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Numerical simulation analysis of ecological monitoring of small reservoir dam based on maximum entropy algorithm

OPEN GEOSCIENCES 2023年第1期15卷

作者： Wang, Qing Zhou, Zhiwei Tang, Shaolong Wan, Siyuan Yu, Weiran Jiangxi Acad Water Sci & Engn Nanchang 330029 Jiangxi Peoples R China Jiangxi Prov Hydraul Safety Engn Technol Res Ctr Nanchang 330029 Jiangxi Peoples R China

Displacement monitoring method of reservoir dam is a key research topic at present. In order to better display the overall efficiency of horizontal displacement and vertical displacement monitoring, a numerical simulation analysis method of ecological monitoring of small reservoir dam based on the maximum entropy algorithm is proposed. The virtual value is calculated by the maximum entropy algorithm, and the probability distribution function of random variables is obtained. The comprehensive prediction model of ecological monitoring results is constructed by the probability distribution function, and the daily monitoring values of ecological history of small reservoir dams are obtained. The maximum entropy probability density function is used to calculate the initial moment of small reservoir displacement samples, calculate the abnormal probability of the dam, get the maximum entropy probability density, realize the unbiased distribution of simulation values, and complete the dam deformation monitoring of small reservoirs. The simulation experiment is verified by numerical simulation. The results show that this method can effectively monitor the horizontal and vertical displacement of the dam;monitor the water-level hydrograph of pressure pipes at each measuring point;and obtain the changes of ecological runoff, temperature difference, and sediment discharge around the dam of small reservoirs in real time, which provides data guarantee for improving the ecological added value of small reservoirs.

关键词： maximum entropy algorithm small reservoir dam ecological monitoring pressure tube water level probability distribution function the vertical displacement

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Research on the Application of maximum entropy Based algorithm in Precipitation Forecasting 24

Research on the Application of Maximum Entropy Based Algorit...

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4th International Conference on Internet of Things and Machine Learning

作者： Tian, Huaiying Zhou, Xiaoguang Zhou, Ming Army 91206 Qingdao Peoples R China Army 91475 Qingdao Peoples R China Team 18 Army 92919 Qingdao Peoples R China

ISBN: (纸本)9798400710353

Precipitation forecasting is crucial in meteorology as well as in fields such as agriculture and urban planning. This paper investigates the application of the maximum entropy algorithm in precipitation forecasting, exploring its unique advantages in handling complex meteorological data. By comparing it with traditional BP neural network algorithms, the paper provides a detailed analysis of the maximum entropy algorithm's performance in data processing, model training, and prediction accuracy. The results indicate that the maximum entropy algorithm offers superior precision and stability in precipitation forecasting, effectively addressing data diversity and uncertainty. These advantages position it as a promising method for precipitation prediction, contributing to enhanced accuracy and reliability in meteorological forecasts and providing scientific basis and technical support for related fields.

关键词： maximum entropy algorithm Neural networks Precipitation forecasting Applied research

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Optimizing the transformation of HYSCORE data using the maximum entropy algorithm

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JOURNAL OF MAGNETIC RESONANCE 2019年 301卷 30-39页

作者： Motygullina, Alina E. Mobli, Mehdi Harmer, Jeffrey R. Univ Queensland Ctr Adv Imaging St Lucia Qld 4072 Australia

Non-uniform sampling (NUS) in combination with the maximum entropy (MaxEnt) algorithm as applied to multi-dimensional NMR data has been thoroughly investigated and the NUS approach shown to provide significant sensitivity improvements as compared to methods using uniformly sampled (US) data and the discrete Fourier transform (DFT). Hyperfine sublevel correlation (HYSCORE) is a standard pulse EPR experiment that can potentially benefit greatly from this approach, but the data present unique challenges as compared to NMR. HYSCORE data typically exhibit a very large range of peak intensities, signals are in the form of irregularly shaped ridges with variable intensities, and time traces are generally truncated to save measurement time. MaxEnt has the advantageous properties that it does not require US data, dampens weak signals (noise) and does not suffer from windowing artifacts due to truncation of the time traces. Critical to the success of the MaxEnt algorithm is the choice of the two input parameters aim and def which describe the data noise and contribution of entropy in the optimization, respectively. In this paper we expand our preliminary study on the application of MaxEnt to the reconstruction of HYSCORE spectra to include a detailed analysis on sensitivity to detect weak peaks, investigate the non-linearity of the transformation and ascertain if it can be characterized by the introduction of synthetic peaks, and define a general range for the choice of aim and def. Furthermore, the ability of the MaxEnt method to remove windowing artefacts in uniformly sampled truncated HYSCORE data is described. (C) 2019 Published by Elsevier Inc.

