As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery...As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.展开更多
Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough corr...Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.展开更多
Joint inversion based on a correlation constraint utilizes a linear correlation function as a structural constraint.The linear correlation function contains a denominator,which may result in a singularity as the objec...Joint inversion based on a correlation constraint utilizes a linear correlation function as a structural constraint.The linear correlation function contains a denominator,which may result in a singularity as the objective function is optimized,leading to an unstable inversion calculation.To improve the robustness of this calculation,this paper proposes a new method in which a sinusoidal correlation function is employed as the structural constraint for joint inversion instead of the conventional linear correlation function.This structural constraint does not contain a denominator,thereby preventing a singularity.Compared with the joint inversion method based on a cross-gradient constraint,the joint inversion method based on a sinusoidal correlation constraint exhibits good performance.An application to actual data demonstrates that this method can process real data.展开更多
Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.Th...Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.展开更多
In standard canonical correlation analysis (CCA), the data from definite datasets are used to estimate their canonical correlation. In real applications, for example in bilingual text retrieval, it may have a great po...In standard canonical correlation analysis (CCA), the data from definite datasets are used to estimate their canonical correlation. In real applications, for example in bilingual text retrieval, it may have a great portion of data that we do not know which set it belongs to. This part of data is called unlabeled data, while the rest from definite datasets is called labeled data. We propose a novel method called regularized canonical correlation analysis (RCCA), which makes use of both labeled and unlabeled samples. Specifically, we learn to approximate canonical correlation as if all data were labeled. Then, we describe a generalization of RCCA for the multi-set situation. Experiments on four real world datasets, Yeast, Cloud, Iris, and Haberman, demonstrate that, by incorporating the unlabeled data points, the accuracy of correlation coefficients can be improved by over 30%.展开更多
Abstract: It has been inferred and proved by the remote sensing equations under rational hypotheses in atmospheric physics that there is a linear correlation between the ground reflective brightness Wij and the total ...Abstract: It has been inferred and proved by the remote sensing equations under rational hypotheses in atmospheric physics that there is a linear correlation between the ground reflective brightness Wij and the total reflective brightness Rij received in different bands with a remote sensor. Nine models delineating the ground-space correlation between the ground spectra and the optimal bands of images of the typical gold deposits have been established based on the ground-space correlativity and field measurements of the ground spectra of the typical gold deposits in the Ailaoshan area. According to the 9 correlation models, TM images were inverted into ground-space correlation images that are related to the typical gold deposits within the area and then recognized by a computer. Research on the ground spectra and TM data in the Ailaoshan area shows that the correlation analysis of the ground spectra and TM data of gold deposits can be effectively applied to the prediction of gold deposits, location of prospecting targets, and extraction of imagery information of gold mineralization.展开更多
Privacy protection for big data linking is discussed here in relation to the Central Statistics Office （CSO）, Ireland＇s, big data linking project titled the ＇Structure of Earnings Survey - Administrative Data Proj...Privacy protection for big data linking is discussed here in relation to the Central Statistics Office （CSO）, Ireland＇s, big data linking project titled the ＇Structure of Earnings Survey - Administrative Data Project＇ （SESADP）. The result of the project was the creation of datasets and statistical outputs for the years 2011 to 2014 to meet Eurostat＇s annual earnings statistics requirements and the Structure of Earnings Survey （SES） Regulation. Record linking across the Census and various public sector datasets enabled the necessary information to be acquired to meet the Eurostat earnings requirements. However, the risk of statistical disclosure （i.e. identifying an individual on the dataset） is high unless privacy and confidentiality safe-guards are built into the data matching process. This paper looks at the three methods of linking records on big datasets employed on the SESADP, and how to anonymise the data to protect the identity of the individuals, where potentially disclosive variables exist.展开更多
