Visualizing high-dimensional data: Advances in the past decade
Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …
computing resources, have generated large, complex, high-dimensional datasets used to …
Visual parameter space analysis: A conceptual framework
Various case studies in different application domains have shown the great potential of
visual parameter space analysis to support validating and using simulation models. In order …
visual parameter space analysis to support validating and using simulation models. In order …
A partition-based framework for building and validating regression models
T Mühlbacher, H Piringer - IEEE Transactions on Visualization …, 2013 - ieeexplore.ieee.org
Regression models play a key role in many application domains for analyzing or predicting
a quantitative dependent variable based on one or more independent variables. Automated …
a quantitative dependent variable based on one or more independent variables. Automated …
The generalized sensitivity scatterplot
Scatterplots remain a powerful tool to visualize multidimensional data. However, accurately
understanding the shape of multidimensional points from 2D projections remains …
understanding the shape of multidimensional points from 2D projections remains …
Markov-switching vector autoregressive neural networks and sensitivity analysis of environment, economic growth and petrol prices
M Bildirici, Ö Ersin - Environmental Science and Pollution Research, 2018 - Springer
The paper aims at evaluating the nonlinear and complex relations between CO 2 emissions,
economic development, and petrol prices to obtain new insights regarding the shape of the …
economic development, and petrol prices to obtain new insights regarding the shape of the …
Self-organizing maps for multi-objective Pareto frontiers
Decision makers often need to take into account multiple conflicting objectives when
selecting a solution for their problem. This can result in a potentially large number of …
selecting a solution for their problem. This can result in a potentially large number of …
Development and evaluation of two approaches of visual sensitivity analysis to support epidemiological modeling
Computational modeling is a commonly used technology in many scientific disciplines and
has played a noticeable role in combating the COVID-19 pandemic. Modeling scientists …
has played a noticeable role in combating the COVID-19 pandemic. Modeling scientists …
[HTML][HTML] Artificial Neural Network (ANN)-Based Water Quality Index (WQI) for Assessing Spatiotemporal Trends in Surface Water Quality—A Case Study of South …
TD Banda, M Kumarasamy - Water, 2024 - mdpi.com
Artificial neural networks (ANNs) are powerful data-oriented “black-box” algorithms capable
of assessing and delineating linear and multifaceted non-linear correlations between the …
of assessing and delineating linear and multifaceted non-linear correlations between the …
Enhancing statistical charts: toward better data visualization and analysis
Conventional statistical charts are widely used in visual analysis. With the development of
digital techniques, statistical charts are confronted with problems when data grow in scale …
digital techniques, statistical charts are confronted with problems when data grow in scale …
Rethinking sensitivity analysis of nuclear simulations with topology
In nuclear engineering, understanding the safety margins of the nuclear reactor via
simulations is arguably of paramount importance in predicting and preventing nuclear …
simulations is arguably of paramount importance in predicting and preventing nuclear …