In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate tim...In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.展开更多
Nano-Fe2O3/goldmine complex was obtained by chemical coprecipitation reaction on the surface of goldmine waste-solid. Being used as the heterogeneous catalyst in Fenton-like advanced oxidation processes (AOPs), its tr...Nano-Fe2O3/goldmine complex was obtained by chemical coprecipitation reaction on the surface of goldmine waste-solid. Being used as the heterogeneous catalyst in Fenton-like advanced oxidation processes (AOPs), its treatment effect was studied in the removal performance of industrial dyes effluent. Although the maximal COD removal efficiency would reach 35.4% when 5 mL NaClO was added in 100 mL industrial dyes effluent, it is found that by using nano-Fe2O3/goldmine system, the COD removal efficiency of 13,000 mg/L dyes wastewater could reach up to 75.5% in the presence of 30 g/L nano-Fe2O3/goldmine complex and 50 mL/L NaClO at 50。C.展开更多
The express delivery induslry of China is relatively backward in the automation degree of critical business processes. The basic reason is that the business-related supporting data, which is scattered in the multidime...The express delivery induslry of China is relatively backward in the automation degree of critical business processes. The basic reason is that the business-related supporting data, which is scattered in the multidimensional space, is difficult to utilize and process. This paper proposes an automatic data acquisition fi-amework to resolve such difficulty, which synthetically utilize intelligent inemet of things （IoT）, semantic web and complext event processing （CEP） technology. We also implement a SCEP prototype system with the capability of real-time detecting complex business events on the goods sorting line, which adopts a detection method consisting of four stages. The simulation results show that the system has good performance and feasible enough to deal with the complex business which need data support fTom multidimensional space.展开更多
基金Project(61025015) supported by the National Natural Science Funds for Distinguished Young Scholars of ChinaProject(21106036) supported by the National Natural Science Foundation of China+2 种基金Project(200805331103) supported by Research Fund for the Doctoral Program of Higher Education of ChinaProject(NCET-08-0576) supported by Program for New Century Excellent Talents in Universities of ChinaProject(11B038) supported by Scientific Research Fund for the Excellent Youth Scholars of Hunan Provincial Education Department,China
文摘In order to effectively analyse the multivariate time series data of complex process,a generic reconstruction technology based on reduction theory of rough sets was proposed,Firstly,the phase space of multivariate time series was originally reconstructed by a classical reconstruction technology.Then,the original decision-table of rough set theory was set up according to the embedding dimensions and time-delays of the original reconstruction phase space,and the rough set reduction was used to delete the redundant dimensions and irrelevant variables and to reconstruct the generic phase space,Finally,the input vectors for the prediction of multivariate time series were extracted according to generic reconstruction results to identify the parameters of prediction model.Verification results show that the developed reconstruction method leads to better generalization ability for the prediction model and it is feasible and worthwhile for application.
文摘Nano-Fe2O3/goldmine complex was obtained by chemical coprecipitation reaction on the surface of goldmine waste-solid. Being used as the heterogeneous catalyst in Fenton-like advanced oxidation processes (AOPs), its treatment effect was studied in the removal performance of industrial dyes effluent. Although the maximal COD removal efficiency would reach 35.4% when 5 mL NaClO was added in 100 mL industrial dyes effluent, it is found that by using nano-Fe2O3/goldmine system, the COD removal efficiency of 13,000 mg/L dyes wastewater could reach up to 75.5% in the presence of 30 g/L nano-Fe2O3/goldmine complex and 50 mL/L NaClO at 50。C.
文摘The express delivery induslry of China is relatively backward in the automation degree of critical business processes. The basic reason is that the business-related supporting data, which is scattered in the multidimensional space, is difficult to utilize and process. This paper proposes an automatic data acquisition fi-amework to resolve such difficulty, which synthetically utilize intelligent inemet of things （IoT）, semantic web and complext event processing （CEP） technology. We also implement a SCEP prototype system with the capability of real-time detecting complex business events on the goods sorting line, which adopts a detection method consisting of four stages. The simulation results show that the system has good performance and feasible enough to deal with the complex business which need data support fTom multidimensional space.
