The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data s...The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining.展开更多
With the rapid development of computer technology, the current society has also entered the era of big data. Under this development background, the business activities of enterprises have also undergone profound chang...With the rapid development of computer technology, the current society has also entered the era of big data. Under this development background, the business activities of enterprises have also undergone profound changes under the influence of big data technology. At the same time, in the process of enterprise operation and development, financial and business integration, which integrates business work with financial management, has also become the main development trend and is highly praised by most enterprises. However, judging from the actual situation of social enterprises in our country, many large-scale financial integration activities cannot be carried out smoothly and can only be carried out reluctantly. The process is also facing many difficulties. In view of this, this paper analyzes the significance and difficulties of financial and business integration in the era of big data, and puts forward scientific and effective development strategies.展开更多
According to the frequency property of Phasedarray ground penetrating radar(PGPR),this paper gives a frequency point slice method based on Wigner time-frequency analysis.This method solves the problem of analysis for ...According to the frequency property of Phasedarray ground penetrating radar(PGPR),this paper gives a frequency point slice method based on Wigner time-frequency analysis.This method solves the problem of analysis for the PGPR's superposition data and makes detecting outcome simpler and detecting target more recognizable.At last,the analytical results of road test data of the Three Gorges prove the analytical method efficient.展开更多
As sandstone layers in thin interbedded section are difficult to identify,conventional model-driven seismic inversion and data-driven seismic prediction methods have low precision in predicting them.To solve this prob...As sandstone layers in thin interbedded section are difficult to identify,conventional model-driven seismic inversion and data-driven seismic prediction methods have low precision in predicting them.To solve this problem,a model-data-driven seismic AVO(amplitude variation with offset)inversion method based on a space-variant objective function has been worked out.In this method,zero delay cross-correlation function and F norm are used to establish objective function.Based on inverse distance weighting theory,change of the objective function is controlled according to the location of the target CDP(common depth point),to change the constraint weights of training samples,initial low-frequency models,and seismic data on the inversion.Hence,the proposed method can get high resolution and high-accuracy velocity and density from inversion of small sample data,and is suitable for identifying thin interbedded sand bodies.Tests with thin interbedded geological models show that the proposed method has high inversion accuracy and resolution for small sample data,and can identify sandstone and mudstone layers of about one-30th of the dominant wavelength thick.Tests on the field data of Lishui sag show that the inversion results of the proposed method have small relative error with well-log data,and can identify thin interbedded sandstone layers of about one-15th of the dominant wavelength thick with small sample data.展开更多
There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analys...There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analysis. This paper proposes a data pre-processing model based on intelligent algorithms. Firstly, we introduce the integrated network platform of ocean observation. Next, the preprocessing model of data is presemed, and an imelligent cleaning model of data is proposed. Based on fuzzy clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering. The proposed dynamic algorithm can automatically f＇md the new clustering center with the updated sample data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results through observation data analysis.展开更多
