The comprehension of sediment grain size parameters and the corresponding sedimentary environment holds paramount importance in elucidating the engineering geological attributes of the subaqueous seabed.This study del...The comprehension of sediment grain size parameters and the corresponding sedimentary environment holds paramount importance in elucidating the engineering geological attributes of the subaqueous seabed.This study delineated the sedimentary environment zoning in the northern sea area of Qingdao through cluster analysis of grain size parameters derived from 123 surface sediment samples.The study analyzed the correlation between sediment geotechnical indices and grain size parameters across diverse sedimentary environments.A correlation equation was established for samples exhibiting a strong correlation.The study found four distinct sedimentary environments in the study area:coastal,transitional,shallow sea,and residual.Within the same sedimentary environment,the average grain size and sorting coefficient exhibit significant correlations with geotechnical indices such as water content,density,shear strength,plastic limit,liquid limit,and plastic index.However,notable disparities in the correlation between grain size parameters and geotechnical indices emerge across different sedimentary environments.展开更多
The growing correlation length prior to the moderate-great earthquakes occurred in Gansu Province and its nearby area since 1986 has been studied using the method of single-link cluster analysis (SLC). According to di...The growing correlation length prior to the moderate-great earthquakes occurred in Gansu Province and its nearby area since 1986 has been studied using the method of single-link cluster analysis (SLC). According to different conditions in the source area, the circular spatial window centered in the epicenter and the parallelgrammic spatial window along the fault belt have been selected. The results show that the phenomena of growing correlation length have been observed before the earthquakes studied in the paper.展开更多
To extract more in-depth information of acoustic emission(AE)signal-cloud in rock failure under triaxial compression,the spatial correlation of scattering AE events in a granite sample is effectively described by the ...To extract more in-depth information of acoustic emission(AE)signal-cloud in rock failure under triaxial compression,the spatial correlation of scattering AE events in a granite sample is effectively described by the cube-cluster model.First,the complete connection of the fracture network is regarded as a critical state.Then,according to the Hoshen-Kopelman(HK)algorithm,the real-time estimation of fracture con-nection is effectively made and a dichotomy between cube size and pore fraction is suggested to solve such a challenge of the one-to-one match between complete connection and cluster size.After,the 3D cube clusters are decomposed into orthogonal layer clusters,which are then transformed into the ellip-soid models.Correspondingly,the anisotropy evolution of fracture network could be visualized by three orthogonal ellipsoids and quantitatively described by aspect ratio.Besides,the other three quantities of centroid axis length,porosity,and fracture angle are analyzed to evaluate the evolution of cube cluster.The result shows the sample dilatancy is strongly correlated to four quantities of aspect ratio,centroid axis length,and porosity as well as fracture angle.Besides,the cube cluster model shows a potential pos-sibility to predict the evolution of fracture angle.So,the cube cluster model provides an in-depth view of spatial correlation to describe the AE signal-cloud.展开更多
Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the ...Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.展开更多
[ Objective] The research aimed to study assessment index system of the rainstorm disaster in Fujian Province based on spectral cluste- ring model with grey correlation analysis. [Method] According to meteorological d...[ Objective] The research aimed to study assessment index system of the rainstorm disaster in Fujian Province based on spectral cluste- ring model with grey correlation analysis. [Method] According to meteorological disaster yearbook in Fujian Province, by comprehensively consider- ing disaster-inducing factor, disaster-inducing environment, disaster-sustaining body and regional disaster-prevention level, evaluation index system of the regional rainstorm disaster in Fujian was established. By spectral clustering model based on grey correlation analysis, dsk zoning of the rain- storm disaster was conducted in each area of Fujian. Finally, effect and application of the clustering model were analyzed by case research. [ Re- sult] In order to dig immanent connection among regional characteristics and improve disaster-preventing linkage performance of the evaluation unit, a spectral clustering model based on grey correlation analysis was used to conduct risk zoning of the rainstorm disaster in Fujian Province. Moreo- ver, combined weight was introduced to judge each evaluation index, so as to adjust clustering model. By case study, rainstorm disaster levels in 67 counties were obtained. Internal characteristics of each type were analyzed, and main correlation factors of each type were extracted. It was compared with statistical result of the rainstorm disaster, verifying validity and feasibility of the model. [ Conclusion] The method was feasible, and its evaluated result had better differentiation and decision accuracv.展开更多
The methods of deformation analysis and modeling at single point are realized easily now,but available approaches do not make full use of the information from monitoring points and can not reveal integrated deformatio...The methods of deformation analysis and modeling at single point are realized easily now,but available approaches do not make full use of the information from monitoring points and can not reveal integrated deformation regularity of a deformable body.This paper presents a fuzzy clusetering method to analyze the correlative relations of multiple points in space,and then the spatial model for a practical dangerous rockmass in the area of Three Gorges,Yangtze River is established,in which the correlation of six points in space is analyzed by geological investigation and fuzzy set theory.展开更多
