We propose a new quantum watermarking scheme based on threshold selection using informational entropy of quantum image.The core idea of this scheme is to embed information into object and background of cover image in ...We propose a new quantum watermarking scheme based on threshold selection using informational entropy of quantum image.The core idea of this scheme is to embed information into object and background of cover image in different ways.First,a threshold method adopting the quantum informational entropy is employed to determine a threshold value.The threshold value can then be further used for segmenting the cover image to a binary image,which is an authentication key for embedding and extraction information.By a careful analysis of the quantum circuits of the scheme,that is,translating into the basic gate sequences which show the low complexity of the scheme.One of the simulation-based experimental results is entropy difference which measures the similarity of two images by calculating the difference in quantum image informational entropy between watermarked image and cover image.Furthermore,the analyses of peak signal-to-noise ratio,histogram and capacity of the scheme are also provided.展开更多
The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attr...The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.展开更多
Assessment of quantity of information that is present in own noises of EE （electronic elements）--informational noise＇s entropy--using spectrum distribution of noises＇ probability of real elements is proposed. It i...Assessment of quantity of information that is present in own noises of EE （electronic elements）--informational noise＇s entropy--using spectrum distribution of noises＇ probability of real elements is proposed. It is shown that informational noise＇s entropy as opposed to used differential entropy of continuous signals defines the quantity of qualitative information related to the features of element＇s structure. Proposed quantitative assessment of information can be used for calculation of information contained in the own noises of other technical systems.展开更多
Traffic encryption techniques facilitate cyberattackers to hide their presence and activities.Traffic classification is an important method to prevent network threats.However,due to the tremendous traffic volume and l...Traffic encryption techniques facilitate cyberattackers to hide their presence and activities.Traffic classification is an important method to prevent network threats.However,due to the tremendous traffic volume and limitations of computing,most existing traffic classification techniques are inapplicable to the high-speed network environment.In this paper,we propose a High-speed Encrypted Traffic Classification(HETC)method containing two stages.First,to efficiently detect whether traffic is encrypted,HETC focuses on randomly sampled short flows and extracts aggregation entropies with chi-square test features to measure the different patterns of the byte composition and distribution between encrypted and unencrypted flows.Second,HETC introduces binary features upon the previous features and performs fine-grained traffic classification by combining these payload features with a Random Forest model.The experimental results show that HETC can achieve a 94%F-measure in detecting encrypted flows and a 85%–93%F-measure in classifying fine-grained flows for a 1-KB flow-length dataset,outperforming the state-of-the-art comparison methods.Meanwhile,HETC does not need to wait for the end of the flow and can extract mass computing features.The average time for HETC to process each flow is only 2 or 16 ms,which is lower than the flow duration in most cases,making it a good candidate for high-speed traffic classification.展开更多
Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual charac...Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification （CDI） criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1-$6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.展开更多
Rockburst is a dynamic phenomenon accompanied by acoustic emission(AE)activities.It is difficult to predict rockburst accurately.Based on the fast Fourier transform(FFT)method and the information entropy theory,the ev...Rockburst is a dynamic phenomenon accompanied by acoustic emission(AE)activities.It is difficult to predict rockburst accurately.Based on the fast Fourier transform(FFT)method and the information entropy theory,the evolution model of dominant frequency entropy was established.The AE energy,frequency and stress were synthetically considered to predict rockburst.Under the triaxial and the single-face unloading tests,the relationship between AE energy and the development of internal cracks was analyzed.Using the FFT method,the distribution characteristics of AE dominant frequency values were obtained.Based on the information entropy theory,the dominant frequencies evolved patterns were ascertained.It was observed that the evolution models of the dominant frequency entropy were nearly the same and shared a characteristic“undulation-decrease-rise-sharp decrease”pattern.Results show that AE energy will be released suddenly before rockburst.The density of intermediate frequency increased prior to rockburst.The dominant frequency entropy reached a relative maximum value before rockburst,and then decreased sharply.These features could be used as a precursory information for predicting rockburst.The proposed relative maximum value could be as a key point to predict rockburst.This is a meaningful attempt on predicting rockburst.展开更多
