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
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
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
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 accurate and timely traffic state prediction has become increasingly important for the traffic participants,especially for the traffic managements.In this paper,the traffic state is described by Micro-LOS,and a di...The accurate and timely traffic state prediction has become increasingly important for the traffic participants,especially for the traffic managements.In this paper,the traffic state is described by Micro-LOS,and a direct prediction method is introduced.The development of the proposed method is based on Maximum Entropy(ME)models trained for multiple modes.In the Multimode Maximum Entropy(MME)framework,the different features like temporal and spatial features of traffic systems,regional traffic state are integrated simultaneously,and the different state behaviors based on 14 traffic modes defined by average speed according to the date-time division are also dealt with.The experiments based on the real data in Beijing expressway prove that the MME models outperforms the already existing model in both effectiveness and robustness.展开更多
The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is ...The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is the key to design a better VSMM.However,MSA methods in the literature have big room to improve both theoretically and practically.To this end,we propose a feedback structure based entropy approach that could fnd the model sequence sets with the smallest size under certain conditions.The fltered data are fed back in real time and can be used by the minimum entropy（ME）based VSMM algorithms,i.e.,MEVSMM.Firstly,the full Markov chains are used to achieve optimal solutions.Secondly,the myopic method together with particle flter（PF）and the challenge match algorithm are also used to achieve sub-optimal solutions,a trade-off between practicability and optimality.The numerical results show that the proposed algorithm provides not only refned model sets but also a good robustness margin and very high accuracy.展开更多
A shot presents a contiguous action recorded by an uninterrupted camera operation and frames within a shot keep spatio-temporal coherence. Segmenting a serial video stream file into meaningful shots is the first pass ...A shot presents a contiguous action recorded by an uninterrupted camera operation and frames within a shot keep spatio-temporal coherence. Segmenting a serial video stream file into meaningful shots is the first pass for the task of video analysis, content-based video understanding. In this paper, a novel scheme based on improved two-dimensional entropy is proposed to complete the partition of video shots. Firstly, shot transition candidates are detected using a two-pass algorithm： a coarse searching pass and a fine searching pass. Secondly, with the character of two-dimensional entropy of the image, correctly detected transition candidates are further classified into different transition types whereas those falsely detected shot breaks are distinguished and removed. Finally, the boundary of gradual transition can be precisely located by merging the characters of two-dimensional entropy of the image into the gradual transition. A large number of video sequences are used to test our system performance and promising results are obtained.展开更多
The resolution of overlapping ambiguity strings(OAS)is studied based on the maximum entropy model.There are two model outputs,where either the first two characters form a word or the last two characters form a word.Th...The resolution of overlapping ambiguity strings(OAS)is studied based on the maximum entropy model.There are two model outputs,where either the first two characters form a word or the last two characters form a word.The features of the model include one word in con-text of OAS,the current OAS and word probability relation of two kinds of segmentation results.OAS in training text is found by the combination of the FMM and BMM segmen-tation method.After feature tagging they are used to train the maximum entropy model.The People Daily corpus of January 1998 is used in training and testing.Experimental results show a closed test precision of 98.64%and an open test precision of 95.01%.The open test precision is 3.76%better compared with that of the precision of common word probability method.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
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
The paper discusses an extended entropy model for the prediction of trip amount and provides a method to solve it, called the simple block iterative algorithm, from the point of view of the system of nonlinear equatio...The paper discusses an extended entropy model for the prediction of trip amount and provides a method to solve it, called the simple block iterative algorithm, from the point of view of the system of nonlinear equations. Because the algorithm gives consideration to the characteristic of the model, it has better effect in our practice. The paper also studies the existence and uniqueness of the solution and convergence of the algorithm.展开更多
