Description: 利用线性神经网络对某一正弦信号进行线性预测。利用函数newlind设计线性神经网络，
在已知正弦信号过去5个值得情况下，预测其将来值。
定义需要的信号，共持续5s，采样频率40Hz-Using linear neural network to a sinusoidal signal for linear prediction. Newlind design using a linear function of neural networks, known sinusoidal signal in the past five worthy cases, forecast its future value. The definition of the needs of the signal, sustained a total of 5s, the sampling frequency of 40Hz Platform: |
Size: 1024 |
Author:舒 |
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Description: 本次实验通过ANFIS神经网络在用电预测中的应用, 对未来某交易时段内统负荷的预先估计。负荷预测是进行实时控制、制定运行计划和发展规划的基础，是电力市场决策支持软件的基本组成部分。-The experiment by the the ANFIS neural network in the electricity forecast, pre-estimate of future trading session system load. The load forecast is for real-time control, develop operational plans and development planning is a basic part of the electricity market decision support software. Platform: |
Size: 12288 |
Author:sunnic |
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Description: 分析了支持向量回归机在能源需求预测中的优势,确定了输入向量集合和输出向量集合,建立了基于Matlab技术的SVR能源需求预测模型.对我国1985-2008年能源需求相关数据进行模拟与仿真,并对中国2010年和2020年能源需求量进行预测.研究结果表明:一是中国未来对能源的需求量逐渐增加,从2010年的330400万吨标准煤上升到2020年418320万吨标准煤,年均增长率为2.39％；二是在解决我国能源系统小样本.非线性及高维模式识别问题中SVR比BP神经网络等方法有更高的预测精度.-Support vector regression analyzes advantage in energy demand forecast to determine the set of input vectors and output vector set, established SVR energy demand forecasting model based on Matlab technology. Energy demand for our 1985-2008 related data modeling and simulation , and China in 2010 and 2020 energy demand forecast results show that: First, China s increasing demand for energy in the future, from 3.304 billion tons of standard coal in 2010 rose to 4.1832 billion tons of standard coal in 2020, average annual growth rate of 2.39 second is to solve our energy system small sample nonlinear and high dimensional pattern recognition problem SVR higher prediction accuracy than the BP neural network method. Platform: |
Size: 4320256 |
Author:王斌 |
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Description: this code utilizes neural network to forecast a data set in future. data set is also attached to the folder Platform: |
Size: 6144 |
Author:shahab |
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Description: 根据过去近20年的交通事故数据，运用BP神经网络预测未来几年的交通事故数据。-On the basis of traffic accident data of rencent twenty years, to use artifical neural network to forecast the traffic accident data in the future. Platform: |
Size: 38912 |
Author:葛丽娜 |
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Description: 用风电功率历史数据来对未来一段时间功率的数值进行预测，通过Matlab软件编程和Excel处理数据，用神经网络仿真预测法、灰度预测法、时间序列预测法通过历史数据所呈现出来的一些规律对某段时间的风电功率展开预测，预测之后对得到的数据进行误差分析，通过与一些标准的对比来确定预测方法的可靠程度-Using historical data to forecast wind power to the value to the future time power, by Matlab software programming and Excel data processing, neural network simulation and prediction of wind power law method, gray prediction method, time sequence prediction method based on the historical data are presented for a period of time after the start prediction, prediction the data are error analysis, by comparing with the standard to determine the degree of reliability prediction method Platform: |
Size: 2048 |
Author:张学阳巨蟹 |
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Description: 通过神经网络来进行股票预测，实现对未来股市的上证大盘的预测。-Stock through neural network prediction, realizes the stocks of Shanghai stock market forecast for the future. Platform: |
Size: 3072 |
Author:陈谦 |
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Description: 8指标预测周线，主要对股票历史的8个指标，及即收盘价、开盘价、最高价、最低价等8个指标进行神经网络的学习，然后形成矩阵，对未来的走势进行预判断。-8 indicators forecast weekly, mainly on the stock history of 8 indicators, and the closing price, opening price, the highest price, the lowest price of 8 indicators of neural network learning, and then the formation of the matrix, the future trend of prejudgment. Platform: |
Size: 1024 |
Author:齐晓 |
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