The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative(BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis...The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative(BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis of equilibrium points without any reference to when or how to achieve it. In this paper, a dynamic gravity model was established based on the Maximum Entropy(MaxEnt) theory to estimate and monitor the interconnection intensity and dynamic characters of bilateral relations. In order to detect the determinants of interconnection intensity, a Geodetector method was applied to identify and evaluate the determinants of spatial networks in five dimensions. The empirical study clearly demonstrates a heterogeneous and non-circular spatial structure. The main driving forces of spatial-temporal evolution are foreign direct investment, tourism and railway infrastructure construction, while determinants in different sub-regions show obvious spatial differentiation. Southeast Asian countries are typically multi-island area where aviation infrastructure plays a more important role. North and Central Asian countries regard oil as a pillar industry where power and port facilities have a greater impact on the interconnection. While Western Asian countries are mostly influenced by the railway infrastructure, Eastern European countries already have relatively robust infrastructure where tariff policies provide a greater impetus.展开更多
Tibetan spruce (Picea smithiana) is an endemic species of the Himalayas,and it distributes only in a re-stricted area with very low number.To address the lack of detailed distributional information,we used maximum en-...Tibetan spruce (Picea smithiana) is an endemic species of the Himalayas,and it distributes only in a re-stricted area with very low number.To address the lack of detailed distributional information,we used maximum en-tropy (Maxent) niche-based model to predict the species' potential distribution from limited occurrence-only records.The location data of P.smithiana,relative bioclimatic variables,vegetation data,digital elevation model (DEM),and the derived data were analyzed in Maxent.The receiver operating characteristic (ROC) curve was applied to assess the prediction accuracy.The Maxent jackknife test was performed to quantify the training gains from data layers and the response of P.smithiana distribution to four typical environmental variables was analyzed.Results show that the model performs well at the regional scale.There is a potential for continued expansion of P.smithiana population numbers and distribution in China.P.smithiana potentially distributes in the lower reaches of Gyirong Zangbo and Poiqu rivers in Gyirong and Nyalam counties in Qomolangma (Mount Everest) National Nature Preserve (QNNP),China.The species prefers warm temperate climate in mountain area and mainly distributes in needle-leaved evergreen closed to open forest and mixed forest along the river valley at relatively low altitudes of about 2000-3000 m.Model simulations suggest that distribution patterns of rare species with few species numbers can be well predicted by Max-ent.展开更多
This letter presents a new chunking method based on Maximum Entropy (ME) model with N-fold template correction model.First two types of machine learning models are described.Based on the analysis of the two models,the...This letter presents a new chunking method based on Maximum Entropy (ME) model with N-fold template correction model.First two types of machine learning models are described.Based on the analysis of the two models,then the chunking model which combines the profits of conditional probability model and rule based model is proposed.The selection of features and rule templates in the chunking model is discussed.Experimental results for the CoNLL-2000 corpus show that this approach achieves impressive accuracy in terms of the F-score:92.93%.Compared with the ME model and ME Markov model,the new chunking model achieves better performance.展开更多
This paper applied Maximum Entropy (ME) model to Pinyin-To-Character (PTC) conversion in-stead of Hidden Markov Model (HMM) that could not include complicated and long-distance lexical informa-tion. Two ME models were...This paper applied Maximum Entropy (ME) model to Pinyin-To-Character (PTC) conversion in-stead of Hidden Markov Model (HMM) that could not include complicated and long-distance lexical informa-tion. Two ME models were built based on simple and complex templates respectively, and the complex one gave better conversion result. Furthermore, conversion trigger pair of y A → y B cBwas proposed to extract the long-distance constrain feature from the corpus; and then Average Mutual Information (AMI) was used to se-lect conversion trigger pair features which were added to the ME model. The experiment shows that conver-sion error of the ME with conversion trigger pairs is reduced by 4% on a small training corpus, comparing with HMM smoothed by absolute smoothing.展开更多
The maximum entropy principle(MEP) is one of the first methods which have been used to predict droplet size and velocity distributions of liquid sprays. This method needs a mean droplets diameter as an input to predic...The maximum entropy principle(MEP) is one of the first methods which have been used to predict droplet size and velocity distributions of liquid sprays. This method needs a mean droplets diameter as an input to predict the droplet size distribution. This paper presents a new sub-model based on the deterministic aspects of liquid atomization process independent of the experimental data to provide the mean droplets diameter for using in the maximum entropy formulation(MEF). For this purpose, a theoretical model based on the approach of energy conservation law entitled energy-based model(EBM) is presented. Based on this approach, atomization occurs due to the kinetic energy loss. Prediction of the combined model(MEF/EBM) is in good agreement with the available experimental data. The energy-based model can be used as a fast and reliable enough model to obtain a good estimation of the mean droplets diameter of a spray and the combined model(MEF/EBM) can be used to well predict the droplet size distribution at the primary breakup.展开更多