关键词： EPR HYSCORE Non-uniform sampling maximum entropy algorithm

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Ecosystem service trade-offs weaken ecological network interactions

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JOURNAL OF CLEANER PRODUCTION 2025年 508卷

作者： Xie, Jing Xie, Binggeng Li, Junhan Zhang, Xuemao Pang, Xiaofei Hunan Normal Univ Sch Geog Sci Changsha 410081 Peoples R China Chinese Acad Sci Inst Geochem State Key Lab Environm Geochem Guiyang 550081 Peoples R China

Clarifying the relationship between ecological networks and ecosystem services will help to enhance regional biodiversity and human well-being. This study evaluated bird suitability in Changsha-Zhuzhou-Xiangtan urban agglomeration through field observations and maximum entropy model, and combined with distance thresholds to identify ecological networks. Network weights were quantified by an improved gravity model. The trade-off and synergistic between ecosystem services were determined, and we examined the relationship between bird ecological networks and ecosystem services from two perspectives: "substituting 'time' by 'space'" and "period differences", respectively. Following are the key findings: Average AUC of the ten iterations of MaxEnt model reached 0.8226, and the threshold of bird dispersal distance was 2300-3000 m. Bird ecological network underwent source degradation and corridor breakup during 2000-2020, in which the highest value of source area declined from 3701 km2 to 3400 km2. Counties at the edge had greater interaction forces, with the highest value of 114130.26, and had spatial spillovers. Trade-off strength of SC and HQ decreased from 0.593 to 0.569 in Yuanjiang and from 0.803 to 0.782 in Yueyang County, accompanied by an increase in the network force between the two counties from 22969.14 to 40026.65. Thus, decreases in the strength of trade-offs had positive effects on ecological network, while changes in the relationships from synergistic to trade-offs weakened interaction forces. Future urban planning should focus on monitoring the dynamics of bird network interactions at county boundaries, attending to stepping stone within buffer zones, and factoring in ecosystem service enhancement priorities and trade-off reduction.

关键词： Ecological network Ecosystem service Trade-offs maximum entropy algorithm Interaction force

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Machine learning for sinkhole risk mapping in Guidonia-Bagni di Tivoli plain (Rome), Italy

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GEOCARTO INTERNATIONAL 2022年第27期37卷 16687-16715页

作者： Bianchini, Silvia Confuorto, Pierluigi Intrieri, Emanuele Sbarra, Paolo Di Martire, Diego Calcaterra, Domenico Fanti, Riccardo Univ Florence Earth Sci Dept Florence Italy Univ Naples Federico II Earth Environm & Resource Sci Dept Naples Italy

This work presents a sinkhole susceptibility and risk assessment mapping in Guidonia-Bagni di Tivoli plain (Italy), a travertine sinkhole-prone area where sudden occurrences of sinkholes have happened in past and recent times. We collected a point-like sinkhole inventory and we considered a series of different sinkhole-controlling and precursory factors over the study area, related to its geo-litho-hydrological setting and to its terrain deformational scenario, i.e. ground motion rates derived from InSAR COSMO-SkyMed imagery. A sinkhole susceptibility map was produced through a machine learning model, namely maximum entropy algorithm (MaxEnt). Results highlight that the most determining factors for sinkhole formation are the lithology, the travertine thickness, groundwater and the land use. The sinkhole susceptibility map was then combined with data on vulnerability and elements-at-risk economic exposure in order to provide a sinkhole risk map of the area. The outcomes show that areas at higher risk covers about 2% of the total study area and primarily relies on the zoning of the main urban fabric. In particular, it is worth to highlight that 5% of the whole road-network pavement and 27% of all the residential buildings fall into High and Very High risk classes. Overall, results of this work demonstrate capabilities of machine learning models to assess sinkhole susceptibility for predicting potential sinkhole areas, and provide a sinkhole risk map, along with information on urban environment, as a useful tool for urban planning and geohazard risk management.

