As the critical equipment,large axial-flow fan(LAF)is used widely in highway tunnels for ventilating.Note that any malfunction of LAF can cause severe consequences for traffic.Specifically,fault deterioration is suppr...As the critical equipment,large axial-flow fan(LAF)is used widely in highway tunnels for ventilating.Note that any malfunction of LAF can cause severe consequences for traffic.Specifically,fault deterioration is suppressed tremendously when an abnormal state is detected in the stage of early fault.Thus,the monitoring of the early fault characteristics is very difficult because of the low signal amplitude and system disturbance(or noise).In order to overcome this problem,a novel early fault judgment method to predict the operation trend is proposed in this paper.The vibration-electric information fusion,the support vector machine(SVM)with particle swarm optimization(PSO),and the cross-validation(CV)for predicting LAF operation states are proposed and discussed.Finally,the results of the experimental study verify that the performance of the proposed method is superior to that of the contrast models.展开更多
A new support vector machine （SVM） optimized by an improved particle swarm optimization （PSO） combined with simulated annealing algorithm （SA） was proposed. By incorporating with the simulated annealing method, ...A new support vector machine （SVM） optimized by an improved particle swarm optimization （PSO） combined with simulated annealing algorithm （SA） was proposed. By incorporating with the simulated annealing method, the global searching capacity of the particle swarm optimization（SAPSO） was enchanced, and the searching capacity of the particle swarm optimization was studied. Then, the improyed particle swarm optimization algorithm was used to optimize the parameters of SVM （c,σ and ε）. Based on the operational data provided by a regional power grid in north China, the method was used in the actual short term load forecasting. The results show that compared to the PSO-SVM and the traditional SVM, the average time of the proposed method in the experimental process reduces by 11.6 s and 31.1 s, and the precision of the proposed method increases by 1.24% and 3.18%, respectively. So, the improved method is better than the PSO-SVM and the traditional SVM.展开更多
Objective: The aim of this study was to identify the correlation between the clinicopathological characteristics and recurrence in early gastric cancer (EGC), what's more, we attempt to look for a predictive bioma...Objective: The aim of this study was to identify the correlation between the clinicopathological characteristics and recurrence in early gastric cancer (EGC), what's more, we attempt to look for a predictive biomarker to predict and treat for re-currence of EGC. Methods: This study retrospectively analyzed 178 early gastric cancer patients who had the complete post-operative and follow-up medical records in the First Affiliated Hospital of Yangtze University (China) between January 1995 to December 2005. All of them were followed-up to December 2009 regularly. Computer tomography (CT), endoscopy, and single photon emission computed tomography (SPET-CT) were used to diagnose for recurrence of EGC. Immunohistochem-istry (IHC) and fluorescence in situ hybridization (FISH) were used for the detection of cerbB2. Chi-square test was applied to this study for statistics analysis. Results: Fourteen patients had recurrence. Eighteen patients were cerbB2-positive, including twelve recurrence patients and six norecurrence patients. Sex, tumor depth, and lymph node metastasis were related to the recurrence of EGC. Also, cerbB2-positive patients had the higher recurrence rate compared to the cerbB2-negative patients. Conclusion: Recurrence of EGC after curative resection can be predicted by using some clinicopathological characteristics. CerbB2 can be used as a predictive biomarker for recurrence of EGC.展开更多
基金Project(2018YFB2002100)supported by the National Key R&D Program of China。
文摘As the critical equipment,large axial-flow fan(LAF)is used widely in highway tunnels for ventilating.Note that any malfunction of LAF can cause severe consequences for traffic.Specifically,fault deterioration is suppressed tremendously when an abnormal state is detected in the stage of early fault.Thus,the monitoring of the early fault characteristics is very difficult because of the low signal amplitude and system disturbance(or noise).In order to overcome this problem,a novel early fault judgment method to predict the operation trend is proposed in this paper.The vibration-electric information fusion,the support vector machine(SVM)with particle swarm optimization(PSO),and the cross-validation(CV)for predicting LAF operation states are proposed and discussed.Finally,the results of the experimental study verify that the performance of the proposed method is superior to that of the contrast models.
基金Project(50579101) supported by the National Natural Science Foundation of China
文摘A new support vector machine （SVM） optimized by an improved particle swarm optimization （PSO） combined with simulated annealing algorithm （SA） was proposed. By incorporating with the simulated annealing method, the global searching capacity of the particle swarm optimization（SAPSO） was enchanced, and the searching capacity of the particle swarm optimization was studied. Then, the improyed particle swarm optimization algorithm was used to optimize the parameters of SVM （c,σ and ε）. Based on the operational data provided by a regional power grid in north China, the method was used in the actual short term load forecasting. The results show that compared to the PSO-SVM and the traditional SVM, the average time of the proposed method in the experimental process reduces by 11.6 s and 31.1 s, and the precision of the proposed method increases by 1.24% and 3.18%, respectively. So, the improved method is better than the PSO-SVM and the traditional SVM.
文摘Objective: The aim of this study was to identify the correlation between the clinicopathological characteristics and recurrence in early gastric cancer (EGC), what's more, we attempt to look for a predictive biomarker to predict and treat for re-currence of EGC. Methods: This study retrospectively analyzed 178 early gastric cancer patients who had the complete post-operative and follow-up medical records in the First Affiliated Hospital of Yangtze University (China) between January 1995 to December 2005. All of them were followed-up to December 2009 regularly. Computer tomography (CT), endoscopy, and single photon emission computed tomography (SPET-CT) were used to diagnose for recurrence of EGC. Immunohistochem-istry (IHC) and fluorescence in situ hybridization (FISH) were used for the detection of cerbB2. Chi-square test was applied to this study for statistics analysis. Results: Fourteen patients had recurrence. Eighteen patients were cerbB2-positive, including twelve recurrence patients and six norecurrence patients. Sex, tumor depth, and lymph node metastasis were related to the recurrence of EGC. Also, cerbB2-positive patients had the higher recurrence rate compared to the cerbB2-negative patients. Conclusion: Recurrence of EGC after curative resection can be predicted by using some clinicopathological characteristics. CerbB2 can be used as a predictive biomarker for recurrence of EGC.
