This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three ...This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three different schemes. We use Matlab to realize the prediction of the sectional passenger flow of the Beijing subway Line 2 and make comparative analysis. The empirical research shows that combining data characteristics of sectional passenger flow with the BP neural network have good prediction accuracy.展开更多
The totally coded method (TCM) reveal the same law which governing the gain calculating for signal flow graph as Mason formula does. This algorithm is carried out merely in the domain of code operation. Based on pure ...The totally coded method (TCM) reveal the same law which governing the gain calculating for signal flow graph as Mason formula does. This algorithm is carried out merely in the domain of code operation. Based on pure code algorithm, it is more efficiency because any figure searching is no longer necessary. The code-series (CS), which are organized from node association table, have the holo-information nature, so that both the content and the sign of each gain-term can be determined via the coded method. The principle of this method is obvious and it is suited for computer programming. The capability of the computer-aided analysis for the active network, such as operation amplifier network, can be enhanced.展开更多
This article describes numerical simulation of gas pipeline network operation using high-accuracy computational fluid dynamics (CFD) simulators of the modes of gas mixture transmission through long, multi-line pipelin...This article describes numerical simulation of gas pipeline network operation using high-accuracy computational fluid dynamics (CFD) simulators of the modes of gas mixture transmission through long, multi-line pipeline systems (CFD-simulator). The approach used in CFD-simulators for modeling gas mixture transmission through long, branched, multi-section pipelines is based on tailoring the full system of fluid dynamics equations to conditions of unsteady, non-isothermal processes of the gas mixture flow. Identification, in a CFD-simulator, of safe parameters for gas transmission through compressor stations amounts to finding the interior points of admissible sets described by systems of nonlinear algebraic equalities and inequalities. Such systems of equalities and inequalities comprise a formal statement of technological, design, operational and other constraints to which operation of the network equipment is subject. To illustrate the practicability of the method of numerical simulation of a gas transmission network, we compare computation results and gas flow parameters measured on-site at the gas transmission enter-prise.展开更多
水库进行水力排沙时,高含沙水流过程可能会对鱼类等水生动物产生负面影响,其量化评估方法研究较为薄弱。为了预测和评估水库排沙过程对下游鱼类的影响,本文利用黄河花斑裸鲤和鲤鱼在高含沙水体中生存特性研究的实验数据,综合考虑含沙量...水库进行水力排沙时,高含沙水流过程可能会对鱼类等水生动物产生负面影响,其量化评估方法研究较为薄弱。为了预测和评估水库排沙过程对下游鱼类的影响,本文利用黄河花斑裸鲤和鲤鱼在高含沙水体中生存特性研究的实验数据,综合考虑含沙量和粒径、溶解氧、暴露时间、水温等因子对鱼类生存的影响,建立了基于IPSO-BP神经网络的高含沙水体对鱼类致死影响预测方法,对目标鱼类死亡率的预测误差小于6%。本文使用了与BP神经网络紧密耦合并引入动态参数和变异扰动的IPSO算法,较BP和PSO-BP神经网络预测能力更佳,相比国内外已有的Stress Index(SI)、Severity of Ill Effect(SEV)和多元拟合方法预测精度得到显著提升。分析表明,本文提出的预测方法能够考虑高含沙水体中鱼类生存受多环境因子联合制约,且多因子之间存在复杂关联的情况,可为评估高含沙水流过程对水生态的影响提供新的方法。展开更多
文摘This paper studies the short-term prediction methods of sectional passenger flow, and selects BP neural network combined with the characteristics of sectional passenger flow itself. With a case study, we design three different schemes. We use Matlab to realize the prediction of the sectional passenger flow of the Beijing subway Line 2 and make comparative analysis. The empirical research shows that combining data characteristics of sectional passenger flow with the BP neural network have good prediction accuracy.
文摘The totally coded method (TCM) reveal the same law which governing the gain calculating for signal flow graph as Mason formula does. This algorithm is carried out merely in the domain of code operation. Based on pure code algorithm, it is more efficiency because any figure searching is no longer necessary. The code-series (CS), which are organized from node association table, have the holo-information nature, so that both the content and the sign of each gain-term can be determined via the coded method. The principle of this method is obvious and it is suited for computer programming. The capability of the computer-aided analysis for the active network, such as operation amplifier network, can be enhanced.
文摘This article describes numerical simulation of gas pipeline network operation using high-accuracy computational fluid dynamics (CFD) simulators of the modes of gas mixture transmission through long, multi-line pipeline systems (CFD-simulator). The approach used in CFD-simulators for modeling gas mixture transmission through long, branched, multi-section pipelines is based on tailoring the full system of fluid dynamics equations to conditions of unsteady, non-isothermal processes of the gas mixture flow. Identification, in a CFD-simulator, of safe parameters for gas transmission through compressor stations amounts to finding the interior points of admissible sets described by systems of nonlinear algebraic equalities and inequalities. Such systems of equalities and inequalities comprise a formal statement of technological, design, operational and other constraints to which operation of the network equipment is subject. To illustrate the practicability of the method of numerical simulation of a gas transmission network, we compare computation results and gas flow parameters measured on-site at the gas transmission enter-prise.
文摘水库进行水力排沙时,高含沙水流过程可能会对鱼类等水生动物产生负面影响,其量化评估方法研究较为薄弱。为了预测和评估水库排沙过程对下游鱼类的影响,本文利用黄河花斑裸鲤和鲤鱼在高含沙水体中生存特性研究的实验数据,综合考虑含沙量和粒径、溶解氧、暴露时间、水温等因子对鱼类生存的影响,建立了基于IPSO-BP神经网络的高含沙水体对鱼类致死影响预测方法,对目标鱼类死亡率的预测误差小于6%。本文使用了与BP神经网络紧密耦合并引入动态参数和变异扰动的IPSO算法,较BP和PSO-BP神经网络预测能力更佳,相比国内外已有的Stress Index(SI)、Severity of Ill Effect(SEV)和多元拟合方法预测精度得到显著提升。分析表明,本文提出的预测方法能够考虑高含沙水体中鱼类生存受多环境因子联合制约,且多因子之间存在复杂关联的情况,可为评估高含沙水流过程对水生态的影响提供新的方法。