The maximum entropy model was introduced and a new intrusion detection approach based on the maximum entropy model was proposed. The vector space model was adopted for data presentation. The minimal entropy partitioni...The maximum entropy model was introduced and a new intrusion detection approach based on the maximum entropy model was proposed. The vector space model was adopted for data presentation. The minimal entropy partitioning method was utilized for attribute diseretization. Experiments on the KDD CUP 1999 standard data set were designed and the experimental results were shown. The receiver operating eharaeteristie（ROC） curve analysis approach was utilized to analyze the experimental results. The analysis results show that the proposed approach is comparable to those based on support vector maehine（SVM） and outperforms those based on C4.5 and Naive Bayes classifiers. According to the overall evaluation result, the proposed approach is a little better than those based on SVM.展开更多
Background: Hylurgus ligniperda(Fabricius) is native to Europe but has established populations in many countries and regions. H. ligniperda mainly infests Pinus species, and can cause severe weakness and even death of...Background: Hylurgus ligniperda(Fabricius) is native to Europe but has established populations in many countries and regions. H. ligniperda mainly infests Pinus species, and can cause severe weakness and even death of the host through its boring activity;it can also be a vector of various pathogenic fungi. This study was conducted to investigate the environmental variables limiting the distribution of H. ligniperda and the change trend of its suitable areas under climate change.Results: We used a maximum entropy model to predict the potential geographical distribution of H. ligniperda on a global scale under near current and future climatic scenarios using its occurrence data and environmental variables. The result shows that the areas surrounding the Mediterranean region, the eastern coastal areas of Asia, and the southeastern part of Oceania are highly suitable for H. ligniperda. The environmental variables with the greatest effect on the distribution of H. ligniperda were determined using the jackknife method and Pearson’s correlation analysis and included the monthly average maximum temperature in April, precipitation of driest quarter, the monthly average minimum temperature in December, precipitation of coldest quarter, mean temperature of driest quarter and mean diurnal range.Conclusions: Excessive precipitation in winter and low temperatures in spring had a great effect on the distribution of H. ligniperda. The potential geographical distribution of H. ligniperda was predicted to change under future climatic conditions compared with near current climate conditions. Highly suitable areas, moderately suitable areas and low suitable areas were predicted to increase by 59.99%, 44.43% and 22.92%, respectively, under the2081–2100 ssp245 scenario.展开更多
Detecting objects of interest from a video sequence is a fundamental and critical task in automated visual surveillance. Most current approaches only focus on discriminating moving objects by background subtraction wh...Detecting objects of interest from a video sequence is a fundamental and critical task in automated visual surveillance. Most current approaches only focus on discriminating moving objects by background subtraction whether or not the objects of interest can be moving or stationary. In this paper, we propose layers segmentation to detect both moving and stationary target objects from surveillance video. We extend the Maximum Entropy (ME) statistical model to segment layers with features, which are collected by constructing a codebook with a set of codewords for each pixel. We also indicate how the training models are used for the discrimination of target objects in surveillance video. Our experimental results are presented in terms of the success rate and the segmenting precision.展开更多
The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming ...The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming and higher plant species diversity,and to identify priority counties for conservation.We employed an integrated approach combining species distribution modeling,GIS overlay analysis,and empirical spatial regression to em pirically assess the impact of tobacco farming intensity on biodiversity risk.Our findings reveal a compelling negative spatial correlation between tobacco farming expansion and higher plant species diversity.Specifically,southern counties in Wenshan and Honghe prefectures are major priority areas of conservation that exhibit signif icant spatial correlations between biodiversity risks and high tobacco farming intensity.Quantitatively,at county level,a 1%increase in tobacco farming area corresponds to a 0.094%decrease in endemic higher plant species richness across the entire province.These results underscore the need for targeted and region-specific regulations to mitigate biodiversity loss and promote sustainable development in Yunnan Province.The integrated approach used in this study provides a comprehensive assessment of the tobacco-biodiversity trade-offs,offering actionable insights for policymaking.展开更多