The research of groundwater vulnerability is the basic work to protect the groundwater. For utilizing groundwater resource continuably, groundwater vulnerability evaluation is necessary. Useful reference to protect, e...The research of groundwater vulnerability is the basic work to protect the groundwater. For utilizing groundwater resource continuably, groundwater vulnerability evaluation is necessary. Useful reference to protect, exploit and utilize on groundwater resource are provided rationally. According to the real condition of Sanjiang Plain, the indexes system is established based on the traditional DRASTIC model. The new system includes the following seven indexes： Depth of Water, Net Recharge, Aquifer Media, Soil Media, Conductivity of the Aquifer, Land Utilizing Ratio and Populace Density. The related analysis appears that the system is rather reasonable. Because traditional methods, such as analytic hierarchy process and fuzzy mathematics theory, can＇t be avoided human interference in selection of weights, they could lead to an imprecise result. In order to evaluate the groundwater vulnerability reasonably, entropy weight coefficient method is applied for the first time, which provides a new way to groundwater vulnerability evaluation. The method is a model whose weights are insured by the calculation process, so the artificial disturb can be avoided. It has been used to evaluate the groundwater vulnerability in Sanjiang Plain. The satisfied result is acquired. Comparably, the same result is acquired by the other method named projection pursuit evaluation based on real-coded accelerating genetic algorithm. It shows that entropy weight coefficient method is applicable on groundwater vulnerability evaluation. The evaluation result can provide reference on the decision-making departments.展开更多
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
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
The cause of substorm onset is not yet understood. Chen CX(2016) proposed an entropy switch model, in which substorm onset results from the development of interchange instability. In this study, we sought observationa...The cause of substorm onset is not yet understood. Chen CX(2016) proposed an entropy switch model, in which substorm onset results from the development of interchange instability. In this study, we sought observational evidence for this model by using Time History of Events and Macroscale Interactions during Substorms(THEMIS) data. We examined two events, one with and the other without a streamer before substorm onset. In contrast to the stable magnetosphere, where the total magnetic field strength is a decreasing function and entropy is an increasing function of the downtail distance, in both events the total magnetic field strength and entropy were reversed before substorm onset. After onset, the total magnetic field strength, entropy, and other plasma quantities fluctuated. In addition, a statistical study was performed. By confining the events with THEMIS satellites located in the downtail region between ~8 and ~12 Earth radii, and 3 hours before and after midnight, we found the occurrence rate of the total magnetic field strength reversal to be 69% and the occurrence rate of entropy reversal to be 77% of the total 205 events.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
This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qu...This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality.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
This paper establishes a new model for calculation of the standard entropies of solid binary oxides as follows: S_(29)=27.07×Φ_1+1.120×Φ_2+n_1×k×Φ, -22.19 e.u (R=0.9960) We have invesigated 103 ...This paper establishes a new model for calculation of the standard entropies of solid binary oxides as follows: S_(29)=27.07×Φ_1+1.120×Φ_2+n_1×k×Φ, -22.19 e.u (R=0.9960) We have invesigated 103 binary oxides. and found good agreemenl between estimated and experimental entropies.展开更多
In order to establish a comprehensive food quality evaluation method,2 mathematical modeling evaluation methods were applied(grey system and entropy weight method).The experimental material was Flammulina velutipes fe...In order to establish a comprehensive food quality evaluation method,2 mathematical modeling evaluation methods were applied(grey system and entropy weight method).The experimental material was Flammulina velutipes feet(FVF).The by-product of F.velutipes was divided into 3 equal portions for frying,and the resulting fried FVF(FFVF)were evaluated.Based on the ranking of 50 people's food attribute preferences,grey relational analysis(grey system)was used for subjective evaluation.The results showed that people's preference ranking for the 3 parts was:lower>middle>upper.The entropy weight method was then used to verify the results based on the FFVF nutritional indexes(total sugars,protein and dietary fiber)and flavor indexes(flavor amino acids,flavor 5'-nucleotides and electronic tongue flavor score).The validation results were lower>middle>upper,which was consistent with the subjective evaluation results,suggesting the lower part of FVF was more suitable for the frying process.In conclusion,values of different parts of FFVF were rated,which provided a new processing method for the utilization of F.velutipes by-products.It also provided a novel means for the evaluation of processed products in food engineering.展开更多
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.
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.
基金supported by Beijing Science Foundation Plan Project(Grant No.D07020601400707)the National High Technology Re-search and Development Program of China(Grant NO.2006AA11Z231)
文摘The accurate and timely traffic state prediction has become increasingly important for the traffic participants,especially for the traffic managements.In this paper,the traffic state is described by Micro-LOS,and a direct prediction method is introduced.The development of the proposed method is based on Maximum Entropy(ME)models trained for multiple modes.In the Multimode Maximum Entropy(MME)framework,the different features like temporal and spatial features of traffic systems,regional traffic state are integrated simultaneously,and the different state behaviors based on 14 traffic modes defined by average speed according to the date-time division are also dealt with.The experiments based on the real data in Beijing expressway prove that the MME models outperforms the already existing model in both effectiveness and robustness.
