With the reform of rural network enterprise system,the speed of transfer property rights in rural power enterprises is accelerated.The evaluation of the operation and development status of rural power enterprises is d...With the reform of rural network enterprise system,the speed of transfer property rights in rural power enterprises is accelerated.The evaluation of the operation and development status of rural power enterprises is directly related to the future development and investment direction of rural power enterprises.At present,the evaluation of the production and operation of rural network enterprises and the development status of power network only relies on the experience of the evaluation personnel,sets the reference index,and forms the evaluation results through artificial scoring.Due to the strong subjective consciousness of the evaluation results,the practical guiding significance is weak.Therefore,distributed data mining method in rural power enterprises status evaluation was proposed which had been applied in many fields,such as food science,economy or chemical industry.The distributed mathematical model was established by using principal component analysis(PCA)and regression analysis.By screening various technical indicators and determining their relevance,the reference value of evaluation results was improved.Combined with statistical program for social sciences(SPSS)data analysis software,the operation status of rural network enterprises was evaluated,and the rationality,effectiveness and economy of the evaluation was verified through comparison with current evaluation results and calculation examples of actual grid operation data.展开更多
Since the early 1990, significant progress in database technology has provided new platform for emerging new dimensions of data engineering. New models were introduced to utilize the data sets stored in the new genera...Since the early 1990, significant progress in database technology has provided new platform for emerging new dimensions of data engineering. New models were introduced to utilize the data sets stored in the new generations of databases. These models have a deep impact on evolving decision-support systems. But they suffer a variety of practical problems while accessing real-world data sources. Specifically a type of data storage model based on data distribution theory has been increasingly used in recent years by large-scale enterprises, while it is not compatible with existing decision-support models. This data storage model stores the data in different geographical sites where they are more regularly accessed. This leads to considerably less inter-site data transfer that can reduce data security issues in some circumstances and also significantly improve data manipulation transactions speed. The aim of this paper is to propose a new approach for supporting proactive decision-making that utilizes a workable data source management methodology. The new model can effectively organize and use complex data sources, even when they are distributed in different sites in a fragmented form. At the same time, the new model provides a very high level of intellectual management decision-support by intelligent use of the data collections through utilizing new smart methods in synthesizing useful knowledge. The results of an empirical study to evaluate the model are provided.展开更多
To make business policy, market analysis, corporate decision, fraud detection, etc., we have to analyze and work with huge amount of data. Generally, such data are taken from different sources. Researchers are using d...To make business policy, market analysis, corporate decision, fraud detection, etc., we have to analyze and work with huge amount of data. Generally, such data are taken from different sources. Researchers are using data mining to perform such tasks. Data mining techniques are used to find hidden information from large data source. Data mining is using for various fields: Artificial intelligence, Bank, health and medical, corruption, legal issues, corporate business, marketing, etc. Special interest is given to associate rules, data mining algorithms, decision tree and distributed approach. Data is becoming larger and spreading geographically. So it is difficult to find better result from only a central data source. For knowledge discovery, we have to work with distributed database. On the other hand, security and privacy considerations are also another factor for de-motivation of working with centralized data. For this reason, distributed database is essential for future processing. In this paper, we have proposed a framework to study data mining in distributed environment. The paper presents a framework to bring out actionable knowledge. We have shown some level by which we can generate actionable knowledge. Possible tools and technique for these levels are discussed.展开更多
A new method of establishing rolling load distribution model was developed by online intelligent information-processing technology for plate rolling. The model combines knowledge model and mathematical model with usin...A new method of establishing rolling load distribution model was developed by online intelligent information-processing technology for plate rolling. The model combines knowledge model and mathematical model with using knowledge discovery in database （KDD） and data mining （DM） as the start. The online maintenance and optimization of the load model are realized. The effectiveness of this new method was testified by offline simulation and online application.展开更多
