将基于粗糙集的默认规则挖掘算法(Mining Default Rules Based on Rough Set,MDRBR)用于电力系统短期负荷预测,首先采用基于Gini指标的粗糙集离散化算法对气温、湿度等影响负荷的条件属性进行离散化,同时兼顾了条件属性和决策属性。在...将基于粗糙集的默认规则挖掘算法(Mining Default Rules Based on Rough Set,MDRBR)用于电力系统短期负荷预测,首先采用基于Gini指标的粗糙集离散化算法对气温、湿度等影响负荷的条件属性进行离散化,同时兼顾了条件属性和决策属性。在此基础上,通过计算规则的信赖度和支持度形成不同层次上符合初定阈值的带粗糙集算子的网络规则集,能减少因噪音的影响而产生的多余规则,提高规则产生和实际分类的效率,使所产生的分类规则集大大缩小,提高在使用规则时检索规则的效率。在负荷预测时自上而下逐层搜索规则网直至找出与所给信息相匹配的规则。粗糙集算子反映了规则的重要程度,同时作为选择规则的标准。实际应用表明,该方法能有效去除噪音,提高默认规则的挖掘效率,从而提高负荷预测的精度,具有一定的实用性。展开更多
Rough sets is one important method of data mining. Data mining processes such a great quantity of data inlarge database that the speed of Rough Sets Data Mining Algorithm is critical to Data Mining System. Utilizing n...Rough sets is one important method of data mining. Data mining processes such a great quantity of data inlarge database that the speed of Rough Sets Data Mining Algorithm is critical to Data Mining System. Utilizing net-work computing resources is an effective approach to improve the performance of Data Mining System. This paperproposes the concept of meta-information,which is used to describes the result of Rough Sets Data Mining in informa-tion system,and a meta-information-based method for rule parallel mining. This method decomposes the information-system into a lot of sub-information-system,dispatchs the task of generating meta-information of sub-information-sys-tem to some task performer in the network,and lets them parallel compute meta-information,then synthesizes themeta-information of sub-information-system to the meta-information of information system in the task synthesizer,and finally produces the rule according to the meta-information.展开更多
Rough set theory has proved to be a useful tool for rule induction. But, the theory based on indiscernibility relation or similarity relation cannot induce rules from decision tables with criteria. Greco et al have pr...Rough set theory has proved to be a useful tool for rule induction. But, the theory based on indiscernibility relation or similarity relation cannot induce rules from decision tables with criteria. Greco et al have proposed a new rough set approach based on dominance relation to handle the problems. The concept of dominance matrix is put forward and the dominance function is constructed to compute the minimal decision rules which are more general and applicable than the ones induced by the classical rough set theory. In addition, the methodology of simplification is presented to eliminate the redundancy in the rule set.展开更多
The concepts of Rough Decision Support System (RDSS) and equivalence matrix are introduced in this paper. Based on a rough attribute vector tree (RAVT) method, two kinds of matrix computation algorithms — Recursive M...The concepts of Rough Decision Support System (RDSS) and equivalence matrix are introduced in this paper. Based on a rough attribute vector tree (RAVT) method, two kinds of matrix computation algorithms — Recursive Matrix Computation (RMC) and Parallel Matrix Computation (PMC) are proposed for rules extraction, attributes reduction and data cleaning finished synchronously. The algorithms emphasize the practicability and efficiency of rules generation. A case study of PMC is analyzed, and a comparison experiment of RMC algorithm shows that it is feasible and efficient for data mining and knowledge-discovery in RDSS.展开更多
To give a better understanding of the morphological features of rock fracture surfaces within the framework of fractal geometry, the fractal characters of the rough surfaces in rock are analyzed according to the vario...To give a better understanding of the morphological features of rock fracture surfaces within the framework of fractal geometry, the fractal characters of the rough surfaces in rock are analyzed according to the variogram method. The study elaborates the significance of the geometric parameters-fractal dimension D and the intercept A on a log-log plot to the surface structure. Investigation extends to the anisotropy and heterogeneity of rock fracture surfaces, and the scale effect on the fractal estimation. The present study indicates that fractal dimension alone may not be sufficient to characterize the surface roughness of rock Joints. A reliable estimation should take into account the combination of D and A.展开更多
