颞肌联合游离STA-脑贴敷融合术治疗ICA系ICVD

目的 评价颞肌联合游离颞浅动脉（STA）-脑贴敷融合术治疗颈内动脉（ICA）系ICVD的临床价值。方法 选取100例ICA系ICVD患者,分为间接组和直接组各50例。间接组给予颞肌联合游离STA-脑贴敷手术治疗,直接组给予STA-大脑中动脉（MCA）搭桥手术治疗,比较2组的治疗效果和并发症情况。结果 2组术前评分和治疗后2周NIHSS评分无明显差异（P〉0.05）;但经过4周~6个月治疗后神经功能障碍恢复评分比较,间接组明显优于直接组,差异有统计学意义（P〈0.01）。2组术后评估：手术血管再狭窄、高灌注脑出血及卒中逆转等间接组发生率低于直接组,差异有统计学意义（P〈0.05）。结论 颞肌联合游离STA-脑贴敷融合术治疗ICVD,手术操作技巧简单、手术时间短,其术后血流动力学稳定,效果显著。

Coordinated and uncoordinated design of LFO damping controllers with IPFC and PSS using ICA and SFLA

A single machine-infinite-bus(SMIB) system including the interline power flow controllers(IPFCs) and the power system stabilizer(PSS) controller is addressed. The linearized system model is considered for investigating the interactions among IPFC and PSS controllers. To improve the stability of whole system again different disturbances, a lead-lag controller is considered to produce supplementary signal. The proposed supplementary controller is implemented to improve the damping of the power system low frequency oscillations(LFOs). Imperialist optimization algorithm(ICA) and shuffled frog leaping algorithm(SFLA) are implemented to search for optimal supplementary controllers and PSS parameters. Moreover, singular value decomposition(SVD) method is utilized to select the most effective damping control signal of IPFC lead-lag controllers. To evaluate the system performance, different operating conditions are considered. Reponses of system in five modes including uncoordinated and coordinated modes of IPFC and PSS using ICA and SFLA are studied and compared. Considering the results, response of system without controller shows the highest overshoot and the longest settling time for rotor angel at the different operating conditions. In this mode of system, rotor speed has the highest overshoot. Rotor angel in the system with only PSS includes lower overshoot and oscillation than system without controller. When PSS is only implemented, rotor speed deviation has the longest settling time. Rotor speed deviation in the uncoordinated mode of IPFC and PSS shows lower overshoot than system with only PSS and without controller. It is noticeable that in this mode, rotor angel has higher overshoot than system with only PSS. The superiority of the suggested ICA-based coordinated controllers is obvious compared with SFLA-based coordinated controllers and other system modes. Responses of coordinated PSS and IPFC SFLA-based supplementary controllers include higher peak amplitude and longer settling time compared with coordinated IPFC and PSS ICA-based controllers. This comparison shows that overshoots, undershoots and the settling times are reduced considerably in coordinated mode of IPFC based controller and PSS using ICA. Analysis of the system performance shows that the proposed method has excellent response to different faults in power system.

Hourly traffic flow forecasting using a new hybrid modelling method

Short-term traffic flow forecasting is a significant part of intelligent transportation system.In some traffic control scenarios,obtaining future traffic flow in advance is conducive to highway management department to have sufficient time to formulate corresponding traffic flow control measures.In hence,it is meaningful to establish an accurate short-term traffic flow method and provide reference for peak traffic flow warning.This paper proposed a new hybrid model for traffic flow forecasting,which is composed of the variational mode decomposition(VMD)method,the group method of data handling(GMDH)neural network,bi-directional long and short term memory(BILSTM)network and ELMAN network,and is optimized by the imperialist competitive algorithm(ICA)method.To illustrate the performance of the proposed model,there are several comparative experiments between the proposed model and other models.The experiment results show that 1)BILSTM network,GMDH network and ELMAN network have better predictive performance than other single models;2)VMD can significantly improve the predictive performance of the ICA-GMDH-BILSTM-ELMAN model.The effect of VMD method is better than that of EEMD method and FEEMD method.To conclude,the proposed model which is made up of the VMD method,the ICA method,the BILSTM network,the GMDH network and the ELMAN network has excellent predictive ability for traffic flow series.