The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean.The abundance and distribution of I.argentinus are associated with clim...The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean.The abundance and distribution of I.argentinus are associated with climate change and environmental fluctuations.The potential distribution of I.argentinus was modeled with various environmental variables including sea surface temperature(SST),sea surface height(SSH),chlorophyll a,sea surface salinity(SSS),net primary productivity(NPP),mixed layer depth(MLD),eddy kinetic energy(EKE),and photosynthetically active radiation(PAR)using the maximum entropy(MaxEnt)approach during the peak fishing seasons(January–April).The habitat suitability index(HSI)was defined as the probability of species emergence from the MaxEnt model and the area of HSI≥0.6 was regarded as suitable.Results indicate that the predicted habitat correlated with the actual fishing position,with similar trends in the percentages of suitable habitats and catch per unit effort(CPUE)of I.argentinus from January to April.Moreover,SST,SSH,PAR,and MLD were identified critical environmental variables for the distribution of I.argentinus.In addition,the median of preferred ranges of the critical environmental variables were concentrated within the suitable habitats of I.argentinus.The Area under the Receiver Operating Characteristic Curve(AUC)was greater than 0.96 for all four months.Variations in latitudinal and longitudinal gravity centers(LATG and LONG)of fishing effort were consistent with latitudinal and longitudinal gravity centers(LATG_H and LONG_H)of the HSI.Our findings suggest that the MaxEnt model is an effective tool to predict the potential distribution of I.argentinus.Meanwhile,SST,SSH,PAR,and MLD should be given with more extensive attention in predicting the potential distribution of I.argentinus,as they are important environmental indicators that can help decision-makers search for the fishing ground of I.argentinus in the Southwest Atlantic.展开更多
This work (in two parts) will present a novel predictive modeling methodology aimed at obtaining “best-estimate results with reduced uncertainties” for the first four moments (mean values, covariance, skewness and k...This work (in two parts) will present a novel predictive modeling methodology aimed at obtaining “best-estimate results with reduced uncertainties” for the first four moments (mean values, covariance, skewness and kurtosis) of the optimally predicted distribution of model results and calibrated model parameters, by combining fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters. Underlying the construction of this fourth-order predictive modeling methodology is the “maximum entropy principle” which is initially used to obtain a novel closed-form expression of the (moments-constrained) fourth-order Maximum Entropy (MaxEnt) probability distribution constructed from the first four moments (means, covariances, skewness, kurtosis), which are assumed to be known, of an otherwise unknown distribution of a high-dimensional multivariate uncertain quantity of interest. This fourth-order MaxEnt distribution provides optimal compatibility of the available information while simultaneously ensuring minimal spurious information content, yielding an estimate of a probability density with the highest uncertainty among all densities satisfying the known moment constraints. Since this novel generic fourth-order MaxEnt distribution is of interest in its own right for applications in addition to predictive modeling, its construction is presented separately, in this first part of a two-part work. The fourth-order predictive modeling methodology that will be constructed by particularizing this generic fourth-order MaxEnt distribution will be presented in the accompanying work (Part-2).展开更多
Marine environmental design parameter extrapolation has important applications in marine engineering and coastal disaster prevention.The distribution models used for environmental design parameter usually pass the hyp...Marine environmental design parameter extrapolation has important applications in marine engineering and coastal disaster prevention.The distribution models used for environmental design parameter usually pass the hypothesis tests in statistical analysis,but the calculation results of different distribution models often vary largely.In this paper,based on the information entropy,the overall uncertainty test criteria were studied for commonly used distributions including Gumbel,Weibull,and Pearson-III distribution.An improved method for parameter estimation of the maximum entropy distribution model is proposed on the basis of moment estimation.The study in this paper shows that the number of sample data and the degree of dispersion are proportional to the information entropy,and the overall uncertainty of the maximum entropy distribution model is minimal compared with other models.展开更多
【目的】研究香料烟在云南的气候适生区,为其合理种植提供理论依据。【方法】使用ArcGIS将气候数据结合地形校正进行协同克里金插值,利用最大熵(maximum entropy,MaxEnt)模型筛选影响香料烟分布的气象因子,最后使用ArcGIS对云南省香料...【目的】研究香料烟在云南的气候适生区,为其合理种植提供理论依据。【方法】使用ArcGIS将气候数据结合地形校正进行协同克里金插值,利用最大熵(maximum entropy,MaxEnt)模型筛选影响香料烟分布的气象因子,最后使用ArcGIS对云南省香料烟的气候适生区进行评价。【结果】MaxEnt模型的曲线下面积(the area under curve,AUC)值为0.993,可精准预测云南省香料烟的气候适生区。影响香料烟在云南省分布的气象因子为2月降雨量、1月日照时间、3月日照时间、3月平均气温、3月降雨量、4月降雨量、1月降雨量、2月日照时间和4月最高气温。香料烟在云南省的最适宜种植区(四级适生区)主要分布在保山、德宏和临沧;适宜种植区(三级适生区)主要分布在保山、德宏、临沧、玉溪、楚雄和大理。MaxEnt模型预测结果与香料烟种植区拟合度较高,其种植区主要分布在四级和三级适生区,极少数分布在二级和一级适生区。【结论】云南省适合种植香料烟的地区主要在西南部,适宜种植区主要为沿怒江、澜沧江、黑惠江及其支流的干热河谷地区。2月降雨量、1月日照时间、3月日照时间和3月平均气温是影响香料烟在云南种植的主要气象因子。展开更多
