scholarly journals Information Geometric Theory in the Prediction of Abrupt Changes in System Dynamics

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 694
Author(s):  
Adrian-Josue Guel-Cortez ◽  
Eun-jin Kim
Keyword(s):  
Information Flow ◽  
Extreme Event ◽  
Geometric Theory ◽  
Theoretical Method ◽  
Sensitive Information ◽  
Systems Management ◽  
Abrupt Changes ◽  
Prediction Capability ◽  
Dependent Probability ◽  
Better Than

Detection and measurement of abrupt changes in a process can provide us with important tools for decision making in systems management. In particular, it can be utilised to predict the onset of a sudden event such as a rare, extreme event which causes the abrupt dynamical change in the system. Here, we investigate the prediction capability of information theory by focusing on how sensitive information-geometric theory (information length diagnostics) and entropy-based information theoretical method (information flow) are to abrupt changes. To this end, we utilise a non-autonomous Kramer equation by including a sudden perturbation to the system to mimic the onset of a sudden event and calculate time-dependent probability density functions (PDFs) and various statistical quantities with the help of numerical simulations. We show that information length diagnostics predict the onset of a sudden event better than the information flow. Furthermore, it is explicitly shown that the information flow like any other entropy-based measures has limitations in measuring perturbations which do not affect entropy.

scholarly journals Applicability of Susceptibility Model for Rock and Loess Earthquake Landslides in the Eastern Tibetan Plateau

2021 ◽  
Vol 13 (13) ◽  
pp. 2546
Author(s):  
Xinyi Guo ◽  
Bihong Fu ◽  
Jie Du ◽  
Pilong Shi ◽  
Qingyu Chen ◽  
...  
Keyword(s):  
Landslide Susceptibility ◽  
Disaster Relief ◽  
Coupling Model ◽  
Scientific Data ◽  
Eastern Tibetan Plateau ◽  
Loess Landslide ◽  
Rock Landslide ◽  
Susceptibility Model ◽  
Prediction Capability ◽  
Better Than

It is crucial to explore a suitable landslide susceptibility model with an excellent prediction capability for rapid evaluation and disaster relief in seismic regions with different lithological features. In this study, we selected two typical seismic events, the Jiuzhaigou and Minxian earthquakes, which occurred in the Alpine karst and loess regions, respectively. Eight influencing factors and five models were chosen to calculate the susceptibility of landslide, including the information (I) model, certainty factor (CF) model, logistic regression (LR) model, I + LR coupling model, and CF + LR coupling model. Then, the accuracy and the landslide susceptibility distribution of these models were assessed by the area under curve (AUC) and distribution criteria. Finally, the model with high accuracy and good applicability for the rock landslide or loess landslide regions was optimized. Our results showed that the accuracy of the coupling model is higher than that of the single models. Except for the LR model, the landslide susceptibility distribution for the above-mentioned models is consistent with universal cognition. The coupling models are generally better than their single models. Among them, the I + LR model can obtain the best comprehensive results for assessing the distribution and accuracy of both rock and loess landslide susceptibility, which is helpful for disaster relief and policy-making, and it can also provide useful scientific data for post-seismic reconstruction and restoration.

Forecasting of an extreme flood in mountainous area of North China based on WRF-Hydro with distributing parameters

2020 ◽  
Author(s):  
Wei Wang ◽  
JIa Liu ◽  
Chuanzhe Li ◽  
Qingtai Qiu ◽  
Yuchen Liu
Keyword(s):  
Extreme Event ◽  
Forecast Accuracy ◽  
Northern China ◽  
Calibration Method ◽  
Mountainous Area ◽  
Coupling System ◽  
Extreme Flood ◽  
Spatio Temporal ◽  
Merging Method ◽  
Better Than

<p>The flood events in the mountainous area of northern China has the characteristics of high intensity and strong sudden occurrence, and atmospheric-hydrological coupling system can improve the forecast accuracy and prolong the lead time. This paper discusses the simulations of the enhanced WRF-Hydro model on a historical flood that occurrs in a mesoscale catchment of Taihang mountain on July 21, 2012. Firstly, the precipitation accuracy of WRF, WRF data assimilation, co-kriging merging method of radar QPE data are as three different input sources for WRF-Hydro. The results show that the rainfall of merging QPE can achieve better simulations in time and space. In addition, the rainfall of WRF assimilation data is obviously better than that of WRF, but still underestimates the rainfall values. The extreme event rainstorm mainly <span>proceeds </span>in 5 hours, and for the assimilation data, the spatio-temporal simulations of the rainfall data in the first 2 hours are slightly poor. Hence we compare the combination of the first few hours to use the merging QPE and following by assimilation precipitation as the model input. In addition, according to the parameters of the WRF-Hydro model, a gridding parameter calibration method based on topographic index is constructed.</p>