This paper mainly introduces the development and implementation of the user centered data mining service ontology on Universal Knowledge Grid （UKG）. UKG is an ontology-based grid architecture model to build large-sc...This paper mainly introduces the development and implementation of the user centered data mining service ontology on Universal Knowledge Grid （UKG）. UKG is an ontology-based grid architecture model to build large-scale distributed knowledge discovery system on the grid. The data mining ontology services are the main service offering by UKG. It can meet the user requirements of knowledge discovery in different domains and different hierarchies and make the system exoteric, extensible and high usable. A data min- ing solution for money laundering is introduced.展开更多
基金Supported by Funding(2017RAXXJ075)from Harbin Applied Technology Research and Development Project
文摘With the reform of rural network enterprise system,the speed of transfer property rights in rural power enterprises is accelerated.The evaluation of the operation and development status of rural power enterprises is directly related to the future development and investment direction of rural power enterprises.At present,the evaluation of the production and operation of rural network enterprises and the development status of power network only relies on the experience of the evaluation personnel,sets the reference index,and forms the evaluation results through artificial scoring.Due to the strong subjective consciousness of the evaluation results,the practical guiding significance is weak.Therefore,distributed data mining method in rural power enterprises status evaluation was proposed which had been applied in many fields,such as food science,economy or chemical industry.The distributed mathematical model was established by using principal component analysis(PCA)and regression analysis.By screening various technical indicators and determining their relevance,the reference value of evaluation results was improved.Combined with statistical program for social sciences(SPSS)data analysis software,the operation status of rural network enterprises was evaluated,and the rationality,effectiveness and economy of the evaluation was verified through comparison with current evaluation results and calculation examples of actual grid operation data.
文摘Since the early 1990, significant progress in database technology has provided new platform for emerging new dimensions of data engineering. New models were introduced to utilize the data sets stored in the new generations of databases. These models have a deep impact on evolving decision-support systems. But they suffer a variety of practical problems while accessing real-world data sources. Specifically a type of data storage model based on data distribution theory has been increasingly used in recent years by large-scale enterprises, while it is not compatible with existing decision-support models. This data storage model stores the data in different geographical sites where they are more regularly accessed. This leads to considerably less inter-site data transfer that can reduce data security issues in some circumstances and also significantly improve data manipulation transactions speed. The aim of this paper is to propose a new approach for supporting proactive decision-making that utilizes a workable data source management methodology. The new model can effectively organize and use complex data sources, even when they are distributed in different sites in a fragmented form. At the same time, the new model provides a very high level of intellectual management decision-support by intelligent use of the data collections through utilizing new smart methods in synthesizing useful knowledge. The results of an empirical study to evaluate the model are provided.
文摘To make business policy, market analysis, corporate decision, fraud detection, etc., we have to analyze and work with huge amount of data. Generally, such data are taken from different sources. Researchers are using data mining to perform such tasks. Data mining techniques are used to find hidden information from large data source. Data mining is using for various fields: Artificial intelligence, Bank, health and medical, corruption, legal issues, corporate business, marketing, etc. Special interest is given to associate rules, data mining algorithms, decision tree and distributed approach. Data is becoming larger and spreading geographically. So it is difficult to find better result from only a central data source. For knowledge discovery, we have to work with distributed database. On the other hand, security and privacy considerations are also another factor for de-motivation of working with centralized data. For this reason, distributed database is essential for future processing. In this paper, we have proposed a framework to study data mining in distributed environment. The paper presents a framework to bring out actionable knowledge. We have shown some level by which we can generate actionable knowledge. Possible tools and technique for these levels are discussed.
文摘A new method of establishing rolling load distribution model was developed by online intelligent information-processing technology for plate rolling. The model combines knowledge model and mathematical model with using knowledge discovery in database （KDD） and data mining （DM） as the start. The online maintenance and optimization of the load model are realized. The effectiveness of this new method was testified by offline simulation and online application.
基金Supported by the National Natural Science Foun-dation of China (60403027) ,the National Key Technologies R&DProgram of China during the 10th Five-Year Plan Period(2002BA103A04 ,2001BA102A06-11)
文摘This paper mainly introduces the development and implementation of the user centered data mining service ontology on Universal Knowledge Grid （UKG）. UKG is an ontology-based grid architecture model to build large-scale distributed knowledge discovery system on the grid. The data mining ontology services are the main service offering by UKG. It can meet the user requirements of knowledge discovery in different domains and different hierarchies and make the system exoteric, extensible and high usable. A data min- ing solution for money laundering is introduced.