The maximum entropy spectral characteristics of seismicity in the seismic enhanced region of 11 great earthquakes is analysed in this paper to seek the difference of seismic period spectral structure between the norm...The maximum entropy spectral characteristics of seismicity in the seismic enhanced region of 11 great earthquakes is analysed in this paper to seek the difference of seismic period spectral structure between the normal and the abnormal stage of seismic activity in this paper. The results show that, during decades or even one hundred years before great earthquakes, only short periods with 6.5～24.3 years appear, and long ones disappear. Otherwise, long periods with 18.5～38.5 years exist chiefly within the normal stages. Decades years after great earthquakes, the period spectra of seismicity are generally about several or ten years. Then the characteristics of great earthquakes is explained physically by applying the strong body seismogenic model, so a method of studying and predicting great earthquakes is offered.展开更多
A grey model with periodic term for sea-level analysis is presented.The present model keeps some advantages of tea GM (1, 1 )model, which well reflects the trend of sea-level changes and gives out the change rate as ...A grey model with periodic term for sea-level analysis is presented.The present model keeps some advantages of tea GM (1, 1 )model, which well reflects the trend of sea-level changes and gives out the change rate as well as the acceleration of sea level conveniently.level conveniently.In addition, the present model can reproduce the periodic phenomena of sealevel, hence, it overcomes the shortcomings of the GM(1,1) model that is unsuitable for forecasting monthly mean sealevel with apparent periodicity, and its prediction accuracy is improved.The present model is used to analyse Guangxi coast sea level,the results show that the rise rates of relative sea level at Beihai, Weizhou and Bailongwei are 1 .67,2 .51 and 0.89 mm/a respectively, the relative sea level at Shitoubu has a falling trend with a rate of 0. 5- 1 .0 mm/a, the rise rate of eustatic sea level along the Guangxi coast is 2 .0 mm/a. In comparison with the model with a lineartrend term plus a periodic term, the simulation accuracies of both models are about the same.展开更多
The efficiency at the maximum power(EMP)for finite-time Carnot engines established with the low-dissipation model,relies significantly on the assumption of the inverse proportion scaling of the irreversible entropy ge...The efficiency at the maximum power(EMP)for finite-time Carnot engines established with the low-dissipation model,relies significantly on the assumption of the inverse proportion scaling of the irreversible entropy generationΔS^(ir)on the operation timeτ,i.e.ΔS^(ir)∝1/τ.The optimal operation time of the finite-time isothermal process for EMP has to be within the valid regime of the inverse proportion scaling.Yet,such consistency was not tested due to the unknown coefficient of the 1/τ-scaling.In this paper,we reveal that the optimization of the finite-time two-level atomic Carnot engines with the low-dissipation model is consistent only in the regime ofη_(C)<<2(1-δ)/(1+δ),whereη_(C)is the Carnot efficiency,andδis the compression ratio in energy level difference of the heat engine cycle.In the large-η_(C)regime,the operation time for EMP obtained with the low-dissipation model is not within the valid regime of the 1/τ-scaling,and the exact EMP of the engine is found to surpass the well-known boundη_(C)=η_(C)/(2-η_(C)).展开更多
In this paper,an effective algorithm for optimizing the subarray of conformal arrays is proposed.The method first divides theconformal array into several first-level subarrays.It uses the X algorithm to solve the feas...In this paper,an effective algorithm for optimizing the subarray of conformal arrays is proposed.The method first divides theconformal array into several first-level subarrays.It uses the X algorithm to solve the feasible solution of first-level subarray tiling and employs the particle swarm algorithm to optimize the conformal array subarray tiling scheme with the maximum entropy of the planar mapping as the fitness function.Subsequently,convex optimization is applied to optimize the subarray amplitude phase.Data results verify that the method can effectively find the optimal conformal array tiling scheme.展开更多
基金the auspices of A Category of Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA20010101)。
文摘The spatial interaction model is an effective way to explore the geographical disparities inherent in the Belt and Road Initiative(BRI) by simulating spatial flows. The traditional gravity model implies the hypothesis of equilibrium points without any reference to when or how to achieve it. In this paper, a dynamic gravity model was established based on the Maximum Entropy(MaxEnt) theory to estimate and monitor the interconnection intensity and dynamic characters of bilateral relations. In order to detect the determinants of interconnection intensity, a Geodetector method was applied to identify and evaluate the determinants of spatial networks in five dimensions. The empirical study clearly demonstrates a heterogeneous and non-circular spatial structure. The main driving forces of spatial-temporal evolution are foreign direct investment, tourism and railway infrastructure construction, while determinants in different sub-regions show obvious spatial differentiation. Southeast Asian countries are typically multi-island area where aviation infrastructure plays a more important role. North and Central Asian countries regard oil as a pillar industry where power and port facilities have a greater impact on the interconnection. While Western Asian countries are mostly influenced by the railway infrastructure, Eastern European countries already have relatively robust infrastructure where tariff policies provide a greater impetus.
