基于附加虚拟阻抗和蚁群优化算法的动态等效模型在线修正方法

提出基于虚拟阻抗的动态等效模型在线修正方法。首先,指出等值过程中不合理的聚类算法、对时变系统的定常化假设是误差主要来源。接着,提出通过等效模型的在线修正以克服系统时变性所导致的误差。由于等效模型可调参数过多,难以对所有参数进行调整。为此,在等效发电机、等效电动机节点引入附加虚拟阻抗,应用蚁群优化算法进行调节,以实现边界点最佳功率匹配,并利用广域测量系统(wide area measurement system,WAMS)提供的实测数据对动态等效模型进行定时修正。最后,IEEE 10机39母线系统的等值计算结果表明：算法较好地改进了动态等效模型的静态精度与暂态精度,提高了模型的强壮性。     

Melt index prediction by RBF neural network optimized with an adaptive new ant colony optimization algorithm

Melt index (MI) is a crucial indicator in determining the product specifications and grades of polypropylene (PP). The prediction of MI, which is important in quality control of the PP polymerization process, is studied in this work. Based on RBF (radial basis function) neural network, a soft‐sensor model (RBF model) of the PP process is developed to infer the MI of PP from a bunch of process variables. Considering that the PP process is too complicated for the RBF neural network with a general set of parameters, a new ant colony optimization (ACO) algorithm, N‐ACO, and its adaptive version, A‐N‐ACO, which aim at continuous optimizing problems are proposed to optimize the structure parameters of the RBF neural network, respectively, and the structure‐best models, N‐ACO‐RBF model and A‐N‐ACO‐RBF model for the MI prediction of propylene polymerization process, are presented then. Based on the data from a real PP production plant, a detailed comparison research among the models is carried out. The research results confirm the prediction accuracy of the models and also prove the effectiveness of proposed N‐ACO and A‐N‐ACO optimization approaches in solving continuous optimizing problem. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Experimental investigation of interfacial tension and oil swelling for asphaltenic crude oil/carbonated water system

The phenomenon of oil swelling at the oil-carbonated water (CW) system could be an important mechanism during the water alternating gas (WAG) injection process. Nevertheless, the study of the main mechanisms during water flooding (WF) is a complex topic that has not been well revealed so far, especially for asphaltenic crude oil (ACO) systems. Hence, the main goal of this experimental work is to determine the influence of carbon dioxide (CO₂) within the water phase in the interfacial tension (IFT) between water and crude oil for an extensive range of pressures between 400 psi and 2000 psi (i.e. 2.76–13.79 MPa), under two temperatures of 313.15 and 323.15 K (i.e. 40 and 50 °C) by axisymmetric drop shape analysis (ADSA) method. The experimental results demonstrate that the water/ CW and crude oil IFTs decline with time. The value of dynamic IFT (DIFT) between CW and crude oil decreased about 6 mN/m in comparison with the oil–water DIFT. As a result of the CO₂ solubility, the crude oil droplet swells with increasing pressure. When the temperature rises, the effects of increasing entropy phenomena and decline of liquids density is dominant compared to the solubility of CO₂. Thus, the volume of oil droplet increases with temperature, unexpectedly. In addition, as thetemperature increases the water/CW-Oil IFT is slightly reduced over a wide range of pressure evaluated. Nevertheless, there is a slight increase as the pressure increases for the water–oil system. According to the predicted results, interfacial tension of the CW-oil system declines with increasing pressure until the solubility of CO₂ is reached to a maximum value and then approximately remains changeless.     

基于改进蚁群优化算法的配电网线损计算新方法

针对径向基函数（radialbasisfunction,RBF）神经网络收敛速度慢、易于陷入局部极小点的问题,提出了基于蚁群优化算法（antcolonyoptimization,ACO）的RBF神经网络线损计算新方法。通过引入交叉和变异改进后的ACO训练BRF神经网络,使其具有神经网络广映射能力、ACO快速全局收敛以及启发式学习等特点。利用优化后的RBF神经网络算法拟合配电线路线损与特征参数之间的复杂关系,实现配电网线损计算。仿真结果表明,优化后的BRF神经网络算法的线损计算误差基本在1％以内,具有良好的收敛能力和较快的计算速度。     

Cold-induced ethylene in relation to chilling injury and chilling sensitivity in the non-climacteric fruit of zucchini (Cucurbita pepo L.)

Zucchini is a non-climacteric fruit which is harvested immature on reaching about 18 cm in length. In the present paper we compare fruit quality parameters in different zucchini cultivars with the production of ethylene and the expression of two ethylene biosynthesis genes (CpACS1 and CpACO1) throughout postharvest storage at 4, 12 and 20 °C. In fruit stored at 12 or 20° ethylene production and expression of CpACS1 and CpACO1 genes remained very low throughout the whole storage period. Ethylene production was also low at 4 °C, but was induced rapidly upon transfer to 20 °C for a minimum of 4 h. The expression of both CpACS1 and CpACO1 genes was also induced by storage at 4 °C. This cold-induced ethylene is not necessary for triggering chilling injury (CI) symptoms in zucchini, since they were already evident in the cold chambers before rewarming of the fruit and, therefore, before the burst of ethylene. However, the level of the cold-induced ethylene was lower in those cultivars that were more tolerant to CI, and it fell in response to temperature conditioning treatments that alleviate CI symptoms.     

一种改进的自适应蚁群算法

蚁群算法是一种新型的模拟进化算法,研究表明此算法具有一些优良性质,但是蚁群算法容易陷入局部最优。分析了蚁群算法陷入局部最优的主要原因,根据算法陷入最优的原因提出一种判断局部最优的方法;在蚁群算法中引入判断局部最优的策略,当算法陷入局部最优时对参数做相应的变化,来克服蚁群算法易陷入局部最优的缺陷。实验表明此方法行之有效。