Objective: To measure the hospital operation efficiency, study the correlation between average length of stay and hospital operation efficiency, analyze the importance of shortening average length of stay to the impro...Objective: To measure the hospital operation efficiency, study the correlation between average length of stay and hospital operation efficiency, analyze the importance of shortening average length of stay to the improvement of the hospital operation efficiency and put forward relevant policy suggestion. Methods: Based on China provincial panel data from 2003 to 2012, the hospital operation efficiencies are calculated using Super Efficiency Data Envelopment Analysis model, and the correlation between average length of stay and hospital operation efficiency is tested using Spearman rank correlation coefficient test. Results: From 2003 to 2012, the average of national hospital operation efficiency was increasing slowly and the hospital operations were inefficient in most of the areas. The national hospital operation efficiency is negatively correlated to the average length of stay. Conclusion: Measures should be taken to set average length of stay in a scientific and reasonable way, improve social and economic benefits based on the improvement of efficiency.展开更多
In the context of urbanization,air pollution has emerged as a significant environmental challenge.A thorough understanding of their transport pathways,especially at a national scale,is essential for environmental prot...In the context of urbanization,air pollution has emerged as a significant environmental challenge.A thorough understanding of their transport pathways,especially at a national scale,is essential for environmental protection and policy-making.However,it remains partially elusive due to the constraints of available data and analytical methods.This study proposed a data-driven spatiotemporal correlation analysis method employing the Dynamic Time Warping(DTW).We represented the first comprehensive attempt to chart the long-term and nationwide transport pathways of PM_(2.5) utilizing an extensive dataset spanning from 2000 to 2021 across China,which is crucial for understanding long-term air pollution trends.Compared with traditional chemical transport models(CTMs),this data-driven method can generate transport pathways of PM_(2.5) without requiring extensive meteorological or emission data,and suggesting fundamentally consistent spatial distribution and trends.Our analysis reveals that China’s transport pathways are notably pronounced in the Northwest(34%of the total pathways in China),Southwest(22%),and North(21%)regions,with less significant pathways in the Northeast(10%)region and isolated occurrences elsewhere.Additionally,a notable decrease in the number of China’s PM_(2.5) transport pathways,similar to annual average concentrations,was observed after 2013,aligning with stricter environmental regulations.Furthermore,we have demonstrated the feasibility of applying our method to the transport pathways of other gaseous pollutants.The approach is effective in detecting and quantifying air pollutants’transport pathways,even in regions like the Northwest with limited monitoring infrastructure,which may aid in environmental decision-making.The study will notably improve the current understanding of air pollutants’transport process,providing a new perspective for studying the large-scale spatiotemporal correlations.展开更多
This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the...This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discuss the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions （vehicles with special numbered plates only run in a special workday） enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation.展开更多
The fluorescence emission wavelength [lambda(max(em))] values of three types of benzaldehyde derivatives, namely, ethylene acetals (1-Ys), 4-nitrophenylhydrazones (2-Ys) and phenylhydrazones (3-Ys), have been measured...The fluorescence emission wavelength [lambda(max(em))] values of three types of benzaldehyde derivatives, namely, ethylene acetals (1-Ys), 4-nitrophenylhydrazones (2-Ys) and phenylhydrazones (3-Ys), have been measured. Correlation analyses by the dual-parameter equation show that the lambda(max(em)) values of 1-Ys are mainly affected by the spin-delocalization effects of the substituents, while those of 2-Ys are mainly affected by the polar effects. However, those of 3-Ys are independent of the substituents.展开更多
Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tac...Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tackles two pivotal challenges in the realm of quantum computing:firstly,the development of an effective encoding protocol for translating classical data into quantum states,a critical step for any quantum computation.Different encoding strategies can significantly influence quantum computer performance.Secondly,we address the need to counteract the inevitable noise that can hinder quantum acceleration.Our primary contribution is the introduction of a novel variational data encoding method,grounded in quantum regression algorithm models.By adapting the learning concept from machine learning,we render data encoding a learnable process.This allowed us to study the role of quantum correlation in data encoding.Through numerical simulations of various regression tasks,we demonstrate the efficacy of our variational data encoding,particularly post-learning from instructional data.Moreover,we delve into the role of quantum correlation in enhancing task performance,especially in noisy environments.Our findings underscore the critical role of quantum correlation in not only bolstering performance but also in mitigating noise interference,thus advancing the frontier of quantum computing.展开更多