Currently the indoor environment quality is described or evaluated mainly by the subjective or objective data.However,research increasingly has demonstrated that objective and subjective data both had some weaknesses ...Currently the indoor environment quality is described or evaluated mainly by the subjective or objective data.However,research increasingly has demonstrated that objective and subjective data both had some weaknesses to characterize the indoor environment quality,and they can compensate for each other's relative weaknesses.Hence,this study aims to develop an integration model to allow indoor subjective and objective data to be combined based on the structural equation modeling approach,using the Northeast China residential indoor environmental survey data.The results indicated that the integration model had a good fit for the survey data,and the model validity was confirmed.Moreover,in contrast to the subjective data(R^(2)=0.363)and objective data(R^(2)=0.239),the integrated data(R^(2)=0.553)improved the explanatory power on the satisfaction with the overall indoor environment.Furthermore,this integration model demonstrated that indoor subjective data assigned more weights to the integrated data than the corresponding objective data.The association strength of thermal environment and indoor air quality(0.43 or 0.47)was the strongest among the interactions of thermal,air quality,acoustic,and lighting environments.Consequently,the main contribution of this paper was that it provided a comprehensive model to accomplish the integration of indoor environmental subjective and objective data,promoting the ability to describe and assess the indoor environment quality.展开更多
利用出行特征数据识别综合交通运输通道是合理布局城市群综合运输通道的关键技术。本文基于城市群手机信令数据,提出一种综合运输通道识别四阶段方法框架,即数据准备、运输方式划分、最短路径搜索和通道识别。在运输方式划分方面,提出...利用出行特征数据识别综合交通运输通道是合理布局城市群综合运输通道的关键技术。本文基于城市群手机信令数据,提出一种综合运输通道识别四阶段方法框架,即数据准备、运输方式划分、最短路径搜索和通道识别。在运输方式划分方面,提出一种以运输平均速度和站点POI (Point of Interest)位置为决策变量的高速铁路、普速铁路和公路多方式划分算法。在最短路搜索方面,设计一种基于双向A*算法的最短路径搜索算法。在通道识别方面,基于行政边界划分通道区段并以运输量为综合运输通道区段判别参数。以京津冀城市群为例进行实证分析,结果表明,本文方法能够有效处理城市群手机信令数据,并识别出6条综合运输通道,验证了方法的可行性和准确性。在案例数据下,京津冀城市群公路和铁路的运输量占比分别为81.87%和18.13%,公路的短程运输客流较铁路更多;节假日因素显著提高了综合运输通道的客流量,平均运输量增加62.6%,平均客流周转量提升61.2%。展开更多
基金Supported by the National 973 Program of China(No.2006CB701305,No.2007CB310804)the National Natural Science Fundation of China(No.60743001)+1 种基金the Best National Thesis Fundation (No.2005047)the National New Century Excellent Talent Fundation (No.NCET-06-0618)
文摘The advanced data mining technologies and the large quantities of remotely sensed Imagery provide a data mining opportunity with high potential for useful results. Extracting interesting patterns and rules from data sets composed of images and associated ground data can be of importance in object identification, community planning, resource discovery and other areas. In this paper, a data field is presented to express the observed spatial objects and conduct behavior mining on them. First, most of the important aspects are discussed on behavior mining and its implications for the future of data mining. Furthermore, an ideal framework of the behavior mining system is proposed in the network environment. Second, the model of behavior mining is given on the observed spatial objects, including the objects described by the first feature data field and the main feature data field by means of the potential function. Finally, a case study about object identification in public is given and analyzed. The experimental results show that the new model is feasible in behavior mining.
基金Supported by National Basic Research Program of China（973 Program）（2013CB035500） National Natural Science Foundation of China（61233004,61221003,61074061）+1 种基金 International Cooperation Program of Shanghai Science and Technology Commission （12230709600） the Higher Education Research Fund for the Doctoral Program of China（20120073130006）
文摘With the rapid development of computer technology, the current society has also entered the era of big data. Under this development background, the business activities of enterprises have also undergone profound changes under the influence of big data technology. At the same time, in the process of enterprise operation and development, financial and business integration, which integrates business work with financial management, has also become the main development trend and is highly praised by most enterprises. However, judging from the actual situation of social enterprises in our country, many large-scale financial integration activities cannot be carried out smoothly and can only be carried out reluctantly. The process is also facing many difficulties. In view of this, this paper analyzes the significance and difficulties of financial and business integration in the era of big data, and puts forward scientific and effective development strategies.
基金Foundation item:Supported by the National Nature Science Founda-tion of China(50099620)and 863 Program Foundation of China(2001AA132050-03)
文摘According to the frequency property of Phasedarray ground penetrating radar(PGPR),this paper gives a frequency point slice method based on Wigner time-frequency analysis.This method solves the problem of analysis for the PGPR's superposition data and makes detecting outcome simpler and detecting target more recognizable.At last,the analytical results of road test data of the Three Gorges prove the analytical method efficient.
