scholarly journals Estimating flood extent during Hurricane Harvey using maximum entropy to build a hazard distribution model

2019 ◽  
Vol 12 (S1) ◽  
Author(s):  
William Mobley ◽  
Antonia Sebastian ◽  
Wesley Highfield ◽  
Samuel D. Brody
Keyword(s):  
Maximum Entropy ◽  
Distribution Model ◽  
Hazard Distribution

scholarly journals A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 26
Author(s):  
Billy Joel M. Almarinez ◽  
Mary Jane A. Fadri ◽  
Richard Lasina ◽  
Mary Angelique A. Tavera ◽  
Thaddeus M. Carvajal ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Biological Control Agent ◽  
The Philippines ◽  
Distribution Model ◽  
Field Surveys ◽  
Probability Of Occurrence ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

scholarly journals An Integrative Dynamic Model of Colombian Population Distribution, Based on the Maximum Entropy Principle and Matter, Energy, and Information Flow

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1172
Author(s):  
César Cardona-Almeida ◽  
Nelson Obregón ◽  
Fausto A. Canales
Keyword(s):  
Maximum Entropy ◽  
Information Exchange ◽  
New Technologies ◽  
Population Distribution ◽  
Knowledge Society ◽  
Maximum Entropy Principle ◽  
Distribution Model ◽  
Human Society ◽  
Natural Systems ◽  
Entropy Principle

Human society has increased its capacity to exploit natural resources thanks to new technologies, which are one of the results of information exchange in the knowledge society. Many approaches to understanding the interactions between human society and natural systems have been developed in the last decades, and some have included considerations about information. However, none of them has considered information as an active variable or flowing entity in the human–natural/social-ecological system, or, moreover, even as a driving force of their interactions. This paper explores these interactions in socio-ecological systems by briefly introducing a conceptual frame focused on the exchange of information, matter, and energy. The human population is presented as a convergence variable of these three physical entities, and a population distribution model for Colombia is developed based on the maximum entropy principle to integrate the balances of related variables as macro-state restrictions. The selected variables were electrical consumption, water demand, and higher education rates (energy, matter, and information). The final model includes statistical moments for previous population distributions. It is shown how population distribution can be predicted yearly by combining these variables, allowing future dynamics exploration. The implications of this model can contribute to bridging information sciences and sustainability studies.

scholarly journals Stand Diameter Distribution Modeling and Prediction Based on Maximum Entropy Principle

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 859 ◽  
Author(s):  
Yuling Chen ◽  
Baoguo Wu ◽  
Zhiqiang Min
Keyword(s):  
Weibull Distribution ◽  
Maximum Entropy ◽  
Measurement Data ◽  
Similarity Index ◽  
Distribution Model ◽  
Diameter Distribution ◽  
Weibull Function ◽  
Prediction Ability ◽  
Actual Distribution ◽  
Modeling And Prediction

Research Highlights: Improving the prediction accuracy represents a popular forest simulation modeling issue, and exploring the optimal maximum entropy (MaxEnt) distribution is a new effective method for improving the diameter distribution model simulation precision to overcome the disadvantages of Weibull. Background and Objectives: The MaxEnt distribution is the closest to the actual distribution under the constraints, which are the main probability density distributions. However, relatively few studies have addressed the optimization of stand diameter distribution based on MaxEnt distribution. The objective of this study was to introduce application of the MaxEnt distribution on modeling and prediction of stand diameter distribution. Materials and Methods: The long-term repeated measurement data sets consisted of 260 diameter frequency distributions from China fir (Cunninghamia lanceolate (Lamb.) Hook) plantations in the southern China Guizhou. The Weibull distribution and the MaxEnt distribution were applied to the fitting of stand diameter distribution, and the modeling and prediction characteristics of Weibull distribution and MaxEnt distribution to stand diameter distribution were compared. Results: Three main conclusions were obtained: (1) MaxEnt distribution presented a more accurate simulation than three-parametric Weibull function; (2) the Chi-square test showed diameter distributions of unknown stands can be well estimated by applying MaxEnt distribution based on the plot similarity index method (PSIM) and Weibull distribution based on the parameter prediction method (PPM); (3) the MaxEnt model can deal with the complex nonlinear relationship and show strong prediction ability when predicting the stand distribution structure. Conclusions: With the increase of sample size, the PSIM has great application prospects in the dynamic prediction system of stand diameter distribution.