The urban ecosystem possesses dissipating structures that can absorb substances and energy from the external environment and export products and wastes to maintain order within the system. Given these circumstances, t...The urban ecosystem possesses dissipating structures that can absorb substances and energy from the external environment and export products and wastes to maintain order within the system. Given these circumstances, this paper analyzed the ability of the urban ecosystem in Guangzhou City to sustain development from the perspective of entropy. The research was carried out in three steps. First, an evaluation index system that considers the ability of the urban ecosystem for sustainable development was formed based on the struc- tures and functions of the urban ecosystem and the change in the entropy of the urban so- cioeconomic ecosystem. Second, the sustainable development ability assessment model for the urban ecosystem was built using information entropy. Last, by combining the time series variation of the evaluation indicators with the entropy weights, this paper analyzed the influ- ence of the combined factors on the sustainable development ability of the urban ecosystem in Guangzhou and suggested some measures to promote the sustainable development of the urban ecosystem in Guangzhou. The conclusions of this study can be summarized as follows： （1） The urban ecosystem has developed in an orderly and healthy direction, with effective control over the urban environmental pollution problems in Guangzhou between 2004 and 2010. （2） The sustainable development ability of the urban ecosystem had been on an up- ward trend in Guangzhou during the study period. The ability of the natural urban ecosystem to support the urban socioeconomic ecosystem increased continuously, and the improved ecoenvironment enhanced the harmony and vitality of the urban ecosystem in Guangzhou.展开更多
For a single-structure deep learning fault diagnosis model,its disadvantages are an insufficient feature extraction and weak fault classification capability.This paper proposes a multi-scale deep feature fusion intell...For a single-structure deep learning fault diagnosis model,its disadvantages are an insufficient feature extraction and weak fault classification capability.This paper proposes a multi-scale deep feature fusion intelligent fault diagnosis method based on information entropy.First,a normal autoencoder,denoising autoencoder,sparse autoencoder,and contractive autoencoder are used in parallel to construct a multi-scale deep neural network feature extraction structure.A deep feature fusion strategy based on information entropy is proposed to obtain low-dimensional features and ensure the robustness of the model and the quality of deep features.Finally,the advantage of the deep belief network probability model is used as the fault classifier to identify the faults.The effectiveness of the proposed method was verified by a gearbox test-bed.Experimental results show that,compared with traditional and existing intelligent fault diagnosis methods,the proposed method can obtain representative information and features from the raw data with higher classification accuracy.展开更多
This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the g...This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the grey value of targets is enhanced by calculating the local energy. Image segmentation based on the adaptive threshold is used to solve the problems that the grey value of noise is enhanced with the grey value improvement of targets. Experimental results show that compared with the adaptive Butterworth high-pass filter method, the proposed algorithm is more effective and faster for the infrared small target detection.展开更多
Configurational information entropy(CIE)theory was employed to determine the neutron-skin thickness of neutron-rich calcium isotopes.The nuclear density distributions and fragment cross sections in 350 MeV/u ^(40-60)C...Configurational information entropy(CIE)theory was employed to determine the neutron-skin thickness of neutron-rich calcium isotopes.The nuclear density distributions and fragment cross sections in 350 MeV/u ^(40-60)Ca+^(9)Be projectile fragmentation reactions were calculated using a modified statistical abrasion-ablation model.CIE quantities were determined from the nuclear density,isotopic,mass,and charge distributions.The linear correlations between the CIE determined using the isotopic,mass,and charge distributions and the neutron-skin thickness of the projectile nucleus show that CIE provides new methods to extract the neutron-skin thickness of neutron-rich nuclei.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