This paper discusses on the detection of outliers by hybridizing Rough_Outlier Algorithm with Negative Association Rules. An optimization algorithm named Binary Particle Swarm Optimization is used to improve the compu...This paper discusses on the detection of outliers by hybridizing Rough_Outlier Algorithm with Negative Association Rules. An optimization algorithm named Binary Particle Swarm Optimization is used to improve the computation of Non_Reduct in order to detect outliers.By using Binary PSO algorithm, the rules generated from Rough_Outliers algorithm is optimized, giving significant outliers object detected. The detection ofoutliers process is then enhanced by hybridizing it with Negative Association Rules. Frequent and Infrequent item sets from outlier rules are generated. Results show that the hybrid Rough_Negative algorithm is able to uncover meaningful knowledge of outliers from the frequent and infrequent item sets. These knowledge can then be used by experts in their field of domain for better decision making.展开更多
文摘将基于粗糙集的默认规则挖掘算法(Mining Default Rules Based on Rough Set,MDRBR)用于电力系统短期负荷预测,首先采用基于Gini指标的粗糙集离散化算法对气温、湿度等影响负荷的条件属性进行离散化,同时兼顾了条件属性和决策属性。在此基础上,通过计算规则的信赖度和支持度形成不同层次上符合初定阈值的带粗糙集算子的网络规则集,能减少因噪音的影响而产生的多余规则,提高规则产生和实际分类的效率,使所产生的分类规则集大大缩小,提高在使用规则时检索规则的效率。在负荷预测时自上而下逐层搜索规则网直至找出与所给信息相匹配的规则。粗糙集算子反映了规则的重要程度,同时作为选择规则的标准。实际应用表明,该方法能有效去除噪音,提高默认规则的挖掘效率,从而提高负荷预测的精度,具有一定的实用性。
文摘Rough sets is one important method of data mining. Data mining processes such a great quantity of data inlarge database that the speed of Rough Sets Data Mining Algorithm is critical to Data Mining System. Utilizing net-work computing resources is an effective approach to improve the performance of Data Mining System. This paperproposes the concept of meta-information,which is used to describes the result of Rough Sets Data Mining in informa-tion system,and a meta-information-based method for rule parallel mining. This method decomposes the information-system into a lot of sub-information-system,dispatchs the task of generating meta-information of sub-information-sys-tem to some task performer in the network,and lets them parallel compute meta-information,then synthesizes themeta-information of sub-information-system to the meta-information of information system in the task synthesizer,and finally produces the rule according to the meta-information.
文摘Rough set theory has proved to be a useful tool for rule induction. But, the theory based on indiscernibility relation or similarity relation cannot induce rules from decision tables with criteria. Greco et al have proposed a new rough set approach based on dominance relation to handle the problems. The concept of dominance matrix is put forward and the dominance function is constructed to compute the minimal decision rules which are more general and applicable than the ones induced by the classical rough set theory. In addition, the methodology of simplification is presented to eliminate the redundancy in the rule set.
文摘The concepts of Rough Decision Support System (RDSS) and equivalence matrix are introduced in this paper. Based on a rough attribute vector tree (RAVT) method, two kinds of matrix computation algorithms — Recursive Matrix Computation (RMC) and Parallel Matrix Computation (PMC) are proposed for rules extraction, attributes reduction and data cleaning finished synchronously. The algorithms emphasize the practicability and efficiency of rules generation. A case study of PMC is analyzed, and a comparison experiment of RMC algorithm shows that it is feasible and efficient for data mining and knowledge-discovery in RDSS.
文摘To give a better understanding of the morphological features of rock fracture surfaces within the framework of fractal geometry, the fractal characters of the rough surfaces in rock are analyzed according to the variogram method. The study elaborates the significance of the geometric parameters-fractal dimension D and the intercept A on a log-log plot to the surface structure. Investigation extends to the anisotropy and heterogeneity of rock fracture surfaces, and the scale effect on the fractal estimation. The present study indicates that fractal dimension alone may not be sufficient to characterize the surface roughness of rock Joints. A reliable estimation should take into account the combination of D and A.
文摘This paper discusses on the detection of outliers by hybridizing Rough_Outlier Algorithm with Negative Association Rules. An optimization algorithm named Binary Particle Swarm Optimization is used to improve the computation of Non_Reduct in order to detect outliers.By using Binary PSO algorithm, the rules generated from Rough_Outliers algorithm is optimized, giving significant outliers object detected. The detection ofoutliers process is then enhanced by hybridizing it with Negative Association Rules. Frequent and Infrequent item sets from outlier rules are generated. Results show that the hybrid Rough_Negative algorithm is able to uncover meaningful knowledge of outliers from the frequent and infrequent item sets. These knowledge can then be used by experts in their field of domain for better decision making.