The correlation between the longitudinal crack occurrence and integrated heat transfer of the mold with data mining methods was investigated.Firstly,three kinds of support vector machine models based on principal comp...The correlation between the longitudinal crack occurrence and integrated heat transfer of the mold with data mining methods was investigated.Firstly,three kinds of support vector machine models based on principal component analysis with different input features were established to explore the effect of integrated heat transfer on the accuracy of the prediction model for the longitudinal crack.The results show that the accuracy was improved while features including mean and standard deviation of integrated heat transfer were added.Then,the difference in integrated heat transfer between defect and normal samples under the same process parameters was quantitatively compared.Compared with normal samples,the temperature difference of cooling water for defect samples decreased by 0.65%,and the temperature difference fluctuation increased by 31.1%.Finally,the literature data were used to provide support for the quantitative correlation according to defect formation mechanism.A new criterion for the prediction of longitudinal crack and a discovering method for correlation between product quality and process parameters in the manufacturing industry have been provided.展开更多
With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The networ...With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.展开更多
Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin(Western Desert,Egypt)necessitate a thorough oil-source ...Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin(Western Desert,Egypt)necessitate a thorough oil-source correlation investigation.This objective is achieved through a meticulous analysis of well-log responses,Rock-Eval pyrolysis,and biomarker data.The analysis of Total Organic Carbon across 31 samples representing Paleozoic formations in the Siwa A-1X well reveals a spectrum of organic richness ranging from 0.17 wt%to 2.04 wt%,thereby highlighting diverse levels of organic content and the presence of both Type II and Type III kerogen.Examination of the fingerprint characteristics of eight samples from the well suggests that the Dhiffah Formation comprises a blend of terrestrial and marine organic matter.Notably,a significant contribution from more oxidized residual organic matter and gas-prone Type III kerogen is observed.Contrarily,the Desouky and Zeitoun formations exhibit mixed organic matter indicative of a transitional environment,and thus featuring a pronounced marine influence within a more reducing setting,which is associated with Type II kerogen.Through analysis of five oil samples from different wells—SIWA L-1X,SIWA R-3X,SIWA D-1X,PTAH 5X,and PTAH 6X,it is evident that terrestrial organic matter,augmented by considerable marine input,was deposited in an oxidizing environment,and contains Type III kerogen.Geochemical scrutiny confirms the coexistence of mixed terrestrial organic matter within varying redox environments.Noteworthy is the uniformity of identified kerogen Types II and III across all samples,known to have potential for hydrocarbon generation.The discovery presented in this paper unveils captivating prospects concerning the genesis of oil in the Jurassic Safa reservoir,suggesting potential links to Paleozoic sources or even originating from the Safa Member itself.These revelations mark a substantial advancement in understanding source rock dynamics and their intricate relationship with reservoir oils within the Siwa Basin.By illuminating the processes of hydrocarbon genesis in the region,this study significantly enriches our knowledge base.展开更多
As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardne...As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.展开更多
At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the p...At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.展开更多
The Chinese Aeronautical Establishment（CAE） Aerodynamic Validation Model（AVM）is a dual-purpose test geometry dedicated to verify the aerodynamic performance of a conceptual intercontinental jet aircraft and to pro...The Chinese Aeronautical Establishment（CAE） Aerodynamic Validation Model（AVM）is a dual-purpose test geometry dedicated to verify the aerodynamic performance of a conceptual intercontinental jet aircraft and to provide a dataset for CFD software validation. To this end, a scaled model of the AVM was tested in the High-Speed Tunnel（HST） of the German-Dutch Wind-tunnels（DNW） with special test consideration and instrumentation. For complementary analysis of experimental results, specific CAE-AVM geometries are analyzed using a CAE inhouse CFD code. The specific geometries consist of a baseline aircraft, an aircraft with a deformed wing shape, and an aircraft with both a deformed wing shape and a representation of the model support system used in the wind tunnel. Detailed analysis of numerical and experimental results is presented; both the combined and individual attributions of wing deformation and support system interference on wing pressure distributions and longitudinal aerodynamic characteristics are summarized.展开更多
The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain facto...The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model, and then, inte- grating correlation analysis, a new way of figuring out the weight of land evaluation factors is proposed. It may solve the limitations of the conventional ways.展开更多