基金supported in part by National Basic Research Program of China(No.2012CB821200)in part by the National Natural Science Foundation of China(No.61174024)
文摘The variable-structure multiple-model（VSMM）approach,one of the multiple-model（MM）methods,is a popular and effective approach in handling problems with mode uncertainties.The model sequence set adaptation（MSA）is the key to design a better VSMM.However,MSA methods in the literature have big room to improve both theoretically and practically.To this end,we propose a feedback structure based entropy approach that could fnd the model sequence sets with the smallest size under certain conditions.The fltered data are fed back in real time and can be used by the minimum entropy（ME）based VSMM algorithms,i.e.,MEVSMM.Firstly,the full Markov chains are used to achieve optimal solutions.Secondly,the myopic method together with particle flter（PF）and the challenge match algorithm are also used to achieve sub-optimal solutions,a trade-off between practicability and optimality.The numerical results show that the proposed algorithm provides not only refned model sets but also a good robustness margin and very high accuracy.
基金Supported by the National Natural Science Foundation of China (Grant No.60675017)National Basic Research Program of China (Grant No.2006CB303103)
文摘A shot presents a contiguous action recorded by an uninterrupted camera operation and frames within a shot keep spatio-temporal coherence. Segmenting a serial video stream file into meaningful shots is the first pass for the task of video analysis, content-based video understanding. In this paper, a novel scheme based on improved two-dimensional entropy is proposed to complete the partition of video shots. Firstly, shot transition candidates are detected using a two-pass algorithm： a coarse searching pass and a fine searching pass. Secondly, with the character of two-dimensional entropy of the image, correctly detected transition candidates are further classified into different transition types whereas those falsely detected shot breaks are distinguished and removed. Finally, the boundary of gradual transition can be precisely located by merging the characters of two-dimensional entropy of the image into the gradual transition. A large number of video sequences are used to test our system performance and promising results are obtained.
文摘The resolution of overlapping ambiguity strings(OAS)is studied based on the maximum entropy model.There are two model outputs,where either the first two characters form a word or the last two characters form a word.The features of the model include one word in con-text of OAS,the current OAS and word probability relation of two kinds of segmentation results.OAS in training text is found by the combination of the FMM and BMM segmen-tation method.After feature tagging they are used to train the maximum entropy model.The People Daily corpus of January 1998 is used in training and testing.Experimental results show a closed test precision of 98.64%and an open test precision of 95.01%.The open test precision is 3.76%better compared with that of the precision of common word probability method.
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 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The paper discusses an extended entropy model for the prediction of trip amount and provides a method to solve it, called the simple block iterative algorithm, from the point of view of the system of nonlinear equations. Because the algorithm gives consideration to the characteristic of the model, it has better effect in our practice. The paper also studies the existence and uniqueness of the solution and convergence of the algorithm.
基金Supported by the National Natural Science Foundation of China(30400275)the Tackle Key Problems of Heilongjiang Province(the Hobbledehoy Science Fund of Heilongjiang Province)(QC04C28)
文摘The research of groundwater vulnerability is the basic work to protect the groundwater. For utilizing groundwater resource continuably, groundwater vulnerability evaluation is necessary. Useful reference to protect, exploit and utilize on groundwater resource are provided rationally. According to the real condition of Sanjiang Plain, the indexes system is established based on the traditional DRASTIC model. The new system includes the following seven indexes： Depth of Water, Net Recharge, Aquifer Media, Soil Media, Conductivity of the Aquifer, Land Utilizing Ratio and Populace Density. The related analysis appears that the system is rather reasonable. Because traditional methods, such as analytic hierarchy process and fuzzy mathematics theory, can＇t be avoided human interference in selection of weights, they could lead to an imprecise result. In order to evaluate the groundwater vulnerability reasonably, entropy weight coefficient method is applied for the first time, which provides a new way to groundwater vulnerability evaluation. The method is a model whose weights are insured by the calculation process, so the artificial disturb can be avoided. It has been used to evaluate the groundwater vulnerability in Sanjiang Plain. The satisfied result is acquired. Comparably, the same result is acquired by the other method named projection pursuit evaluation based on real-coded accelerating genetic algorithm. It shows that entropy weight coefficient method is applicable on groundwater vulnerability evaluation. The evaluation result can provide reference on the decision-making departments.