Configurational information entropy(CIE)analysis has been shown to be applicable for determining the neutron skin thickness(δnp)of neutron-rich nuclei from fragment production in projectile fragmentation reactions.Th...Configurational information entropy(CIE)analysis has been shown to be applicable for determining the neutron skin thickness(δnp)of neutron-rich nuclei from fragment production in projectile fragmentation reactions.The BNN+FRACS machine learning model was adopted to predict the fragment mass cross-sections(σ_(A))of the projectile fragmentation reactions induced by calcium isotopes from ^(36)Ca to ^(56)Ca on a ^(9)Be target at 140MeV/u.The fast Fourier transform was adopted to decompose the possible information compositions inσA distributions and determine the quantity of CIE(S_(A)[f]).It was found that the range of fragments significantly influences the quantity of S_(A)[f],which results in different trends of S_(A)[f]~δnp correlation.The linear S_(A)[f]~δnp correlation in a previous study[Nucl.Sci.Tech.33,6(2022)]could be reproduced using fragments with relatively large mass fragments,which verifies that S_(A)[f]determined from fragmentσAis sensitive to the neutron skin thickness of neutron-rich isotopes.展开更多
Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh f...Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh form, involves two parameters: the average wave height H— and the state parameter γ. The role of γ in the distribution of wave heights is examined. It is found that γ may be a certain measure of sea state. A least square method for determining γ from measured data is proposed. In virtue of the method, the values of γ are determined for three sea states from the data measured in the East China Sea. The present PDF is compared with the well known Rayleigh PDF of wave height and it is shown that it much better fits the data than the Rayleigh PDF. It is expected that the present PDF would fit some other wave variables, since its derivation is not restricted only to the wave height.展开更多
Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy patter...Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy pattern-recognition theory. Weight coefficients of each target of ship form scheme are determined by information entropy and individual subjective partiality. This model is used to select the optimal ship form scheme, the example shows that the model is exact and the resuh is credible. It can provide a reference for choosing the optimization scheme of ship form.展开更多
The entropy squeezing properties for a two-level atom interacting with a two-mode field via two differentcompeting transitions are investigated from a quantum information point of view.The influences of the initial st...The entropy squeezing properties for a two-level atom interacting with a two-mode field via two differentcompeting transitions are investigated from a quantum information point of view.The influences of the initial state of thesystem and the relative coupling strength between the atom and the field on the atomic information entropy squeezingare discussed.Our results show that the squeezed direction and the frequency of the information entropy squeezing canbe controlled by choosing the phase of the atom dipole and the relative competing strength of atom-field,respectively.We find that,under the same condition,no atomic variance squeezing is predicted from the HUR while optimal entropysqueezing is obtained from the EUR,so the quantum information entropy is a remarkable precision measure for theatomic squeezing in the considered system.展开更多
This paper shows the Fokker-Planck equation of a dynamical system driven by coloured cross-correlated white noises in the absence and presence of a small external force. Based on the Fokker-Planck equation and the def...This paper shows the Fokker-Planck equation of a dynamical system driven by coloured cross-correlated white noises in the absence and presence of a small external force. Based on the Fokker-Planck equation and the definition of Shannon＇s information entropy, the time dependence of entropy flux and entropy production can be calculated. The present results can be used to explain the extremal behaviour of time dependence of entropy flux and entropy production in view of the dissipative parameter γ of the system, coloured cross-correlation time τ and coloured cross-correlation strength λ.展开更多
Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks.In a previous work [Xu et al. Physica A, 456 294（2016）], we measure the contribution of a path in...Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks.In a previous work [Xu et al. Physica A, 456 294（2016）], we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight,and propose a weighted prediction index based on the contributions of paths, namely weighted path entropy（WPE）, to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three other typical weighted indices.展开更多
It is shown how the cross-correlation time and strength of coloured cross-correlated white noises can set an upper bound for the time derivative of entropy in a nonequilibrium system. The value of upper bound can be c...It is shown how the cross-correlation time and strength of coloured cross-correlated white noises can set an upper bound for the time derivative of entropy in a nonequilibrium system. The value of upper bound can be calculated directly based on the Schwartz inequality principle and the Fokker-Planck equation of the dynamical system driven by coloured cross-correlated white noises. The present calculations can be used to interpret the interplay of the dissipative constant and cross-correlation time and strength of coloured cross-correlated white noises on the upper bound.展开更多