OBJECTIVE:To explore the correlation between diagnostic information of tongue and gastroscopy results of patients with chronic gastritis.METHODS:Frequent pattern growth(FP-Growth),SPSS Modeler was used to analyze the ...OBJECTIVE:To explore the correlation between diagnostic information of tongue and gastroscopy results of patients with chronic gastritis.METHODS:Frequent pattern growth(FP-Growth),SPSS Modeler was used to analyze the correlation rules between the image information of tongue parameters and the characteristics of the stomach and duodenum seen under gastroscopy.RESULTS:Ranking in order of confidence:cyanotic tongue,slippery fur,yellow fur and spotted tongue were sequently associated with both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.L,one value of tongue coating color,which counted among(30,60),tooth-marked tongue and b,one value of tongue coating color,which counted in the range of(5,20)were sequently associated with gastric antrum mucosal erythema/macula.A,one value of tongue body color,which counted in the range of(0,20),was related to both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.a,one value of tongue coating color,which counted in the range of(15,35),was associated with gastric antrum mucosal erythema/macula.There are a total of 9 strong correlation rules.CONCLUSIONS:Cyanotic tongue,slippery fur,yellow fur,the CIE Lab value of tongue coating,a,the value of tongue body color,spotted tongue,and tooth-marked tongue are all related to the gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.The conditions of gastric mucosa could be predicted by the examination of the above related image information of tongue.展开更多
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z433)Hunan Provincial Natural Science Foundation of China (Grant No. 09JJ8005)Scientific Research Foundation of Graduate School of Beijing University of Chemical and Technology,China (Grant No. 10Me002)
文摘As the differences of sensor＇s precision and some random factors are difficult to control,the actual measurement signals are far from the target signals that affect the reliability and precision of rotating machinery fault diagnosis.The traditional signal processing methods,such as classical inference and weighted averaging algorithm usually lack dynamic adaptability that is easy for trends to cause the faults to be misjudged or left out.To enhance the measuring veracity and precision of vibration signal in rotary machine multi-sensor vibration signal fault diagnosis,a novel data level fusion approach is presented on the basis of correlation function analysis to fast determine the weighted value of multi-sensor vibration signals.The approach doesn＇t require knowing the prior information about sensors,and the weighted value of sensors can be confirmed depending on the correlation measure of real-time data tested in the data level fusion process.It gives greater weighted value to the greater correlation measure of sensor signals,and vice versa.The approach can effectively suppress large errors and even can still fuse data in the case of sensor failures because it takes full advantage of sensor＇s own-information to determine the weighted value.Moreover,it has good performance of anti-jamming due to the correlation measures between noise and effective signals are usually small.Through the simulation of typical signal collected from multi-sensors,the comparative analysis of dynamic adaptability and fault tolerance between the proposed approach and traditional weighted averaging approach is taken.Finally,the rotor dynamics and integrated fault simulator is taken as an example to verify the feasibility and advantages of the proposed approach,it is shown that the multi-sensor data level fusion based on correlation function weighted approach is better than the traditional weighted average approach with respect to fusion precision and dynamic adaptability.Meantime,the approach is adaptable and easy to use,can be applied to other areas of vibration measurement.
基金This project was supported by the National Natural Science Foundation of China (60672139, 60672140)the Excellent Ph.D. Paper Author Foundation of China (200237)the Natural Science Foundation of Shandong (2005ZX01).
文摘Under the scenario of dense targets in clutter, a multi-layer optimal data correlation algorithm is proposed. This algorithm eliminates a large number of false location points from the assignment process by rough correlations before we calculate the correlation cost, so it avoids the operations for the target state estimate and the calculation of the correlation cost for the false correlation sets. In the meantime, with the elimination of these points in the rough correlation, the disturbance from the false correlations in the assignment process is decreased, so the data correlation accuracy is improved correspondingly. Complexity analyses of the new multi-layer optimal algorithm and the traditional optimal assignment algorithm are given. Simulation results show that the new algorithm is feasible and effective.
基金supported by the National Key Research and Development Project of China(No:2017YFC0602201)
文摘Joint inversion based on a correlation constraint utilizes a linear correlation function as a structural constraint.The linear correlation function contains a denominator,which may result in a singularity as the objective function is optimized,leading to an unstable inversion calculation.To improve the robustness of this calculation,this paper proposes a new method in which a sinusoidal correlation function is employed as the structural constraint for joint inversion instead of the conventional linear correlation function.This structural constraint does not contain a denominator,thereby preventing a singularity.Compared with the joint inversion method based on a cross-gradient constraint,the joint inversion method based on a sinusoidal correlation constraint exhibits good performance.An application to actual data demonstrates that this method can process real data.
基金supported by the Science and Technology Project of China Southern Power Grid(GZHKJXM20210043-080041KK52210002).