基金Under the auspices of National Basic Research Program of China (No.2010CB951704)Institutional Consolidation for Coordinated and Integrated Monitoring of Natural Resources towards Sustainable Development and Environmental Conservation in the Hindu Kush-Karakoram-Himalaya Mountain Complex (No.76444-000)External Cooperation Program of Chinese Academy of Sciences (No.GJHZ0954)
文摘Tibetan spruce (Picea smithiana) is an endemic species of the Himalayas,and it distributes only in a re-stricted area with very low number.To address the lack of detailed distributional information,we used maximum en-tropy (Maxent) niche-based model to predict the species' potential distribution from limited occurrence-only records.The location data of P.smithiana,relative bioclimatic variables,vegetation data,digital elevation model (DEM),and the derived data were analyzed in Maxent.The receiver operating characteristic (ROC) curve was applied to assess the prediction accuracy.The Maxent jackknife test was performed to quantify the training gains from data layers and the response of P.smithiana distribution to four typical environmental variables was analyzed.Results show that the model performs well at the regional scale.There is a potential for continued expansion of P.smithiana population numbers and distribution in China.P.smithiana potentially distributes in the lower reaches of Gyirong Zangbo and Poiqu rivers in Gyirong and Nyalam counties in Qomolangma (Mount Everest) National Nature Preserve (QNNP),China.The species prefers warm temperate climate in mountain area and mainly distributes in needle-leaved evergreen closed to open forest and mixed forest along the river valley at relatively low altitudes of about 2000-3000 m.Model simulations suggest that distribution patterns of rare species with few species numbers can be well predicted by Max-ent.
基金Supported by National Natural Science Foundation of China (No.60504021).
文摘This letter presents a new chunking method based on Maximum Entropy (ME) model with N-fold template correction model.First two types of machine learning models are described.Based on the analysis of the two models,then the chunking model which combines the profits of conditional probability model and rule based model is proposed.The selection of features and rule templates in the chunking model is discussed.Experimental results for the CoNLL-2000 corpus show that this approach achieves impressive accuracy in terms of the F-score:92.93%.Compared with the ME model and ME Markov model,the new chunking model achieves better performance.
基金Supported by the National Natural Science Foundation of China as key program (No.60435020) and The HighTechnology Research and Development Programme of China (2002AA117010-09).
文摘This paper applied Maximum Entropy (ME) model to Pinyin-To-Character (PTC) conversion in-stead of Hidden Markov Model (HMM) that could not include complicated and long-distance lexical informa-tion. Two ME models were built based on simple and complex templates respectively, and the complex one gave better conversion result. Furthermore, conversion trigger pair of y A → y B cBwas proposed to extract the long-distance constrain feature from the corpus; and then Average Mutual Information (AMI) was used to se-lect conversion trigger pair features which were added to the ME model. The experiment shows that conver-sion error of the ME with conversion trigger pairs is reduced by 4% on a small training corpus, comparing with HMM smoothed by absolute smoothing.