This paper studied on the clustering problem for intrusion detection with the theory of information entropy, it was put forward that the clustering problem for exact intrusion detection based on information entropy is...This paper studied on the clustering problem for intrusion detection with the theory of information entropy, it was put forward that the clustering problem for exact intrusion detection based on information entropy is NP complete, therefore, the heuristic algorithm to solve the clustering problem for intrusion detection was designed, this algorithm has the characteristic of incremental development, it can deal with the database with large connection records from the internet.展开更多
This paper deals with the time evolution of information entropy for a stochastic system with double singularities driven by quasimonochromatic noise. The dimension of the Fokker Planck equation is reduced by the linea...This paper deals with the time evolution of information entropy for a stochastic system with double singularities driven by quasimonochromatic noise. The dimension of the Fokker Planck equation is reduced by the linear transfor- mation. The exact expression of the time dependence of information entropy is obtained based on the definition of Shannon＇s information entropy. The relationships between the properties of dissipative parameters, system singularity strength parameter, quasimonochromatic noise, and their effects on information entropy are discussed.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.6217070290)the Shanghai Science and Technology Project(Grant Nos.21JC1402800 and 20040501500)+2 种基金the Scientific Research Fund of Hunan Provincial Education Department(Grant No.21A0470)the Hunan Provincial Natural Science Foundation of China(Grant No.2020JJ4557)Top-Notch Innovative Talent Program for Postgraduate Students of Shanghai Maritime University(Grant No.2021YBR009)。
文摘We propose a new quantum watermarking scheme based on threshold selection using informational entropy of quantum image.The core idea of this scheme is to embed information into object and background of cover image in different ways.First,a threshold method adopting the quantum informational entropy is employed to determine a threshold value.The threshold value can then be further used for segmenting the cover image to a binary image,which is an authentication key for embedding and extraction information.By a careful analysis of the quantum circuits of the scheme,that is,translating into the basic gate sequences which show the low complexity of the scheme.One of the simulation-based experimental results is entropy difference which measures the similarity of two images by calculating the difference in quantum image informational entropy between watermarked image and cover image.Furthermore,the analyses of peak signal-to-noise ratio,histogram and capacity of the scheme are also provided.
基金Anhui Province Natural Science Research Project of Colleges and Universities(2023AH040321)Excellent Scientific Research and Innovation Team of Anhui Colleges(2022AH010098).
文摘The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.
文摘Assessment of quantity of information that is present in own noises of EE （electronic elements）--informational noise＇s entropy--using spectrum distribution of noises＇ probability of real elements is proposed. It is shown that informational noise＇s entropy as opposed to used differential entropy of continuous signals defines the quantity of qualitative information related to the features of element＇s structure. Proposed quantitative assessment of information can be used for calculation of information contained in the own noises of other technical systems.
基金supported by the National Natural Science Foundation of China under Grant No.U1736216。
文摘Traffic encryption techniques facilitate cyberattackers to hide their presence and activities.Traffic classification is an important method to prevent network threats.However,due to the tremendous traffic volume and limitations of computing,most existing traffic classification techniques are inapplicable to the high-speed network environment.In this paper,we propose a High-speed Encrypted Traffic Classification(HETC)method containing two stages.First,to efficiently detect whether traffic is encrypted,HETC focuses on randomly sampled short flows and extracts aggregation entropies with chi-square test features to measure the different patterns of the byte composition and distribution between encrypted and unencrypted flows.Second,HETC introduces binary features upon the previous features and performs fine-grained traffic classification by combining these payload features with a Random Forest model.The experimental results show that HETC can achieve a 94%F-measure in detecting encrypted flows and a 85%–93%F-measure in classifying fine-grained flows for a 1-KB flow-length dataset,outperforming the state-of-the-art comparison methods.Meanwhile,HETC does not need to wait for the end of the flow and can extract mass computing features.The average time for HETC to process each flow is only 2 or 16 ms,which is lower than the flow duration in most cases,making it a good candidate for high-speed traffic classification.