scholarly journals Preface to the special issue on quantitative information flow

2014 ◽  
Vol 25 (2) ◽  
pp. 203-206 ◽  
Author(s):  
MIGUEL E. ANDRÉS ◽  
CATUSCIA PALAMIDESSI ◽  
GEOFFREY SMITH
Keyword(s):  
Computer Security ◽  
Information Flow ◽  
Quantitative Information ◽  
Side Channel ◽  
Sensitive Information ◽  
Fundamental Issue ◽  
Special Issue ◽  
The One ◽  
Flow Of Information ◽  
Quantitative Information Flow

A long-standing and fundamental issue in computer security is to control the flow of information, whether to prevent confidential information from being leaked, or to prevent trusted information from being tainted. While there have been many efforts aimed at preventing improper flows completely (see for example, the survey by Sabelfeld and Myers (2003)), it has long been recognized that perfection is often impossible in practice. A basic example is a login program – whenever it rejects an incorrect password, it unavoidably reveals that the secret password differs from the one that was entered. More subtly, systems may be vulnerable to side channel attacks, because observable characteristics like running time and power consumption may depend, at least partially, on sensitive information.

scholarly journals A Hardware Design Language for Timing-Sensitive Information-Flow Security

2015 ◽  
Vol 50 (4) ◽  
pp. 503-516 ◽  
Author(s):  
Danfeng Zhang ◽  
Yao Wang ◽  
G. Edward Suh ◽  
Andrew C. Myers
Keyword(s):  
Information Flow ◽  
Hardware Design ◽  
Sensitive Information ◽  
Information Flow Security ◽  
Design Language

scholarly journals Causal Information Rate

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1087
Author(s):  
Eun-jin Kim ◽  
Adrian-Josue Guel-Cortez
Keyword(s):  
Information Flow ◽  
Geometric Theory ◽  
Information Rate ◽  
Causal Information ◽  
Geometric Measure ◽  
Equilibrium Processes ◽  
Statistical State ◽  
New Information ◽  
Kramers Equation ◽  
Rate Information

Information processing is common in complex systems, and information geometric theory provides a useful tool to elucidate the characteristics of non-equilibrium processes, such as rare, extreme events, from the perspective of geometry. In particular, their time-evolutions can be viewed by the rate (information rate) at which new information is revealed (a new statistical state is accessed). In this paper, we extend this concept and develop a new information-geometric measure of causality by calculating the effect of one variable on the information rate of the other variable. We apply the proposed causal information rate to the Kramers equation and compare it with the entropy-based causality measure (information flow). Overall, the causal information rate is a sensitive method for identifying causal relations.

scholarly journals Evaluation and Development of Pedotransfer Functions for Predicting Saturated Hydraulic Conductivity for Mexican Soils

2020 ◽  
Author(s):  
Josué Trejo-Alonso ◽  
Antonio Quevedo ◽  
Carlos Fuentes ◽  
Carlos Chávez
Keyword(s):  
Hydraulic Conductivity ◽  
Water Content ◽  
Bulk Density ◽  
Saturated Hydraulic Conductivity ◽  
Irrigation District ◽  
Pedotransfer Functions ◽  
Del Rio ◽  
Clay Percentage ◽  
Prediction Capability ◽  
Better Than

In the present work, we evaluate the prediction capability of six Pedotransfer functions (PTFs), reported in the literature, for the saturated hydraulic conductivity estimations (Ks). We used a database with 900 measured samples obtained from the Irrigation District 023, in San Juan del Rio, Queretaro, Mexico. Additionally, six new PTFs were construct for Ks from clay percentage, bulk density and saturation water content data. The results show, for the evaluated models, that one model present an overestimation for Ks>0.5 cm h-1 values, three models have a underestimation for Ks>1.0 cm h-1 and two models have a good correlation (R2>0.98) but are necessary more than three parameters. Nevertheless, the last two models requires from three to four parameters in order to get the optimization. By other hand, the models proposed in this work have a similar correlation with a less number of parameters: the fit is seen to be much better than using the existing ones, achieving a correlation of R2 = 0.9822 with only one variable and a R2 = 0.9901 when we use two.

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