Description: 用Matlab人工神经网络工具箱预测公交客流量，数据可以输入成文本形式，改变数据和精度即可使用。-Using Matlab neural network toolbox prediction bus traffic, data can enter into text form and change the data and the accuracy can be used. Platform: |
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Author:jsd |
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Description: 利用灰色系统进行预测的几篇好论文:
BP神经网络_灰色系统联合模型预测软基沉降量 非线性时间序列神经网络预测方法的研究及应用 股票投资价值灰色马尔可夫预测 股票投资价值灰色系统模型及应用 灰色关联神经网络模型在股指预测中的应用 灰色理论与模型及在车辆拥有量预测中的应用 灰色神经网络交通事故预测比较 灰色神经网络预测模型的应用 灰色-神经网络综合预测模型-Gray prediction system using a few good papers: BP neural network system _ a joint model gray soft ground settlement prediction of nonlinear time series prediction method of neural network research and application of the gray value of equity investments Markov prediction value of the equity investments of the gray system Application of gray relational model and neural network model in forecasting stock gray theory and model and prediction of vehicle ownership in the application of gray neural network traffic prediction compare gray neural network prediction model of the application of gray- the integrated neural network prediction model Platform: |
Size: 883712 |
Author:yujian |
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Description: 用matlab实现神经网络的城市交通流量预测。主要以大脑生理变化过程为基础、模仿大脑的结构和功能-Neural network using matlab implementation of the urban traffic flow prediction. Major physiological changes to brain-based process, to imitate the structure and function of the brain Platform: |
Size: 17408 |
Author:陈猪猪 |
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Description: 城市交通流的运行存在着高度的复杂性、时变性和随机性,实时准确的交通流预测是智能交通系统,特别是先进的交通管理系统与先进的出行者信息系统研究的关键. 基于交通流预测的特点,给出了基于遗传算法的小波神经
网络的交通预测模型GA-WNN ,用具有自然进化规律的遗传算法来对小波神经网络的连接权值和伸缩平移尺度进行前期优化训练,部分代替了小波框架神经网络中按单一梯度方向进行参数优化的梯度下降法,克服了单一梯度下降法易陷入局部极小和引起振荡效应等缺陷. 仿真实验验证了GA-WNN 预测模型对短时交通流的预测的有效性.-For the high complexity ,time-variation and probability of urban traffic flow , its real-time and exact
prediction is critical to the research of intelligent traffic systems , especially for the advanced traffic manage-ment system and advanced traveler information system. Based on the character of the traffic flow prediction , a
GA-WNN model is given based on the wavelet neural network with genetic algorithm. The genetic algorithm of
natural evolving law for the gradient descendent algorithm in Wavelet Neural Network is partly substituted to
pre-optimize the connection weight and the extension scale of the wavelet neural network and later optimize the
parameters along a single gradient vector. This method overcomes some drawbacks when there exists a single
gradient descendent algorithm , such as local minimum and oscillation. A short-time traffic flow prediction sim-
ulation using the GA2WNN prediction model demonstrates the validity of the model . Platform: |
Size: 615424 |
Author:mengfei |
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