基金Project(50934006) supported by the National Natural Science Foundation of ChinaProject(2010CB732004) supported by the National Basic Research Program of China+1 种基金Project(2009ssxt230) supported by the Central South University Innovation Fund,ChinaProject(CX2011B119) supported by the Graduated Students’Research and Innovation Fund of Hunan Province,China
文摘Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification （CDI） criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1-$6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.
基金Project(2017YFC0804201)supported by the National Key Research and Development Program of ChinaProject(51574246)supported by the National Natural Science Foundation of China+1 种基金Project(2011QZ01)supported by Fundamental Research Funds for the Central Universities,ChinaProject(C201911362)supported by the National Training Program of Innovation and Entrepreneurship for Undergraduates,China。
文摘Rockburst is a dynamic phenomenon accompanied by acoustic emission(AE)activities.It is difficult to predict rockburst accurately.Based on the fast Fourier transform(FFT)method and the information entropy theory,the evolution model of dominant frequency entropy was established.The AE energy,frequency and stress were synthetically considered to predict rockburst.Under the triaxial and the single-face unloading tests,the relationship between AE energy and the development of internal cracks was analyzed.Using the FFT method,the distribution characteristics of AE dominant frequency values were obtained.Based on the information entropy theory,the dominant frequencies evolved patterns were ascertained.It was observed that the evolution models of the dominant frequency entropy were nearly the same and shared a characteristic“undulation-decrease-rise-sharp decrease”pattern.Results show that AE energy will be released suddenly before rockburst.The density of intermediate frequency increased prior to rockburst.The dominant frequency entropy reached a relative maximum value before rockburst,and then decreased sharply.These features could be used as a precursory information for predicting rockburst.The proposed relative maximum value could be as a key point to predict rockburst.This is a meaningful attempt on predicting rockburst.
基金Project funded by both the Bureau of Science and Information Technology of Guangzhou Municipal Governmentthe Key Laboratory of Offshore Oil Exploration and Development in 2011
文摘The urban ecosystem possesses dissipating structures that can absorb substances and energy from the external environment and export products and wastes to maintain order within the system. Given these circumstances, this paper analyzed the ability of the urban ecosystem in Guangzhou City to sustain development from the perspective of entropy. The research was carried out in three steps. First, an evaluation index system that considers the ability of the urban ecosystem for sustainable development was formed based on the struc- tures and functions of the urban ecosystem and the change in the entropy of the urban so- cioeconomic ecosystem. Second, the sustainable development ability assessment model for the urban ecosystem was built using information entropy. Last, by combining the time series variation of the evaluation indicators with the entropy weights, this paper analyzed the influ- ence of the combined factors on the sustainable development ability of the urban ecosystem in Guangzhou and suggested some measures to promote the sustainable development of the urban ecosystem in Guangzhou. The conclusions of this study can be summarized as follows： （1） The urban ecosystem has developed in an orderly and healthy direction, with effective control over the urban environmental pollution problems in Guangzhou between 2004 and 2010. （2） The sustainable development ability of the urban ecosystem had been on an up- ward trend in Guangzhou during the study period. The ability of the natural urban ecosystem to support the urban socioeconomic ecosystem increased continuously, and the improved ecoenvironment enhanced the harmony and vitality of the urban ecosystem in Guangzhou.
基金Supported by National Natural Science Foundation of China and Civil Aviation Administration of China Joint Funded Project(Grant No.U1733108)Key Project of Tianjin Science and Technology Support Program(Grant No.16YFZCSY00860).