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(Grant No.NSFC41974204)。
文摘The cause of substorm onset is not yet understood. Chen CX(2016) proposed an entropy switch model, in which substorm onset results from the development of interchange instability. In this study, we sought observational evidence for this model by using Time History of Events and Macroscale Interactions during Substorms(THEMIS) data. We examined two events, one with and the other without a streamer before substorm onset. In contrast to the stable magnetosphere, where the total magnetic field strength is a decreasing function and entropy is an increasing function of the downtail distance, in both events the total magnetic field strength and entropy were reversed before substorm onset. After onset, the total magnetic field strength, entropy, and other plasma quantities fluctuated. In addition, a statistical study was performed. By confining the events with THEMIS satellites located in the downtail region between ~8 and ~12 Earth radii, and 3 hours before and after midnight, we found the occurrence rate of the total magnetic field strength reversal to be 69% and the occurrence rate of entropy reversal to be 77% of the total 205 events.
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2024 Key Project of Teaching Reform Research and Practice in Higher Education in Henan Province“Exploration and Practice of Training Model for Outstanding Students in Basic Mechanics Discipline”(2024SJGLX094)Henan Province“Mechanics+X”Basic Discipline Outstanding Student Training Base2024 Research and Practice Project of Higher Education Teaching Reform in Henan University of Science and Technology“Optimization and Practice of Ability-Oriented Teaching Mode for Computational Mechanics Course:A New Exploration in Cultivating Practical Simulation Engineers”(2024BK074)。
文摘This paper takes the assessment and evaluation of computational mechanics course as the background,and constructs a diversified course evaluation system that is student-centered and integrates both quantitative and qualitative evaluation methods.The system not only pays attention to students’practical operation and theoretical knowledge mastery but also puts special emphasis on the cultivation of students’innovative abilities.In order to realize a comprehensive and objective evaluation,the assessment and evaluation method of the entropy weight model combining TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)multi-attribute decision analysis and entropy weight theory is adopted,and its validity and practicability are verified through example analysis.This method can not only comprehensively and objectively evaluate students’learning outcomes,but also provide a scientific decision-making basis for curriculum teaching reform.The implementation of this diversified course evaluation system can better reflect the comprehensive ability of students and promote the continuous improvement of teaching quality.
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.
文摘This paper establishes a new model for calculation of the standard entropies of solid binary oxides as follows: S_(29)=27.07×Φ_1+1.120×Φ_2+n_1×k×Φ, -22.19 e.u (R=0.9960) We have invesigated 103 binary oxides. and found good agreemenl between estimated and experimental entropies.
基金supported by Edible Mushroom Resources Exploitation and the Key Technology Development in Efficient Processing(2018YFD0400200)the Central Guidance on Local Science and Technology Development Project of Liaoning Province(2021JH5/10400011)High-end Talent Introduction Fund of Shenyang Agricultural University(SYAU20160003).
文摘In order to establish a comprehensive food quality evaluation method,2 mathematical modeling evaluation methods were applied(grey system and entropy weight method).The experimental material was Flammulina velutipes feet(FVF).The by-product of F.velutipes was divided into 3 equal portions for frying,and the resulting fried FVF(FFVF)were evaluated.Based on the ranking of 50 people's food attribute preferences,grey relational analysis(grey system)was used for subjective evaluation.The results showed that people's preference ranking for the 3 parts was:lower>middle>upper.The entropy weight method was then used to verify the results based on the FFVF nutritional indexes(total sugars,protein and dietary fiber)and flavor indexes(flavor amino acids,flavor 5'-nucleotides and electronic tongue flavor score).The validation results were lower>middle>upper,which was consistent with the subjective evaluation results,suggesting the lower part of FVF was more suitable for the frying process.In conclusion,values of different parts of FFVF were rated,which provided a new processing method for the utilization of F.velutipes by-products.It also provided a novel means for the evaluation of processed products in food engineering.