Weibull Model Based on the Maximum Entropy Principle and its Applications on Elements Grade Distribution

2012 ◽  
Vol 204-208 ◽  
pp. 4851-4854 ◽  
Author(s):  
Li Wan ◽  
Peng Chen ◽  
Xu Yi Hu
Keyword(s):  
Maximum Entropy ◽  
Maximum Entropy Principle ◽  
Mineral Resources ◽  
Weibull Model ◽  
Distribution Model ◽  
Forming Process ◽  
Grade Distribution ◽  
Economical Evaluation ◽  
Entropy Principle ◽  
Orderly State

The distribution of metallogenic elements grade is an effective index for the quantitatively economical evaluation of mineral resources. We have defined the information entropy as a measure of randomness of metallogenic elements grade distribution, assumed its primary distribution is in an extremely random situation, and deduced the density function of the primary distribution based on maximum entropy principle. Considering the fact that elements concentration goes from a non-orderly state to an orderly one in the ore-forming process, we added restraint parameters to the primary distribution model, got a two-parameter Weibull distribution model with embedded fractal features, and then fitted metallogenic element's grade distribution of Ag-Cu-Pb-Zn from a mine in China. The results show that the Weibull model is more effective than a lognormal model to describe elements distribution, and should be applied more broadly than common lognormal models in geology discipline.

Statistical Distribution Models of Clutch Service Load

2011 ◽  
Vol 403-408 ◽  
pp. 5244-5249
Author(s):  
Chang Gao Xia ◽  
Meng Zhang ◽  
Xiang Gao ◽  
Zhen Yu Zhang
Keyword(s):  
Maximum Entropy ◽  
Distribution Model ◽  
Statistical Features ◽  
Maximum Entropy Model ◽  
Linear Least Squares ◽  
Distribution Models ◽  
Entropy Model ◽  
Service Load ◽  
Maximum Entropy Distribution ◽  
Model Expression

The mixed distribution model and the maximum entropy model are used to represent service load of the vehicle clutch. The parameters of those models are estimated with different methods. The findings indicate that maximum entropy distribution can accurately describe different statistical features of random variables as minimally prejudiced probability distribution if order of the distribution function is properly selected, and that the mixed Weibull distribution shows super performance of the complicated statistical model expression. The parameters of those models are estimated by optimization based on non-linear least squares.

scholarly journals Potential distribution model of Leontochir ovallei using remote sensing data

2019 ◽  
pp. 59
Author(s):  
S. Payacán ◽  
F.D. Alfaro ◽  
W. Pérez-Martínez ◽  
I. Briceño-de-Urbaneja
Keyword(s):  
Maximum Entropy ◽  
Potential Distribution ◽  
Remote Sensing Data ◽  
Local Scale ◽  
Distribution Model ◽  
Natural Distribution ◽  
Coastal Desert ◽  
Restricted Distribution ◽  
Distribution Ranges ◽  
Coastal Fog

<p>Predicting the potential distribution of short-lived species with a narrow natural distribution range is a difficult task, especially when there is limited field data. The possible distribution of <em>L. ovallei</em> was modeled using the maximum entropy approach. This species has a very restricted distribution along the hyperarid coastal desert in northern Chile. Our results showed that local and regional environmental factors define its distribution. Changes in altitude and microhabitat related to the landforms are of critical importance at the local scale, whereas cloud cover variations associated with coastal fog was the principal factor determining the presence <em>of L. ovallei</em> at the regional level. This study verified the value of the maximum entropy in understanding the factors that influence the distribution of plant species with restricted distribution ranges.</p>

scholarly journals Equity Market Description under High and Low Volatility Regimes Using Maximum Entropy Pairwise Distribution

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1307
Author(s):  
Mauricio A. Valle ◽  
Jaime F. Lavín ◽  
Nicolás S. Magner
Keyword(s):  
Maximum Entropy ◽  
Maximum Entropy Principle ◽  
Ferromagnetic State ◽  
Second Order ◽  
Distribution Model ◽  
Subprime Crisis ◽  
Second Moments ◽  
Entropy Principle ◽  
Volatility Regimes ◽  
Equity Indices

The financial market is a complex system in which the assets influence each other, causing, among other factors, price interactions and co-movement of returns. Using the Maximum Entropy Principle approach, we analyze the interactions between a selected set of stock assets and equity indices under different high and low return volatility episodes at the 2008 Subprime Crisis and the 2020 Covid-19 outbreak. We carry out an inference process to identify the interactions, in which we implement the a pairwise Ising distribution model describing the first and second moments of the distribution of the discretized returns of each asset. Our results indicate that second-order interactions explain more than 80% of the entropy in the system during the Subprime Crisis and slightly higher than 50% during the Covid-19 outbreak independently of the period of high or low volatility analyzed. The evidence shows that during these periods, slight changes in the second-order interactions are enough to induce large changes in assets correlations but the proportion of positive and negative interactions remains virtually unchanged. Although some interactions change signs, the proportion of these changes are the same period to period, which keeps the system in a ferromagnetic state. These results are similar even when analyzing triadic structures in the signed network of couplings.

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