关键词： Sinkhole susceptibility risk machine learning maximum entropy algorithm Guidonia-Tivoli plain

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Validation of Transverse Phase Space Tomography at TRIUMF

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原子能科学技术 2022年第9期56卷 1760-1773页

作者： RAO Y N BAARTMAN R TRIUMF 4004 Wesbrook MallVancouver British ColumbiaV6T2A3Canada

Knowledge of the phase space density distribution in details is useful to understand subsequent evolution of the charged particle beam in a transport *** makes the beam tomography very useful in the application for beam *** application is not limited by the beam energy,as opposed to the emittance *** paper presented the simulations and measurements we undertook in TRIUMF beam-lines to validate the maximum entropy(MENT)technique for the tomographic reconstruction of beam density distribution in the 2-dimensional transverse phase *** profiles were taken with a single wire scanner while changing an upstream quadrupole’s ***,the phase space plots were directly measured with emittance scanner.A close comparison was made on the resulting phase space density distribution and the emittance value at the same location of the *** show good agreement.

关键词： beam tomography maximum entropy algorithm phase space emittance

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Ecological monitoring and assessment of habitat suitability for brown bear species in the Oshtorankooh protected area, Iran

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ECOLOGICAL INDICATORS 2021年 126卷 107606-107606页

作者： Ahmadipari, Masumeh Yavari, Ahmadreza Ghobadi, Morteza Univ Tehran Grad Fac Environm Dept Environm Tehran Iran Lorestan Univ Fac Agr & Nat Resources Dept Environm Khorramabad Iran

Habitat assessment of species is one of the most important strategies to conserve biodiversity in the protected areas. The main objective of this study is to present an ecological assessment model for habitat management of brown bears using the MaxEnt algorithm in Oshtorankooh protected area, Lorestan. 55 presence points of brown bear and seven environmental variables including slope, elevation, distance from river, distance from road, distance from forest and grassland, distance from cropland and vegetation, and distance from rural area were applied for habitat assessment process. The importance of these variables was investigated by the Jaknikfe test and their predictive rate was assessed by response curves. The distance from the rural area and elevation were respectively the most important factors for modeling the distribution of brown bears in Oshtorankooh protected area. The final suitability map of habitat for brown bear species was classified into four categories: more suitable, suitable, less suitable and unsuitable. An area of 22566.7 ha was determined as a more suitable habitat for brown bears in the study area. The result indicates that the southern and central areas of the study area are more suitable for the species. The result of the model validity was obtained as 0.92, showing that the integrated model was very efficient in the habitat assessment process.

关键词： Ecological modeling Jackknife test Habitat suitability maximum entropy algorithm Oshtorankooh protected area

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maximum entropy algorithm with inexact upper entropy bound based on Fup basis functions with compact support

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JOURNAL OF COMPUTATIONAL PHYSICS 2009年第24期228卷 9079-9091页

作者： Gotovac, Hrvoje Gotovac, Blaz Univ Split Dept Civil & Architectural Engn Split 21000 Croatia KTH Dept Land & Water Resources Engn S-10044 Stockholm Sweden

The maximum entropy (MaxEnt) principle is a versatile tool for statistical inference of the probability density function (pdf) from its moments as a least-biased estimation among all other possible pdfs. It maximizes Shannon entropy, satisfying the moment constraints. Thus, the MaxEnt algorithm transforms the original constrained optimization problem to the unconstrained dual optimization problem using Lagrangian multipliers. The Classic Moment Problem (CMP) uses algebraic power moments, causing typical conventional numerical methods to fail for higher-order moments (m > 5-10) due to different sensitivities of Lagrangian multipliers and unbalanced nonlinearities. Classic MaxEnt algorithms overcome these difficulties by using orthogonal polynomials, which enable roughly the same sensitivity for all Lagrangian multipliers. In this paper, we employ an idea based on different principles, using Fup(n) basis functions with compact support, which can exactly describe algebraic polynomials, but only if the Fup order-n is greater than or equal to the polynomial's order. Our algorithm solves the CMP with respect to the moments of only low order Fup(2) basis functions, finding a Fup(2) optimal pdf with better balanced Lagrangian multipliers. The algorithm is numerically very efficient due to localized properties of Fup(2) basis functions implying a weaker dependence between Lagrangian multipliers and faster convergence. Only consequences are an iterative scheme of the algorithm where power moments are a sum of Fup(2) and residual moments and an inexact entropy upper bound. However, due to small residual moments, the algorithm converges very quickly as demonstrated on two continuous pdf examples - the beta distribution and a bi-modal pdf, and two discontinuous pdf examples - the step and double Dirac pdf. Finally, these pdf examples present that Fup MaxEnt algorithm yields smaller entropy value than classic MaxEnt algorithm, but differences are very small for all practical engi

关键词： maximum entropy algorithm Classic Moment Problem Fup basis functions Compact support

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Is the current network system of protected areas in the Atlantic Forest effective in conserving key species of bryophytes?

