本文将BP网络模型与灰色系统预测方法相结合，建立了公交客流量预测模型。
This article establish a forecast model of passenger volume in the public transportation by combine with gray system estimate and the BP networks model.
与传统的公交客流量预测方法相比，本模型预测结果具有更高的精度。
With traditional forecast method compare, the accuracy of this model forecast result is higher.
实际的城市交通流量预测研究表明，该模型具有较高的预测精度，可以为城市交通规划和控制提供准确的参考。
Practical prediction research of urban traffic flow shows that this model has famous predicted precision, and it can provide exact reference for urban traffic programming and control.
本文基于均相模型，运用非线性分岔理论，计算预测了两相自然循环系统静态分岔(流量漂移)解图。
Based on homogeneous model and with the application of nonlinear bifurcation theory, this paper presents prediction of static bifurcation (flow excursion) diagram of two-phase natural circulation.
提出一种新的贝叶斯组合神经网络模型并将其应用于短期交通流量的预测。
Method named BAYESIAN combined neural network model is proposed for short term traffic flow prediction in this paper.
实验结果表明，该模型对网络流量的短期预测是有效可行的，并具有良好的收敛性和稳定性。
The experimental results prove that the model is efficient in network traffic prediction with good astringency and stability.
根据其时间序列，建立线性神经网络模型，并将其用于地下水流量的动态预测。
Based on the time series, a model of linear artificial neural network is set and used for dynamic prediction of discharge of groundwater.
结合小波变换和人工神经网络的优势，建立一种网络流量预测的小波神经网络模型。
Integrating the merit of wavelet transform with that of artificial neural network, a wavelet neural network (WNN) model for forecasting network traffic was created.
关联方法可替代复杂的数学模型，用以预测绝热毛细管的壅塞流量特性。
Instead of the complicated mathematical model, the correlation method could be used to predict the choked flow rate through adiabatic capillary tube.
基于四阶段法，采用双重力模型，预测全国空域的交通流量OD分布。
The four stage method and a double gravity model were used to forecast the OD(origin-destination) distribution of air traffic flow in the whole airspace of China.
凭借采集的济南市经十路上各交叉路口的车流量数据，建立了可行的预测模型。
By means of recorded vehicle flow data of each crossing of Jingshi Road in Jinan, prediction models are feasibly constructed.
本文以大柳塔井田双沟泉域为例，应用该模型分别对双沟泉域在天然条件和矿井疏水条件下的泉流量进行预测，并据此评价矿井疏水对泉流量的影响。
Takeing Shuanggou Spring Area in Daliuta Coal Field as example, spring flow rate has been predicted by using this model under both natural and dewatering conditions.
好的流量模型必须能够准确描述网络实际流量的特征情况，这样才能准确预测流量状况。
A good traffic model must be able to describe network traffic characteristics and predict the practical traffic condition accurately.
叙述了系统的主要模型：空域流量预测模块，空域状态识别模块和冲突解决方案产生模块的实现过程。
The three major modules are explained including airspace flow prediction, airspace status identification and conflict solution, which uses the technique of neural network to realize.
介绍了灰色预测模型以及灰色预测模型在物流量预测中的应用。
The gray forecasting model and its application to predict logistics scale are introduced in this paper .
结果表明，该模型能够较准确地预测交通流量时间序列和低维混沌时间序列。
Experimental results show that the proposed Volterra adaptive prediction model is capable of effectively predicting traffic flow time sequence and low-dimensional chaotic time sequence.
根据降水量与地下水流量之间的相关关系，建立线性神经网络模型，并且将其用于地下水流量的动态预测。
According to the relationship between precipitation and discharge of groundwater, a model of linear artificial neural network is set and used for dynamic prediction of discharge of groundwater.
其中LCBP模型在考虑了经济收入水平、人口、年龄结构层次及流动人口流量等环境因子的条件下对趋势分量进行预测。
LCBP model predicts the weight of trend on terms that have considered such environmental factors as the economic income level, population, age composition level and flow of floating population, etc.
传统的交通需求4阶段分析模型大多基于各类出行的起讫点调查(OD调查)，建立出行生成、出行分布、出行方式选择和流量分配的4阶段预测模式。
The traditional travel demand model usually bases itself on the od study survey and employs a 4-step modeling process including trip generation, trip distribution, mode choice and assignment.
通过水文干旱识别和枯水期径流量预估，建立了供水系统水文干旱的预测模型。
Based on the recognition of hydrological drought and the runoff forecasting during the drought period, a forecasting model of hydrological drought is established.
本文采用改进型BP神经网络建立起交通流的时间序列模型，该模型可用于短期内道路交通流量的预测。
In this paper, the time - sequence model of traffic flow is based on the improved BP neural network, and this model can be used for short time prediction of traffic flow.
基于此，本文提出了基于集成神经网络的城市道路交通流量的融合预测模型。
Accordingly, this paper proposes a fusion-prediction model of traffic-flow in urban road-intersection based on integrated ANN (Artificial Neural Network).
提出基于产业关联度的城际轨道交通客流预测方法，并以沪杭城际轨道交通客流量预测为例，验证模型的合理性。
Industrial correlativeness degree was proposed based on the inter-city rail transit volume forecast method, with the case of Huhang intercity rail transit, it verifies the model's rationality.
利用改进的神经元网络构建了泵站流量以及效率预测模型，并利用改进的遗传算法构建了泵站优化模型。
A predictive model of flow rate for pumping stations based on the neuron network theory and an optimal operation model of pumping stations based on the hereditary algorithm were proposed.
网络流量预测传统方法是利用流量的统计特性建立数学模型。
The traditional methods of network traffic prediction are to build mathematical models using its statistical characteristics.
针对通用无线分组业务(GPRS)小区流量预测问题，对几种典型时序预测模型的性能进行了综合分析。
The performances of some classic time series prediction models were analyzed together concerning the traffic prediction of General Packets Radio Service (GPRS) cells.
针对通用无线分组业务(GPRS)小区流量预测问题，对几种典型时序预测模型的性能进行了综合分析。
The performances of some classic time series prediction models were analyzed together concerning the traffic prediction of General Packets Radio Service (GPRS) cells.
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