文摘Traditional distribution network planning relies on the professional knowledge of planners,especially when analyzing the correlations between the problems existing in the network and the crucial influencing factors.The inherent laws reflected by the historical data of the distribution network are ignored,which affects the objectivity of the planning scheme.In this study,to improve the efficiency and accuracy of distribution network planning,the characteristics of distribution network data were extracted using a data-mining technique,and correlation knowledge of existing problems in the network was obtained.A data-mining model based on correlation rules was established.The inputs of the model were the electrical characteristic indices screened using the gray correlation method.The Apriori algorithm was used to extract correlation knowledge from the operational data of the distribution network and obtain strong correlation rules.Degree of promotion and chi-square tests were used to verify the rationality of the strong correlation rules of the model output.In this study,the correlation relationship between heavy load or overload problems of distribution network feeders in different regions and related characteristic indices was determined,and the confidence of the correlation rules was obtained.These results can provide an effective basis for the formulation of a distribution network planning scheme.
基金Project (No. 5959438) supported by Microsoft (China) Co., Ltd
文摘In standard canonical correlation analysis (CCA), the data from definite datasets are used to estimate their canonical correlation. In real applications, for example in bilingual text retrieval, it may have a great portion of data that we do not know which set it belongs to. This part of data is called unlabeled data, while the rest from definite datasets is called labeled data. We propose a novel method called regularized canonical correlation analysis (RCCA), which makes use of both labeled and unlabeled samples. Specifically, we learn to approximate canonical correlation as if all data were labeled. Then, we describe a generalization of RCCA for the multi-set situation. Experiments on four real world datasets, Yeast, Cloud, Iris, and Haberman, demonstrate that, by incorporating the unlabeled data points, the accuracy of correlation coefficients can be improved by over 30%.
文摘Abstract: It has been inferred and proved by the remote sensing equations under rational hypotheses in atmospheric physics that there is a linear correlation between the ground reflective brightness Wij and the total reflective brightness Rij received in different bands with a remote sensor. Nine models delineating the ground-space correlation between the ground spectra and the optimal bands of images of the typical gold deposits have been established based on the ground-space correlativity and field measurements of the ground spectra of the typical gold deposits in the Ailaoshan area. According to the 9 correlation models, TM images were inverted into ground-space correlation images that are related to the typical gold deposits within the area and then recognized by a computer. Research on the ground spectra and TM data in the Ailaoshan area shows that the correlation analysis of the ground spectra and TM data of gold deposits can be effectively applied to the prediction of gold deposits, location of prospecting targets, and extraction of imagery information of gold mineralization.
文摘Privacy protection for big data linking is discussed here in relation to the Central Statistics Office （CSO）, Ireland＇s, big data linking project titled the ＇Structure of Earnings Survey - Administrative Data Project＇ （SESADP）. The result of the project was the creation of datasets and statistical outputs for the years 2011 to 2014 to meet Eurostat＇s annual earnings statistics requirements and the Structure of Earnings Survey （SES） Regulation. Record linking across the Census and various public sector datasets enabled the necessary information to be acquired to meet the Eurostat earnings requirements. However, the risk of statistical disclosure （i.e. identifying an individual on the dataset） is high unless privacy and confidentiality safe-guards are built into the data matching process. This paper looks at the three methods of linking records on big datasets employed on the SESADP, and how to anonymise the data to protect the identity of the individuals, where potentially disclosive variables exist.
文摘Objective: To measure the hospital operation efficiency, study the correlation between average length of stay and hospital operation efficiency, analyze the importance of shortening average length of stay to the improvement of the hospital operation efficiency and put forward relevant policy suggestion. Methods: Based on China provincial panel data from 2003 to 2012, the hospital operation efficiencies are calculated using Super Efficiency Data Envelopment Analysis model, and the correlation between average length of stay and hospital operation efficiency is tested using Spearman rank correlation coefficient test. Results: From 2003 to 2012, the average of national hospital operation efficiency was increasing slowly and the hospital operations were inefficient in most of the areas. The national hospital operation efficiency is negatively correlated to the average length of stay. Conclusion: Measures should be taken to set average length of stay in a scientific and reasonable way, improve social and economic benefits based on the improvement of efficiency.
基金funded by the National Natural Science Foundation of China(grant No.42376246)the Key Research and Development Project of Guangxi(grant No.GuikeAB24010046)the Joint Funds of the National Natural Science Foundation of China(grant No.U2268217).