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TROPICAL CONSERVATION SCIENCE 2014年第1期7卷 61-U251页

作者： Silva, Mercia P. P. Kamino, Luciana H. Y. Porto, Katia C. Univ Fed Bahia Inst Biol Dept Bot Lab Taxon Briofitas BR-40170280 Salvador BA Brazil Univ Fed Minas Gerais Inst Ciencias Biol Dept Bot BR-31270901 Belo Horizonte MG Brazil Univ Fed Pernambuco Ctr Ciencias Biol Dept Bot Lab Biol Briofitas BR-50670901 Recife PE Brazil

We combined distribution data of bryophyte species with protected areas in the Brazilian Atlantic Forest, using models of potential distribution of species, in order to assess the effectiveness and representativeness of Conservation Units for bryophyte species. We performed potential distribution models for ten bryophyte species classified as bio-indicators for environmental quality and/or endemic to the Atlantic Forest, or endemic to Brazil (key species). Data from online herbarium collections, literature, and sampling were used to estimate the potential distribution of the species, based on the MAXENT method. We performed an intersection between the maps with > 50% of environmental suitability for the occurrence of the studied species and the maps of the Brazilian protected areas. Areas with the greatest potential presence of bryophyte species not superimposed on protected areas were considered areas of gaps in protection. The habitat suitability of the models for nine species was explained by the Mean Diurnal Temperature Range. The consensus map of high environmental suitability for all species showed significant gaps in knowledge about their distribution. However, three centers of potential distribution were recognizable: one in the Northeast, one Central and another one in the Southeast. The total potentially suitable area overlapped with 83 Conservation Units (only 27%), less than adequate for efficient conservation of the species. The Central Corridor was the region with the highest environmental suitability but also has only a few Conservation Units in the Atlantic Forest, and is therefore a priority for conducting inventories and creating reserves.

关键词： Conservation Units environmental suitability gap analysis maximum entropy algorithm potential distribution models Tropical Forest

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Quantifying bursting neuron activity from calcium signals using blind deconvolution

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JOURNAL OF NEUROSCIENCE METHODS 2013年第2期218卷 196-205页

作者： Park, In Jun Bobkov, Yuriy V. Ache, Barry W. Principe, Jose C. Univ Florida Dept Elect & Comp Engn Gainesville FL 32611 USA Univ Florida Ctr Smell & Taste Whitney Lab Gainesville FL 32611 USA Univ Florida McKnight Brain Inst Gainesville FL 32611 USA Univ Florida Dept Biol Gainesville FL 32611 USA Univ Florida Dept Neurosci Gainesville FL 32611 USA

Advances in calcium imaging have enabled studies of the dynamic activity of both individual neurons and neuronal assemblies. However, challenges, such as unknown nonlinearities in the spike-calcium relationship, noise, and the often relatively low temporal resolution of the calcium signal compared to the time-scale of spike generation, restrict the accurate estimation of action potentials from the calcium signal. Complex neuronal discharge, such as the activity demonstrated by bursting and rhythmically active neurons, represents an even greater challenge for reconstructing spike trains based on calcium signals. We propose a method using blind calcium signal deconvolution based on an information-theoretic approach. This model is meant to maximise the output entropy of a nonlinear filter where the nonlinearity is defined by the cumulative distribution function of the spike signal. We tested our maximum entropy (ME) algorithm using bursting olfactory receptor neurons (bORNs) of the lobster olfactory organ. The advantage of the ME algorithm is that the filter can be trained online based only on the statistics of the spike signal, without any assumptions regarding the unknown transfer function characterizing the relation between the spike and calcium signal. We show that the ME method is able to more accurately reconstruct the timing of the first and last spikes of a burst compared to other methods and that it improves the temporal precision fivefold compared to direct timing resolution of calcium signal. (c) 2013 Elsevier B.V. All rights reserved.

关键词： Calcium imaging Olfactory receptor neuron Blind deconvolution Information-theoretic approach maximum entropy algorithm

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