文摘For a single-structure deep learning fault diagnosis model,its disadvantages are an insufficient feature extraction and weak fault classification capability.This paper proposes a multi-scale deep feature fusion intelligent fault diagnosis method based on information entropy.First,a normal autoencoder,denoising autoencoder,sparse autoencoder,and contractive autoencoder are used in parallel to construct a multi-scale deep neural network feature extraction structure.A deep feature fusion strategy based on information entropy is proposed to obtain low-dimensional features and ensure the robustness of the model and the quality of deep features.Finally,the advantage of the deep belief network probability model is used as the fault classifier to identify the faults.The effectiveness of the proposed method was verified by a gearbox test-bed.Experimental results show that,compared with traditional and existing intelligent fault diagnosis methods,the proposed method can obtain representative information and features from the raw data with higher classification accuracy.
基金supported by the National Natural Science Foundation of China (61171194)
文摘This paper presents a method for detecting the small infrared target under complex background. An algorithm, named local mutation weighted information entropy （LMWIE）, is proposed to suppress background. Then, the grey value of targets is enhanced by calculating the local energy. Image segmentation based on the adaptive threshold is used to solve the problems that the grey value of noise is enhanced with the grey value improvement of targets. Experimental results show that compared with the adaptive Butterworth high-pass filter method, the proposed algorithm is more effective and faster for the infrared small target detection.
基金supported by the National Natural Science Foundation of China(Nos.11975091 and U1732135)the Program for Innovative Research Team(in Science and Technology)in University of Henan Province,China(No.21IRTSTHN011)。
文摘Configurational information entropy(CIE)theory was employed to determine the neutron-skin thickness of neutron-rich calcium isotopes.The nuclear density distributions and fragment cross sections in 350 MeV/u ^(40-60)Ca+^(9)Be projectile fragmentation reactions were calculated using a modified statistical abrasion-ablation model.CIE quantities were determined from the nuclear density,isotopic,mass,and charge distributions.The linear correlations between the CIE determined using the isotopic,mass,and charge distributions and the neutron-skin thickness of the projectile nucleus show that CIE provides new methods to extract the neutron-skin thickness of neutron-rich nuclei.
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.
基金the National Natural Science Foundation of China(No.11975091)the Program for Innovative Research Team(in Science and Technology)in the University of Henan Province,China(No.21IRTSTHN011).
文摘Configurational information entropy(CIE)analysis has been shown to be applicable for determining the neutron skin thickness(δnp)of neutron-rich nuclei from fragment production in projectile fragmentation reactions.The BNN+FRACS machine learning model was adopted to predict the fragment mass cross-sections(σ_(A))of the projectile fragmentation reactions induced by calcium isotopes from ^(36)Ca to ^(56)Ca on a ^(9)Be target at 140MeV/u.The fast Fourier transform was adopted to decompose the possible information compositions inσA distributions and determine the quantity of CIE(S_(A)[f]).It was found that the range of fragments significantly influences the quantity of S_(A)[f],which results in different trends of S_(A)[f]~δnp correlation.The linear S_(A)[f]~δnp correlation in a previous study[Nucl.Sci.Tech.33,6(2022)]could be reproduced using fragments with relatively large mass fragments,which verifies that S_(A)[f]determined from fragmentσAis sensitive to the neutron skin thickness of neutron-rich isotopes.
文摘Based on the maximum entropy principle, a probability density function (PDF) is derived for the distribution of wave heights in a random wave field, without any more hypothesis. The present PDF, being a non-Rayleigh form, involves two parameters: the average wave height H— and the state parameter γ. The role of γ in the distribution of wave heights is examined. It is found that γ may be a certain measure of sea state. A least square method for determining γ from measured data is proposed. In virtue of the method, the values of γ are determined for three sea states from the data measured in the East China Sea. The present PDF is compared with the well known Rayleigh PDF of wave height and it is shown that it much better fits the data than the Rayleigh PDF. It is expected that the present PDF would fit some other wave variables, since its derivation is not restricted only to the wave height.