文摘In the context of urbanization,air pollution has emerged as a significant environmental challenge.A thorough understanding of their transport pathways,especially at a national scale,is essential for environmental protection and policy-making.However,it remains partially elusive due to the constraints of available data and analytical methods.This study proposed a data-driven spatiotemporal correlation analysis method employing the Dynamic Time Warping(DTW).We represented the first comprehensive attempt to chart the long-term and nationwide transport pathways of PM_(2.5) utilizing an extensive dataset spanning from 2000 to 2021 across China,which is crucial for understanding long-term air pollution trends.Compared with traditional chemical transport models(CTMs),this data-driven method can generate transport pathways of PM_(2.5) without requiring extensive meteorological or emission data,and suggesting fundamentally consistent spatial distribution and trends.Our analysis reveals that China’s transport pathways are notably pronounced in the Northwest(34%of the total pathways in China),Southwest(22%),and North(21%)regions,with less significant pathways in the Northeast(10%)region and isolated occurrences elsewhere.Additionally,a notable decrease in the number of China’s PM_(2.5) transport pathways,similar to annual average concentrations,was observed after 2013,aligning with stricter environmental regulations.Furthermore,we have demonstrated the feasibility of applying our method to the transport pathways of other gaseous pollutants.The approach is effective in detecting and quantifying air pollutants’transport pathways,even in regions like the Northwest with limited monitoring infrastructure,which may aid in environmental decision-making.The study will notably improve the current understanding of air pollutants’transport process,providing a new perspective for studying the large-scale spatiotemporal correlations.
基金Project supported by the National High Technology Research and Development Program of China(Grant Nos.2008AA01Z208 and 2009AA01Z405)the Applied Basic Research Program of Sichuan Province of China(Grant No.2010JY0013)the Youth Foundation of Sichuan Province of China(Grant No.2009-28-419)
文摘This paper investigates urban traffic data by analysing the long-range correlation with detrended fluctuation analysis. Through a large number of real data collected by the travel time detection system in Beijing, the variation of flow in different time periods and intersections is studied. According to the long-range correlation in different time scales, it mainly discuss the effect of intersection location in road net, people activity customs and special traffic controls on urban traffic flow. As demonstrated by obtained results, the urban traffic flow represents three-phase characters similar to highway traffic. Moreover, compared by the two groups of data obtained before and after the special traffic restrictions （vehicles with special numbered plates only run in a special workday） enforcement, it indicates that the rules not only reduce the flow but also avoid irregular fluctuation.
文摘The fluorescence emission wavelength [lambda(max(em))] values of three types of benzaldehyde derivatives, namely, ethylene acetals (1-Ys), 4-nitrophenylhydrazones (2-Ys) and phenylhydrazones (3-Ys), have been measured. Correlation analyses by the dual-parameter equation show that the lambda(max(em)) values of 1-Ys are mainly affected by the spin-delocalization effects of the substituents, while those of 2-Ys are mainly affected by the polar effects. However, those of 3-Ys are independent of the substituents.
基金the National Natural Science Foun-dation of China(Grant Nos.12105090 and 12175057).
文摘Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tackles two pivotal challenges in the realm of quantum computing:firstly,the development of an effective encoding protocol for translating classical data into quantum states,a critical step for any quantum computation.Different encoding strategies can significantly influence quantum computer performance.Secondly,we address the need to counteract the inevitable noise that can hinder quantum acceleration.Our primary contribution is the introduction of a novel variational data encoding method,grounded in quantum regression algorithm models.By adapting the learning concept from machine learning,we render data encoding a learnable process.This allowed us to study the role of quantum correlation in data encoding.Through numerical simulations of various regression tasks,we demonstrate the efficacy of our variational data encoding,particularly post-learning from instructional data.Moreover,we delve into the role of quantum correlation in enhancing task performance,especially in noisy environments.Our findings underscore the critical role of quantum correlation in not only bolstering performance but also in mitigating noise interference,thus advancing the frontier of quantum computing.
基金the support from National Natural Science Foundation of China(52274318).
文摘The correlation between the longitudinal crack occurrence and integrated heat transfer of the mold with data mining methods was investigated.Firstly,three kinds of support vector machine models based on principal component analysis with different input features were established to explore the effect of integrated heat transfer on the accuracy of the prediction model for the longitudinal crack.The results show that the accuracy was improved while features including mean and standard deviation of integrated heat transfer were added.Then,the difference in integrated heat transfer between defect and normal samples under the same process parameters was quantitatively compared.Compared with normal samples,the temperature difference of cooling water for defect samples decreased by 0.65%,and the temperature difference fluctuation increased by 31.1%.Finally,the literature data were used to provide support for the quantitative correlation according to defect formation mechanism.A new criterion for the prediction of longitudinal crack and a discovering method for correlation between product quality and process parameters in the manufacturing industry have been provided.