文摘The maximum entropy principle(MEP) is one of the first methods which have been used to predict droplet size and velocity distributions of liquid sprays. This method needs a mean droplets diameter as an input to predict the droplet size distribution. This paper presents a new sub-model based on the deterministic aspects of liquid atomization process independent of the experimental data to provide the mean droplets diameter for using in the maximum entropy formulation(MEF). For this purpose, a theoretical model based on the approach of energy conservation law entitled energy-based model(EBM) is presented. Based on this approach, atomization occurs due to the kinetic energy loss. Prediction of the combined model(MEF/EBM) is in good agreement with the available experimental data. The energy-based model can be used as a fast and reliable enough model to obtain a good estimation of the mean droplets diameter of a spray and the combined model(MEF/EBM) can be used to well predict the droplet size distribution at the primary breakup.
基金Supported bythe National Research Foundationforthe Doctoral Program of Higher Education of China(20030145029) the Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of the Ministry ofEducation
文摘The maximum entropy model was introduced and a new intrusion detection approach based on the maximum entropy model was proposed. The vector space model was adopted for data presentation. The minimal entropy partitioning method was utilized for attribute diseretization. Experiments on the KDD CUP 1999 standard data set were designed and the experimental results were shown. The receiver operating eharaeteristie（ROC） curve analysis approach was utilized to analyze the experimental results. The analysis results show that the proposed approach is comparable to those based on support vector maehine（SVM） and outperforms those based on C4.5 and Naive Bayes classifiers. According to the overall evaluation result, the proposed approach is a little better than those based on SVM.
基金funded by National Key R&D Program of China(No. 2021YFC2600400)National Natural Science Foundation of China(No. 32171794)Forestry Science and Technology Innovation Special of Jiangxi Forestry Department (No. 201912)
文摘Background: Hylurgus ligniperda(Fabricius) is native to Europe but has established populations in many countries and regions. H. ligniperda mainly infests Pinus species, and can cause severe weakness and even death of the host through its boring activity;it can also be a vector of various pathogenic fungi. This study was conducted to investigate the environmental variables limiting the distribution of H. ligniperda and the change trend of its suitable areas under climate change.Results: We used a maximum entropy model to predict the potential geographical distribution of H. ligniperda on a global scale under near current and future climatic scenarios using its occurrence data and environmental variables. The result shows that the areas surrounding the Mediterranean region, the eastern coastal areas of Asia, and the southeastern part of Oceania are highly suitable for H. ligniperda. The environmental variables with the greatest effect on the distribution of H. ligniperda were determined using the jackknife method and Pearson’s correlation analysis and included the monthly average maximum temperature in April, precipitation of driest quarter, the monthly average minimum temperature in December, precipitation of coldest quarter, mean temperature of driest quarter and mean diurnal range.Conclusions: Excessive precipitation in winter and low temperatures in spring had a great effect on the distribution of H. ligniperda. The potential geographical distribution of H. ligniperda was predicted to change under future climatic conditions compared with near current climate conditions. Highly suitable areas, moderately suitable areas and low suitable areas were predicted to increase by 59.99%, 44.43% and 22.92%, respectively, under the2081–2100 ssp245 scenario.
基金Project supported by the National Natural Science Foundation of China (No. 60272031), and Technology Plan Program of ZhejiangProvince (No. 2003C21010), and Zhejiang Provincial Natural Sci-ence Foundation of China (No. M603202)
文摘Detecting objects of interest from a video sequence is a fundamental and critical task in automated visual surveillance. Most current approaches only focus on discriminating moving objects by background subtraction whether or not the objects of interest can be moving or stationary. In this paper, we propose layers segmentation to detect both moving and stationary target objects from surveillance video. We extend the Maximum Entropy (ME) statistical model to segment layers with features, which are collected by constructing a codebook with a set of codewords for each pixel. We also indicate how the training models are used for the discrimination of target objects in surveillance video. Our experimental results are presented in terms of the success rate and the segmenting precision.
文摘The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming and higher plant species diversity,and to identify priority counties for conservation.We employed an integrated approach combining species distribution modeling,GIS overlay analysis,and empirical spatial regression to em pirically assess the impact of tobacco farming intensity on biodiversity risk.Our findings reveal a compelling negative spatial correlation between tobacco farming expansion and higher plant species diversity.Specifically,southern counties in Wenshan and Honghe prefectures are major priority areas of conservation that exhibit signif icant spatial correlations between biodiversity risks and high tobacco farming intensity.Quantitatively,at county level,a 1%increase in tobacco farming area corresponds to a 0.094%decrease in endemic higher plant species richness across the entire province.These results underscore the need for targeted and region-specific regulations to mitigate biodiversity loss and promote sustainable development in Yunnan Province.The integrated approach used in this study provides a comprehensive assessment of the tobacco-biodiversity trade-offs,offering actionable insights for policymaking.