文摘Selecting optimization ship form scheme is an important content in the process of concept design of ship. Multi-objective fuzzy decision-making model for ship form demonstration is set up according to the fuzzy pattern-recognition theory. Weight coefficients of each target of ship form scheme are determined by information entropy and individual subjective partiality. This model is used to select the optimal ship form scheme, the example shows that the model is exact and the resuh is credible. It can provide a reference for choosing the optimization scheme of ship form.
基金National Natural Science Foundation of China under Grant No:10374025the Education Department of Hunan Province of China under Grant No.06A038
文摘The entropy squeezing properties for a two-level atom interacting with a two-mode field via two differentcompeting transitions are investigated from a quantum information point of view.The influences of the initial state of thesystem and the relative coupling strength between the atom and the field on the atomic information entropy squeezingare discussed.Our results show that the squeezed direction and the frequency of the information entropy squeezing canbe controlled by choosing the phase of the atom dipole and the relative competing strength of atom-field,respectively.We find that,under the same condition,no atomic variance squeezing is predicted from the HUR while optimal entropysqueezing is obtained from the EUR,so the quantum information entropy is a remarkable precision measure for theatomic squeezing in the considered system.
基金Project supported by the National Natural Science Foundation of China （Grant No 10472091 and 10332030） and Natural Science Foundation of Shaanxi Province, China （Grant No 2003A03）. The author gratefully acknowledges the support of Youth for NPU Teachers Scientific and Technological Innovation Foundation.
文摘This paper shows the Fokker-Planck equation of a dynamical system driven by coloured cross-correlated white noises in the absence and presence of a small external force. Based on the Fokker-Planck equation and the definition of Shannon＇s information entropy, the time dependence of entropy flux and entropy production can be calculated. The present results can be used to explain the extremal behaviour of time dependence of entropy flux and entropy production in view of the dissipative parameter γ of the system, coloured cross-correlation time τ and coloured cross-correlation strength λ.
基金supported by the National Natural Science Foundation of China(Grant Nos.61201173 and 61304154)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20133219120032)+1 种基金the Postdoctoral Science Foundation of China(Grant No.2013M541673)China Postdoctoral Science Special Foundation(Grant No.2015T80556)
文摘Information entropy has been proved to be an effective tool to quantify the structural importance of complex networks.In a previous work [Xu et al. Physica A, 456 294（2016）], we measure the contribution of a path in link prediction with information entropy. In this paper, we further quantify the contribution of a path with both path entropy and path weight,and propose a weighted prediction index based on the contributions of paths, namely weighted path entropy（WPE）, to improve the prediction accuracy in weighted networks. Empirical experiments on six weighted real-world networks show that WPE achieves higher prediction accuracy than three other typical weighted indices.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 10472091 and 10332030）, the Natural Science Foundation of Shaanxi Province of China （Grant No 2003A03）.
文摘It is shown how the cross-correlation time and strength of coloured cross-correlated white noises can set an upper bound for the time derivative of entropy in a nonequilibrium system. The value of upper bound can be calculated directly based on the Schwartz inequality principle and the Fokker-Planck equation of the dynamical system driven by coloured cross-correlated white noises. The present calculations can be used to interpret the interplay of the dissipative constant and cross-correlation time and strength of coloured cross-correlated white noises on the upper bound.
文摘This paper studied on the clustering problem for intrusion detection with the theory of information entropy, it was put forward that the clustering problem for exact intrusion detection based on information entropy is NP complete, therefore, the heuristic algorithm to solve the clustering problem for intrusion detection was designed, this algorithm has the characteristic of incremental development, it can deal with the database with large connection records from the internet.
基金Project supported by the National Natural Science Foundation of China(Grant No.11102132)
文摘This paper deals with the time evolution of information entropy for a stochastic system with double singularities driven by quasimonochromatic noise. The dimension of the Fokker Planck equation is reduced by the linear transfor- mation. The exact expression of the time dependence of information entropy is obtained based on the definition of Shannon＇s information entropy. The relationships between the properties of dissipative parameters, system singularity strength parameter, quasimonochromatic noise, and their effects on information entropy are discussed.