基金This work was supported by the National Natural Science Foundation of China(U2133208,U20A20161).
文摘With the popularization of the Internet and the development of technology,cyber threats are increasing day by day.Threats such as malware,hacking,and data breaches have had a serious impact on cybersecurity.The network security environment in the era of big data presents the characteristics of large amounts of data,high diversity,and high real-time requirements.Traditional security defense methods and tools have been unable to cope with the complex and changing network security threats.This paper proposes a machine-learning security defense algorithm based on metadata association features.Emphasize control over unauthorized users through privacy,integrity,and availability.The user model is established and the mapping between the user model and the metadata of the data source is generated.By analyzing the user model and its corresponding mapping relationship,the query of the user model can be decomposed into the query of various heterogeneous data sources,and the integration of heterogeneous data sources based on the metadata association characteristics can be realized.Define and classify customer information,automatically identify and perceive sensitive data,build a behavior audit and analysis platform,analyze user behavior trajectories,and complete the construction of a machine learning customer information security defense system.The experimental results show that when the data volume is 5×103 bit,the data storage integrity of the proposed method is 92%.The data accuracy is 98%,and the success rate of data intrusion is only 2.6%.It can be concluded that the data storage method in this paper is safe,the data accuracy is always at a high level,and the data disaster recovery performance is good.This method can effectively resist data intrusion and has high air traffic control security.It can not only detect all viruses in user data storage,but also realize integrated virus processing,and further optimize the security defense effect of user big data.
基金the research project is funded by Abdullah Alrushaid Chair for Earth Science Remote Sensing Research at King Saud University,Riyadh,Saudi Arabia.。
文摘Understanding the origins of potential source rocks and unraveling the intricate connections between reservoir oils and their source formations in the Siwa Basin(Western Desert,Egypt)necessitate a thorough oil-source correlation investigation.This objective is achieved through a meticulous analysis of well-log responses,Rock-Eval pyrolysis,and biomarker data.The analysis of Total Organic Carbon across 31 samples representing Paleozoic formations in the Siwa A-1X well reveals a spectrum of organic richness ranging from 0.17 wt%to 2.04 wt%,thereby highlighting diverse levels of organic content and the presence of both Type II and Type III kerogen.Examination of the fingerprint characteristics of eight samples from the well suggests that the Dhiffah Formation comprises a blend of terrestrial and marine organic matter.Notably,a significant contribution from more oxidized residual organic matter and gas-prone Type III kerogen is observed.Contrarily,the Desouky and Zeitoun formations exhibit mixed organic matter indicative of a transitional environment,and thus featuring a pronounced marine influence within a more reducing setting,which is associated with Type II kerogen.Through analysis of five oil samples from different wells—SIWA L-1X,SIWA R-3X,SIWA D-1X,PTAH 5X,and PTAH 6X,it is evident that terrestrial organic matter,augmented by considerable marine input,was deposited in an oxidizing environment,and contains Type III kerogen.Geochemical scrutiny confirms the coexistence of mixed terrestrial organic matter within varying redox environments.Noteworthy is the uniformity of identified kerogen Types II and III across all samples,known to have potential for hydrocarbon generation.The discovery presented in this paper unveils captivating prospects concerning the genesis of oil in the Jurassic Safa reservoir,suggesting potential links to Paleozoic sources or even originating from the Safa Member itself.These revelations mark a substantial advancement in understanding source rock dynamics and their intricate relationship with reservoir oils within the Siwa Basin.By illuminating the processes of hydrocarbon genesis in the region,this study significantly enriches our knowledge base.
基金supported by the National Natural Science Foundation of China(61472443)the Basic Research Priorities Program of Shaanxi Province Natural Science Foundation of China(2013JQ8042)
文摘As an important application research topic of the intelligent aviation multi-station, collaborative detecting must overcome the problem of scouting measurement with status of 'fragmentation', and the NP-hardness problem of matching association between target and measurement in the process of scouting to data-link, which has complicated technical architecture of network construction. In this paper, taking advantage of cooperation mechanism on signal level in the aviation multi-station sympathetic network, a method of obtaining target time difference of arrival (TDOA) measurement using multi-station collaborative detecting based on time-frequency association is proposed. The method can not only achieve matching between target and its measurement, but also obtain TDOA measurement by further evolutionary transaction through refreshing sequential pulse time of arrival (TOA) measurement matrix for matching and correlating. Simulation results show that the accuracy of TDOA measurement has significant superiority over TOA, and detection probability of false TDOA measurement introduced by noise and fake measurement can be reduced effectively.
