.2010.15 dblp:conf/iv/JusufiDK10 fatcat:vuon2qdbvfaibdz7pk65ywe65i

The Prediction of Concrete Temperature during Curing Using Regression and Artificial Neural Network

Zahra Najafi, Kaveh Ahangari
2013 Journal of Engineering  
In this paper, multivariable regression and neural network methods were used for estimating concrete temperature.  ...  By using the same input set, the artificial neural network predicted concrete temperature with higher R 2 of 0.999.  ...  The authors do not have a direct financial relation with the commercial identity mentioned in the paper (SPSS and MATLAB softwares).  ... 
doi:10.1155/2013/946829 fatcat:feezxhv5fzerfaphorb4sjzn4e

State-of-the-art in control engineering

Štefan Kozák
2014 Journal of Electrical Systems and Information Technology  
Main ideas covered in this paper are motivated namely by the development of new advanced control engineering methods (predictive, hybrid predictive, optimal, adaptive, robust, fuzzy logic, and neural network  ...  Present trends in the complex process control design demand an increasing degree of integration of numerical mathematics, control engineering methods, new control structures based of distribution, embedded  ...  Much of the fuzzy control literature and some commercial software, employ fuzzy rules in combination with PID control.  ... 
doi:10.1016/j.jesit.2014.03.002 fatcat:hxcl5r2325eljcguo54p5lj53i

Page 129 of American Society of Civil Engineers. Collected Journals Vol. 8, Issue 2 [page]

1994 American Society of Civil Engineers. Collected Journals  
EDITORIAL WHERE AND WHY ARTIFICIAL NEURAL NETWORKS ARE APPLICABLE IN CIVIL ENGINEERING In our attemps to design, analyze and control the behavior of systems, both man-made and natural, we engineers find  ...  An ANN is quite simply a collection of simple processing units (often simulated on a serial computer in software) that pass around activations that are filtered and modified by the connections between  ... 

Statistical dependence in risk analysis for project networks using Monte Carlo methods

J.R. van Dorp, M.R. Duffey
1999 International Journal of Production Economics  
Monte Carlo simulation of project networks is increasingly used by engineering firms to analyze schedule/cost risk for bidding purposes.  ...  However, one serious methodological flaw of most Monte Carlo simulations is the assumption of statistical independence of activity durations in the network.  ...  Financial support for this research has been provided in part by NIST.  ... 
doi:10.1016/s0925-5273(98)00081-4 fatcat:nq5io7ey7fbodi5q6j25jgj5ii

Developing Pedotransfer Functions For Estimating Some Soil Properties Using Artificial Neural Network And Multivariate Regression Approaches

Fereydoon Sarmadian, Ali Keshavarzi
2010 Zenodo  
Results showed that ANN with five neurons in hidden layer had better performance in predicting soil properties than multivariate regression.  ...  Both multivariate regression and artificial neural network (ANN) techniques were employed to develop the appropriate PTFs for predicting soil parameters using easily measurable characteristics of clay,  ...  Hence with respecting to Table III , multivariate regression equations were developed for studied parameters using SPSS 15 software.  ... 
doi:10.5281/zenodo.1060638 fatcat:lb63x47a3bhynhi2rtz62wnrtq

Table of Contents

2020 2020 IEEE International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)  
product startup in Thailand Techawit Hirisatja, Panita Surachaikulwattana and Boonrat Lohwongwatana An Innovative Approach:Coupling Project Based Learning and Game Based Approach in Teaching Software Engineering  ...  Sasikala 15-20 Multivariate Statistical Investigation of Climatic Changes for Northern & Southern Hemisphere S2A: Electrical & Electronics Engineering Pages Detection of Choking Moments in College  ... 
doi:10.1109/temsmet51618.2020.9557444 fatcat:c2dg6ebph5gsze6m3oai22krri

Soft Computational Approaches for Prediction and Estimation of Software Development

Xiao-Zhi Gao, Arun Kumar Sangaiah, Muthu Ramachandran
2016 The Scientific World Journal  
extensive software engineering research problems.  ...  In particular, the special issue focuses on publishing the highly technical articles describing the software development topics: advanced software engineering, computational intelligence, and wireless  ...  Acknowledgments We would like to express our sincere gratitude to all the contributors who have submitted their high-quality manuscripts and to the experts for their support in providing review comments  ... 
doi:10.1155/2016/3905931 pmid:26989763 pmcid:PMC4775804 fatcat:574zhazhf5f27euaiqrcak3674
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