Description: This book is about the use of artificial neural networks for supervised learning problems. Many such problems occur in practical applications of artificial neural networks. For example, a neural network might be used as a component of a face recognition system for a security appli-
cation. After seeing a number of images of legitimate users' faces, the network needs to determine accurately whether a new image corresponds to the face of a legitimate user or an imposter. In other applications, such as the prediction of future price of shares on the stock exchange, we may require a neural network to model the relationship between a pattern and a real-valued quantity. Platform: |
Size: 20091030 |
Author:kj5566 |
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Description: 程序名：ga_bp_predict.cpp
描述： 采用GA优化的BP神经网络程序，用于单因素时间
序列的预测,采用了单步与多步相结合预测
说明： 采用GA(浮点编码)优化NN的初始权值W[j][i],V[k][j]，然后再采用BP算法
优化权值-Program name: ga_bp_predict.cpp Description: The GA-optimized BP neural network procedure for single-factor time series prediction using the single-step and multi-step prediction combining Description: using GA (floating point coding) to optimize the initial NN weights W [j] [i], V [k] [j], then BP algorithm to optimize the use of weights Platform: |
Size: 6144 |
Author:fk774 |
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Description: bp人工神经网络算法实现，用java编写程序代码，应用案例是港口吞吐量预测-bp artificial neural network algorithm, using java programming code, the application case is the throughput of the port prediction Platform: |
Size: 24576 |
Author:林林 |
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Description: 可用于bp,elman,rbf,grnn四种神经网络的预测命令-Can be used for bp, elman, rbf, grnn four types of neural network prediction order Platform: |
Size: 2048 |
Author:liu |
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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: Elman递归神经网络对时间序列的预测代码，做的效果还行，仅供参考-Elman recurrent neural network for time series prediction code, do the results were OK for reference purposes only Platform: |
Size: 30720 |
Author:chenshengli |
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Description: Neural Network Based Clustering
using Self Organizing Map (SOM) in Excel
Here is a small tool in Excel using which you can find clusters in your data set. The tool uses Self Organizing Maps (SOM) - originally proposed by T.Kohonen as the method for clustering.
* Neural Network based Clustering tool in Excel (209 KB in Zipped format. 947 KB when unzipped.)
Inside the downloaded zip file, you will find the Excel file containing the application. Before running it, I suggest that you go through the ReadMe worksheet. It contains brief instructions on how to run the tool.
If you are interested in building Prediction and Classification models in Excel using Feedforward-Backpropagation Neural Network, here are two small Excel based tools for you. Also, if you are interested in Tree based Classification models, here is a Tree based classifier in Excel.
-Neural Network Based Clustering
using Self Organizing Map (SOM) in Excel
Here is a small tool in Excel using which you can find clusters in your data set. The tool uses Self Organizing Maps (SOM)- originally proposed by T.Kohonen as the method for clustering.
* Neural Network based Clustering tool in Excel (209 KB in Zipped format. 947 KB when unzipped.)
Inside the downloaded zip file, you will find the Excel file containing the application. Before running it, I suggest that you go through the ReadMe worksheet. It contains brief instructions on how to run the tool.
If you are interested in building Prediction and Classification models in Excel using Feedforward-Backpropagation Neural Network, here are two small Excel based tools for you. Also, if you are interested in Tree based Classification models, here is a Tree based classifier in Excel.
Platform: |
Size: 214016 |
Author:Jessie |
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Description: Neural Network OCR.
There are many different approaches to optical character recognition problem. One of the most common and popular approaches is based on neural networks, which can be applied to different tasks, such as pattern recognition, time series prediction, function approximation, clustering, etc.
In this article, I ll try to review some approaches for optical character recognition using artificial neural networks. The attached project is aimed as a research project, so don t try to find here a ready solution for scanned document processing.
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Size: 367616 |
Author:reyjav |
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Description: Multi-step-prediction of chaotic time series based
on co-evolutionary recurrent neural network
协同进化递归神经网络的多步混沌时间序列预测-This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic
time series, it estimates the proper parameters of phase space reconstruction and optimizes the structure of recurrent
neural networks by co-evolutionary strategy. The searching space was separated into two subspaces and the individuals
are trained in a parallel computational procedure. It can dynamically combine the embedding method with the capability
of recurrent neural network to incorporate past experience due to internal recurrence. The eff ectiveness of CERNN is
evaluated by using three benchmark chaotic time series data sets: the Lorenz series, Mackey–Glass series and real-world
sun spot series. The simulation results show that CERNN improves the performances of multi-step-prediction of chaotic
time series. Platform: |
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Author: |
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Description: 运用神经网络pso的算法进行极值的搜索，并且以函数例子进行了演示。-Use grnn neural network algorithms for data prediction, and the cargo as an example for a demonstration. Platform: |
Size: 2048 |
Author:xcxc |
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Description: 神经网络的数据预测—电力负荷预测模型研究,带有数据，调 试过，可以运行，希望对大家有帮助-Neural network data prediction- the power load forecasting model with data, debugging, you can run, and I hope for all of us to help Platform: |
Size: 2048 |
Author:张力 |
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Search - neural network for prediction