基金Supported by the Natural Science Foundation of Shanghai(No.23ZR1427100)the National Key R&D Program of China(No.2023YFD2401303)the Shanghai Talent Development Funding for the Project(No.2021078)。
文摘The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean.The abundance and distribution of I.argentinus are associated with climate change and environmental fluctuations.The potential distribution of I.argentinus was modeled with various environmental variables including sea surface temperature(SST),sea surface height(SSH),chlorophyll a,sea surface salinity(SSS),net primary productivity(NPP),mixed layer depth(MLD),eddy kinetic energy(EKE),and photosynthetically active radiation(PAR)using the maximum entropy(MaxEnt)approach during the peak fishing seasons(January–April).The habitat suitability index(HSI)was defined as the probability of species emergence from the MaxEnt model and the area of HSI≥0.6 was regarded as suitable.Results indicate that the predicted habitat correlated with the actual fishing position,with similar trends in the percentages of suitable habitats and catch per unit effort(CPUE)of I.argentinus from January to April.Moreover,SST,SSH,PAR,and MLD were identified critical environmental variables for the distribution of I.argentinus.In addition,the median of preferred ranges of the critical environmental variables were concentrated within the suitable habitats of I.argentinus.The Area under the Receiver Operating Characteristic Curve(AUC)was greater than 0.96 for all four months.Variations in latitudinal and longitudinal gravity centers(LATG and LONG)of fishing effort were consistent with latitudinal and longitudinal gravity centers(LATG_H and LONG_H)of the HSI.Our findings suggest that the MaxEnt model is an effective tool to predict the potential distribution of I.argentinus.Meanwhile,SST,SSH,PAR,and MLD should be given with more extensive attention in predicting the potential distribution of I.argentinus,as they are important environmental indicators that can help decision-makers search for the fishing ground of I.argentinus in the Southwest Atlantic.
文摘This work (in two parts) will present a novel predictive modeling methodology aimed at obtaining “best-estimate results with reduced uncertainties” for the first four moments (mean values, covariance, skewness and kurtosis) of the optimally predicted distribution of model results and calibrated model parameters, by combining fourth-order experimental and computational information, including fourth (and higher) order sensitivities of computed model responses to model parameters. Underlying the construction of this fourth-order predictive modeling methodology is the “maximum entropy principle” which is initially used to obtain a novel closed-form expression of the (moments-constrained) fourth-order Maximum Entropy (MaxEnt) probability distribution constructed from the first four moments (means, covariances, skewness, kurtosis), which are assumed to be known, of an otherwise unknown distribution of a high-dimensional multivariate uncertain quantity of interest. This fourth-order MaxEnt distribution provides optimal compatibility of the available information while simultaneously ensuring minimal spurious information content, yielding an estimate of a probability density with the highest uncertainty among all densities satisfying the known moment constraints. Since this novel generic fourth-order MaxEnt distribution is of interest in its own right for applications in addition to predictive modeling, its construction is presented separately, in this first part of a two-part work. The fourth-order predictive modeling methodology that will be constructed by particularizing this generic fourth-order MaxEnt distribution will be presented in the accompanying work (Part-2).
基金This research was financially supported by the National Natural Science Foundation of China(Grant Nos.52071306 and 51379195)the Natural Science Foundation of Shandong Province(Grant No.ZR2019MEE050).
文摘Marine environmental design parameter extrapolation has important applications in marine engineering and coastal disaster prevention.The distribution models used for environmental design parameter usually pass the hypothesis tests in statistical analysis,but the calculation results of different distribution models often vary largely.In this paper,based on the information entropy,the overall uncertainty test criteria were studied for commonly used distributions including Gumbel,Weibull,and Pearson-III distribution.An improved method for parameter estimation of the maximum entropy distribution model is proposed on the basis of moment estimation.The study in this paper shows that the number of sample data and the degree of dispersion are proportional to the information entropy,and the overall uncertainty of the maximum entropy distribution model is minimal compared with other models.