The work on the paper is focused on the use of Fractal Dimension in clustering for evolving data streams. Recently Anuradha et al. proposed a new approach based on Relative Change in Fractal Dimension (RCFD) and dampe...The work on the paper is focused on the use of Fractal Dimension in clustering for evolving data streams. Recently Anuradha et al. proposed a new approach based on Relative Change in Fractal Dimension (RCFD) and damped window model for clustering evolving data streams. Through observations on the aforementioned referred paper, this paper reveals that the formation of quality cluster is heavily predominant on the suitable selection of threshold value. In the above-mentionedpaper Anuradha et al. have used a heuristic approach for fixing the threshold value. Although the outcome of the approach is acceptable, however, the approach is purely based on random selection and has no basis to claim the acceptability in general. In this paper a novel method is proposed to optimally compute threshold value using a population based randomized approach known as particle swarm optimization (PSO). Simulations are done on two huge data sets KDD Cup 1999 data set and the Forest Covertype data set and the results of the cluster quality are compared with the fixed approach. The comparison reveals that the chosen value of threshold by Anuradha et al., is robust and can be used with confidence.展开更多
In this paper we present a signal processing method capable of detecting cardiopathies in electrocardiograms that was implemented in FPGA. The adopted procedure is based on fuzzy clustering to reduce the amount of dat...In this paper we present a signal processing method capable of detecting cardiopathies in electrocardiograms that was implemented in FPGA. The adopted procedure is based on fuzzy clustering to reduce the amount of data sampling, and a comparison with samples from a previously established database. By using the correlation method on the samples, it is possible to establish an initial indication of a cardiopathy. The reduced number of samples of the clustering process turns the processing simpler and allows its hardware implementation. According to the tests conducted, the method achieves 91% correct diagnoses.展开更多
The COVID-19 pandemic has caused an unprecedented spike in confirmed cases in 230 countries globally. In this work, a set of data from the COVID-19 coronavirus outbreak has been subjected to two well-known unsupervise...The COVID-19 pandemic has caused an unprecedented spike in confirmed cases in 230 countries globally. In this work, a set of data from the COVID-19 coronavirus outbreak has been subjected to two well-known unsupervised learning techniques: K-means clustering and correlation. The COVID-19 virus has infected several nations, and K-means automatically looks for undiscovered clusters of those infections. To examine the spread of COVID-19 before a vaccine becomes widely available, this work has used unsupervised approaches to identify the crucial county-level confirmed cases, death cases, recover cases, total_cases_per_million, and total_deaths_per_million aspects of county-level variables. We combined countries into significant clusters using this feature subspace to assist more in-depth disease analysis efforts. As a result, we used a clustering technique to examine various trends in COVID-19 incidence and mortality across nations. This technique took the key components of a trajectory and incorporates them into a K-means clustering process. We separated the trend lines into measures that characterize various features of a trend. The measurements were first reduced in dimension, then clustered using a K-means algorithm. This method was used to individually calculate the incidence and death rates and then compare them.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
基金funded by the National Key R&D Program Project(No.2022YFC3103604).
文摘The comprehension of sediment grain size parameters and the corresponding sedimentary environment holds paramount importance in elucidating the engineering geological attributes of the subaqueous seabed.This study delineated the sedimentary environment zoning in the northern sea area of Qingdao through cluster analysis of grain size parameters derived from 123 surface sediment samples.The study analyzed the correlation between sediment geotechnical indices and grain size parameters across diverse sedimentary environments.A correlation equation was established for samples exhibiting a strong correlation.The study found four distinct sedimentary environments in the study area:coastal,transitional,shallow sea,and residual.Within the same sedimentary environment,the average grain size and sorting coefficient exhibit significant correlations with geotechnical indices such as water content,density,shear strength,plastic limit,liquid limit,and plastic index.However,notable disparities in the correlation between grain size parameters and geotechnical indices emerge across different sedimentary environments.
基金Joint Seismological Science Foundation of China (95-07-436)
文摘The growing correlation length prior to the moderate-great earthquakes occurred in Gansu Province and its nearby area since 1986 has been studied using the method of single-link cluster analysis (SLC). According to different conditions in the source area, the circular spatial window centered in the epicenter and the parallelgrammic spatial window along the fault belt have been selected. The results show that the phenomena of growing correlation length have been observed before the earthquakes studied in the paper.
基金This study was sponsored by the National Natural Science Foundation of China(No.51504257)the State Key Research Development Program of China(No.2016YFC0600704)+1 种基金the Fundamental Research Funds for the Central Universities(Yueqi Outstanding Scholars)(No.2018B051616,2021JCCXLJ01,2021YJSLJ06)the Open Fund of the State Key Laboratory of Coal Mine Disaster Dynamics and Control(No.2011DA105287-FW201604).