基金the National Natural Science Foundation of China(No.51775185)Natural Science Foundation of Hunan Province(No.2022JJ90013)+1 种基金Intelligent Environmental Monitoring Technology Hunan Provincial Joint Training Base for Graduate Students in the Integration of Industry and Education,and Hunan Normal University University-Industry Cooperation.the 2011 Collaborative Innovation Center for Development and Utilization of Finance and Economics Big Data Property,Universities of Hunan Province,Open Project,Grant Number 20181901CRP04.
文摘At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.
文摘The Chinese Aeronautical Establishment（CAE） Aerodynamic Validation Model（AVM）is a dual-purpose test geometry dedicated to verify the aerodynamic performance of a conceptual intercontinental jet aircraft and to provide a dataset for CFD software validation. To this end, a scaled model of the AVM was tested in the High-Speed Tunnel（HST） of the German-Dutch Wind-tunnels（DNW） with special test consideration and instrumentation. For complementary analysis of experimental results, specific CAE-AVM geometries are analyzed using a CAE inhouse CFD code. The specific geometries consist of a baseline aircraft, an aircraft with a deformed wing shape, and an aircraft with both a deformed wing shape and a representation of the model support system used in the wind tunnel. Detailed analysis of numerical and experimental results is presented; both the combined and individual attributions of wing deformation and support system interference on wing pressure distributions and longitudinal aerodynamic characteristics are summarized.
文摘The veracity of land evaluation is tightly related to the reasonable weights of land evaluation fac- tors. By mapping qualitative linguistic words into a fine-changeable cloud drops and translating the uncertain factor conditions into quantitative values with the uncertain illation based on cloud model, and then, inte- grating correlation analysis, a new way of figuring out the weight of land evaluation factors is proposed. It may solve the limitations of the conventional ways.
基金Key Special Project of the National Key Research and Development Program of Ministry of Science and Technology(No.2017YFB1002300):Topic One:Multimodal Heterogeneous Efficient Acquisition of Traditional Chinese Medicine Big Data and Resource Library Construction(No.2017YFB1002301)and Topic Three:Multi-Scale Cognition Methods and Treatment Analysis Model of Traditional Chinese Medicine Based on Deep Learning(No.2017YFB1002303)from Big Data-Driven Traditional Chinese Medicine Intelligent Auxiliary Diagnostic Service SystemGraduation Design of“Cultivation Program”for Cross-cultivation of High-level Talents in Beijing Colleges and Universities in 2010(Scientific Research):the Research on the Clinical Diagnosis and Prediction System of Gastric Precancerous Lesions Based on Artificial Intelligence+2 种基金National Natural Science Foundation of China(No.30701071)the Sixth Batch of Academic Experience Inheritance of Traditional Chinese Medicine Experts(2017)“3+3”Project of Beijing Traditional Chinese Medicine Inheritance(No.2012-SZ-C-41)。
文摘OBJECTIVE:To explore the correlation between diagnostic information of tongue and gastroscopy results of patients with chronic gastritis.METHODS:Frequent pattern growth(FP-Growth),SPSS Modeler was used to analyze the correlation rules between the image information of tongue parameters and the characteristics of the stomach and duodenum seen under gastroscopy.RESULTS:Ranking in order of confidence:cyanotic tongue,slippery fur,yellow fur and spotted tongue were sequently associated with both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.L,one value of tongue coating color,which counted among(30,60),tooth-marked tongue and b,one value of tongue coating color,which counted in the range of(5,20)were sequently associated with gastric antrum mucosal erythema/macula.A,one value of tongue body color,which counted in the range of(0,20),was related to both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.a,one value of tongue coating color,which counted in the range of(15,35),was associated with gastric antrum mucosal erythema/macula.There are a total of 9 strong correlation rules.CONCLUSIONS:Cyanotic tongue,slippery fur,yellow fur,the CIE Lab value of tongue coating,a,the value of tongue body color,spotted tongue,and tooth-marked tongue are all related to the gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.The conditions of gastric mucosa could be predicted by the examination of the above related image information of tongue.