文摘As sandstone layers in thin interbedded section are difficult to identify,conventional model-driven seismic inversion and data-driven seismic prediction methods have low precision in predicting them.To solve this problem,a model-data-driven seismic AVO(amplitude variation with offset)inversion method based on a space-variant objective function has been worked out.In this method,zero delay cross-correlation function and F norm are used to establish objective function.Based on inverse distance weighting theory,change of the objective function is controlled according to the location of the target CDP(common depth point),to change the constraint weights of training samples,initial low-frequency models,and seismic data on the inversion.Hence,the proposed method can get high resolution and high-accuracy velocity and density from inversion of small sample data,and is suitable for identifying thin interbedded sand bodies.Tests with thin interbedded geological models show that the proposed method has high inversion accuracy and resolution for small sample data,and can identify sandstone and mudstone layers of about one-30th of the dominant wavelength thick.Tests on the field data of Lishui sag show that the inversion results of the proposed method have small relative error with well-log data,and can identify thin interbedded sandstone layers of about one-15th of the dominant wavelength thick with small sample data.
基金Key Science and Technology Project of the Shanghai Committee of Science and Technology, China (No.06dz1200921)Major Basic Research Project of the Shanghai Committee of Science and Technology(No.08JC1400100)+1 种基金Shanghai Talent Developing Foundation, China(No.001)Specialized Foundation for Excellent Talent of Shanghai,China
文摘There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analysis. This paper proposes a data pre-processing model based on intelligent algorithms. Firstly, we introduce the integrated network platform of ocean observation. Next, the preprocessing model of data is presemed, and an imelligent cleaning model of data is proposed. Based on fuzzy clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering. The proposed dynamic algorithm can automatically f＇md the new clustering center with the updated sample data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results through observation data analysis.
基金supported by the National Natural Science Foundation of China(No.51978121 and No.51578103)the Key Projects in the National Science&Technology Pillar Program during the 12th Five-year Plan Period of China(No.2012BAJ 02B05)the National Key R&D Program during the 13th Five-year Plan Period of China(No.2018YFD1100701).
文摘Currently the indoor environment quality is described or evaluated mainly by the subjective or objective data.However,research increasingly has demonstrated that objective and subjective data both had some weaknesses to characterize the indoor environment quality,and they can compensate for each other's relative weaknesses.Hence,this study aims to develop an integration model to allow indoor subjective and objective data to be combined based on the structural equation modeling approach,using the Northeast China residential indoor environmental survey data.The results indicated that the integration model had a good fit for the survey data,and the model validity was confirmed.Moreover,in contrast to the subjective data(R^(2)=0.363)and objective data(R^(2)=0.239),the integrated data(R^(2)=0.553)improved the explanatory power on the satisfaction with the overall indoor environment.Furthermore,this integration model demonstrated that indoor subjective data assigned more weights to the integrated data than the corresponding objective data.The association strength of thermal environment and indoor air quality(0.43 or 0.47)was the strongest among the interactions of thermal,air quality,acoustic,and lighting environments.Consequently,the main contribution of this paper was that it provided a comprehensive model to accomplish the integration of indoor environmental subjective and objective data,promoting the ability to describe and assess the indoor environment quality.
文摘利用出行特征数据识别综合交通运输通道是合理布局城市群综合运输通道的关键技术。本文基于城市群手机信令数据,提出一种综合运输通道识别四阶段方法框架,即数据准备、运输方式划分、最短路径搜索和通道识别。在运输方式划分方面,提出一种以运输平均速度和站点POI (Point of Interest)位置为决策变量的高速铁路、普速铁路和公路多方式划分算法。在最短路搜索方面,设计一种基于双向A*算法的最短路径搜索算法。在通道识别方面,基于行政边界划分通道区段并以运输量为综合运输通道区段判别参数。以京津冀城市群为例进行实证分析,结果表明,本文方法能够有效处理城市群手机信令数据,并识别出6条综合运输通道,验证了方法的可行性和准确性。在案例数据下,京津冀城市群公路和铁路的运输量占比分别为81.87%和18.13%,公路的短程运输客流较铁路更多;节假日因素显著提高了综合运输通道的客流量,平均运输量增加62.6%,平均客流周转量提升61.2%。