文摘To extract more in-depth information of acoustic emission(AE)signal-cloud in rock failure under triaxial compression,the spatial correlation of scattering AE events in a granite sample is effectively described by the cube-cluster model.First,the complete connection of the fracture network is regarded as a critical state.Then,according to the Hoshen-Kopelman(HK)algorithm,the real-time estimation of fracture con-nection is effectively made and a dichotomy between cube size and pore fraction is suggested to solve such a challenge of the one-to-one match between complete connection and cluster size.After,the 3D cube clusters are decomposed into orthogonal layer clusters,which are then transformed into the ellip-soid models.Correspondingly,the anisotropy evolution of fracture network could be visualized by three orthogonal ellipsoids and quantitatively described by aspect ratio.Besides,the other three quantities of centroid axis length,porosity,and fracture angle are analyzed to evaluate the evolution of cube cluster.The result shows the sample dilatancy is strongly correlated to four quantities of aspect ratio,centroid axis length,and porosity as well as fracture angle.Besides,the cube cluster model shows a potential pos-sibility to predict the evolution of fracture angle.So,the cube cluster model provides an in-depth view of spatial correlation to describe the AE signal-cloud.
基金Supported by Platform Construction for Germplasm Resources of China Tobacco (2007, 152)
文摘Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.
基金Supported by Special Item of the Public Sector(Meteorological) Science Research(GYHY201106040)
文摘[ Objective] The research aimed to study assessment index system of the rainstorm disaster in Fujian Province based on spectral cluste- ring model with grey correlation analysis. [Method] According to meteorological disaster yearbook in Fujian Province, by comprehensively consider- ing disaster-inducing factor, disaster-inducing environment, disaster-sustaining body and regional disaster-prevention level, evaluation index system of the regional rainstorm disaster in Fujian was established. By spectral clustering model based on grey correlation analysis, dsk zoning of the rain- storm disaster was conducted in each area of Fujian. Finally, effect and application of the clustering model were analyzed by case research. [ Re- sult] In order to dig immanent connection among regional characteristics and improve disaster-preventing linkage performance of the evaluation unit, a spectral clustering model based on grey correlation analysis was used to conduct risk zoning of the rainstorm disaster in Fujian Province. Moreo- ver, combined weight was introduced to judge each evaluation index, so as to adjust clustering model. By case study, rainstorm disaster levels in 67 counties were obtained. Internal characteristics of each type were analyzed, and main correlation factors of each type were extracted. It was compared with statistical result of the rainstorm disaster, verifying validity and feasibility of the model. [ Conclusion] The method was feasible, and its evaluated result had better differentiation and decision accuracv.
文摘The methods of deformation analysis and modeling at single point are realized easily now,but available approaches do not make full use of the information from monitoring points and can not reveal integrated deformation regularity of a deformable body.This paper presents a fuzzy clusetering method to analyze the correlative relations of multiple points in space,and then the spatial model for a practical dangerous rockmass in the area of Three Gorges,Yangtze River is established,in which the correlation of six points in space is analyzed by geological investigation and fuzzy set theory.
文摘The work on the paper is focused on the use of Fractal Dimension in clustering for evolving data streams. Recently Anuradha et al. proposed a new approach based on Relative Change in Fractal Dimension (RCFD) and damped window model for clustering evolving data streams. Through observations on the aforementioned referred paper, this paper reveals that the formation of quality cluster is heavily predominant on the suitable selection of threshold value. In the above-mentionedpaper Anuradha et al. have used a heuristic approach for fixing the threshold value. Although the outcome of the approach is acceptable, however, the approach is purely based on random selection and has no basis to claim the acceptability in general. In this paper a novel method is proposed to optimally compute threshold value using a population based randomized approach known as particle swarm optimization (PSO). Simulations are done on two huge data sets KDD Cup 1999 data set and the Forest Covertype data set and the results of the cluster quality are compared with the fixed approach. The comparison reveals that the chosen value of threshold by Anuradha et al., is robust and can be used with confidence.
文摘In this paper we present a signal processing method capable of detecting cardiopathies in electrocardiograms that was implemented in FPGA. The adopted procedure is based on fuzzy clustering to reduce the amount of data sampling, and a comparison with samples from a previously established database. By using the correlation method on the samples, it is possible to establish an initial indication of a cardiopathy. The reduced number of samples of the clustering process turns the processing simpler and allows its hardware implementation. According to the tests conducted, the method achieves 91% correct diagnoses.
文摘The COVID-19 pandemic has caused an unprecedented spike in confirmed cases in 230 countries globally. In this work, a set of data from the COVID-19 coronavirus outbreak has been subjected to two well-known unsupervised learning techniques: K-means clustering and correlation. The COVID-19 virus has infected several nations, and K-means automatically looks for undiscovered clusters of those infections. To examine the spread of COVID-19 before a vaccine becomes widely available, this work has used unsupervised approaches to identify the crucial county-level confirmed cases, death cases, recover cases, total_cases_per_million, and total_deaths_per_million aspects of county-level variables. We combined countries into significant clusters using this feature subspace to assist more in-depth disease analysis efforts. As a result, we used a clustering technique to examine various trends in COVID-19 incidence and mortality across nations. This technique took the key components of a trajectory and incorporates them into a K-means clustering process. We separated the trend lines into measures that characterize various features of a trend. The measurements were first reduced in dimension, then clustered using a K-means algorithm. This method was used to individually calculate the incidence and death rates and then compare them.
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.