文摘【目的】研究香料烟在云南的气候适生区,为其合理种植提供理论依据。【方法】使用ArcGIS将气候数据结合地形校正进行协同克里金插值,利用最大熵(maximum entropy,MaxEnt)模型筛选影响香料烟分布的气象因子,最后使用ArcGIS对云南省香料烟的气候适生区进行评价。【结果】MaxEnt模型的曲线下面积(the area under curve,AUC)值为0.993,可精准预测云南省香料烟的气候适生区。影响香料烟在云南省分布的气象因子为2月降雨量、1月日照时间、3月日照时间、3月平均气温、3月降雨量、4月降雨量、1月降雨量、2月日照时间和4月最高气温。香料烟在云南省的最适宜种植区(四级适生区)主要分布在保山、德宏和临沧;适宜种植区(三级适生区)主要分布在保山、德宏、临沧、玉溪、楚雄和大理。MaxEnt模型预测结果与香料烟种植区拟合度较高,其种植区主要分布在四级和三级适生区,极少数分布在二级和一级适生区。【结论】云南省适合种植香料烟的地区主要在西南部,适宜种植区主要为沿怒江、澜沧江、黑惠江及其支流的干热河谷地区。2月降雨量、1月日照时间、3月日照时间和3月平均气温是影响香料烟在云南种植的主要气象因子。
文摘The maximum entropy spectral characteristics of seismicity in the seismic enhanced region of 11 great earthquakes is analysed in this paper to seek the difference of seismic period spectral structure between the normal and the abnormal stage of seismic activity in this paper. The results show that, during decades or even one hundred years before great earthquakes, only short periods with 6.5～24.3 years appear, and long ones disappear. Otherwise, long periods with 18.5～38.5 years exist chiefly within the normal stages. Decades years after great earthquakes, the period spectra of seismicity are generally about several or ten years. Then the characteristics of great earthquakes is explained physically by applying the strong body seismogenic model, so a method of studying and predicting great earthquakes is offered.
文摘A grey model with periodic term for sea-level analysis is presented.The present model keeps some advantages of tea GM (1, 1 )model, which well reflects the trend of sea-level changes and gives out the change rate as well as the acceleration of sea level conveniently.level conveniently.In addition, the present model can reproduce the periodic phenomena of sealevel, hence, it overcomes the shortcomings of the GM(1,1) model that is unsuitable for forecasting monthly mean sealevel with apparent periodicity, and its prediction accuracy is improved.The present model is used to analyse Guangxi coast sea level,the results show that the rise rates of relative sea level at Beihai, Weizhou and Bailongwei are 1 .67,2 .51 and 0.89 mm/a respectively, the relative sea level at Shitoubu has a falling trend with a rate of 0. 5- 1 .0 mm/a, the rise rate of eustatic sea level along the Guangxi coast is 2 .0 mm/a. In comparison with the model with a lineartrend term plus a periodic term, the simulation accuracies of both models are about the same.
基金supported by the National Natural Science Foundation of China(NSFC)(Grants No.11534002,No.11875049,No.U1730449,No.U1530401,No.U1930403)the National Basic Research Program of China(Grant No.2016YFA0301201)the China Postdoctoral Science Foundation(Grant No.BX2021030)。
文摘The efficiency at the maximum power(EMP)for finite-time Carnot engines established with the low-dissipation model,relies significantly on the assumption of the inverse proportion scaling of the irreversible entropy generationΔS^(ir)on the operation timeτ,i.e.ΔS^(ir)∝1/τ.The optimal operation time of the finite-time isothermal process for EMP has to be within the valid regime of the inverse proportion scaling.Yet,such consistency was not tested due to the unknown coefficient of the 1/τ-scaling.In this paper,we reveal that the optimization of the finite-time two-level atomic Carnot engines with the low-dissipation model is consistent only in the regime ofη_(C)<<2(1-δ)/(1+δ),whereη_(C)is the Carnot efficiency,andδis the compression ratio in energy level difference of the heat engine cycle.In the large-η_(C)regime,the operation time for EMP obtained with the low-dissipation model is not within the valid regime of the 1/τ-scaling,and the exact EMP of the engine is found to surpass the well-known boundη_(C)=η_(C)/(2-η_(C)).
基金supported by the Advanced Functional Composites Technology Key Laboratory Fund under Grant No.6142906220404Sichuan Province Centralized Guided Local Science and Technology Development Special Project under Grant No.2022ZYD0121。
文摘In this paper,an effective algorithm for optimizing the subarray of conformal arrays is proposed.The method first divides theconformal array into several first-level subarrays.It uses the X algorithm to solve the feasible solution of first-level subarray tiling and employs the particle swarm algorithm to optimize the conformal array subarray tiling scheme with the maximum entropy of the planar mapping as the fitness function.Subsequently,convex optimization is applied to optimize the subarray amplitude phase.Data results verify that the method can effectively find the optimal conformal array tiling scheme.
