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For Short term Load Forecasting using ANN,how to choose the number of hidden layer neurons?
Greg Heath has developed a two loop approach which has been relatively successful over the years. SINCE A SINGLE HIDDEN LAY...

7 years ago | 1

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Relation between input data points and hyper parameters that needs to be tuned
Each case is different. However, things tend to be relatively straightforward if you have at least as many training equations as...

7 years ago | 0

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DUH ... HOW DO I SEARCH/BROWSE THE TOPIC "NEURAL"?
OK … the search window has to be brought out from hiding by clicking on the magnifying glass! Greg

7 years ago | 0

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Question

DUH ... HOW DO I SEARCH/BROWSE THE TOPIC "NEURAL"?
I appear to be missing something Greg

7 years ago | 1 answer | 0

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Answered
Can Greg post an example for using neural network time series in the whole sense?
Q1a: Do I need to normalize/standardize the data before feeding to neural network? A1a: Typically, Yes. One of the follow...

7 years ago | 1

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Relation between input data points and hyper parameters that needs to be tuned
[ I N] = size(input) [ O N ] = size(target) % (MATLAB DEFAULT) Ntst = round(0.15*N) Nval = Ntst Ntrn ...

7 years ago | 0

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Answered
How to retrain existing and trained Neural Network without destroying trained content?
TRAIN initializes weights ONLY IF ALL weights are zero. OTHERWISE TRAIN will update weights with the new data. Therefor...

7 years ago | 4

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Can Greg post an example for using neural network time series in the whole sense?
Can Greg post an example for using neural network time series in the whole sense? Yes he can … and in fact, he has! If the ex...

7 years ago | 1

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Answered
Future Prediction Narx-Net vs Nar-net
> My doubt is that i can use a NAR-NET with only Y(t) and try to forecast the future prices and find a future trend with some ac...

7 years ago | 1

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Answered
How to retrain existing and trained Neural Network without destroying trained content?
In order to preserve the dominant characteristics of the 1st dataset you must include that information while adapting to the new...

7 years ago | 1

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Function change in NARX NN for time series prediction
>Hello, I am doing a NARX prediction model by the tool in matlab. I normalized my inputs and targets by standard deviation 1 and...

7 years ago | 0

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Answered
Script for neural nertwork
The "N"umber of individual "I"-dimensional "I"nputs and corresponding "O"-dimensional "O"utput "t"argets are given by x = ...

7 years ago | 0

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why the prediction of neural network is wrong?
1.There is nothing in your design to prevent negative outputs. 2. Therefore the question is What are the ranks of the ABS...

7 years ago | 0

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What is the difference among using fitnet(), configure() or just using narxnet()?
> I am trying to optimize and characterize a NARX network with 2 inputs and 2 outputs based on the number of neurons, delays, an...

7 years ago | 0

Question

Neural Network Search Strategy Confusion
I am trying to categorize my ANSWERS posts on the neural network CLOSELOOP operation. The reason is that NO ONE has demonstrated...

7 years ago | 1 answer | 0

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What is the difference among using fitnet(), configure() or just using narxnet()?
>> I am trying to optimize and characterize a NARX network with 2 inputs and 2 outputs based on the number of neurons, delays, a...

7 years ago | 0

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ANN training using two time series as input
You have a mischaracterization of the standard classification and timeseries models. 1. Classification input data is divided ...

7 years ago | 0

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Can I train the SAME neural network with multiple datasets using Neural Fitting Tool?
In order to not forget a learned dataset while learning a new one: Continue training with a mixture (NOT a concatenation!) o...

7 years ago | 0

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preparets error for using in narxnet
Come on ... Error using preparets (line 105) Feedback and inputs have different numbers of timesteps So why don't you EXPL...

7 years ago | 0

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How to implement fitnet.m in MATLAB R2007?
There may be licensing problems. Otherwise just use NEWFF. It's old but it is pretty good. Greg

7 years ago | 0

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Answered
How to train too large data set using neural network
Insufficient explanation. Need details, [ I N ] = size(input) % [ ? 2721 ] [ O n ] = size(target) % [ ? 2721 ] If you ...

7 years ago | 0

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How do you fit a Neural net with weight decay using the train function?
Well, have you tried it ? See help trainbr and doc trainbr *Thank you for formally accepting my answer* Greg...

7 years ago | 0

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How can I assess the reliability of my machine learning model on unseen data?
THE ABOVE IS INCORRECT FOR NEURAL NETWORKS. FOR NNs: DESIGN = TRAIN + VALIDATE 1. Collect data. 2. a. Split t...

7 years ago | 0

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Why does the "trainbr" function not require a validation dataset?
OVERFITTING + OVERTRAINING combine to form an ugly monster that prevents nets from performing well on nontraining data. Training...

7 years ago | 3

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How to calculate the MSE for multi-output neural network?
It is better to combine scalars into vectors and matrices when they have the same numerical scale. My ideal is to STANDARDIZE in...

7 years ago | 1

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Inputs and number of neuron
I use the concept Number of training equations Ntrneq >> Number of unknown weights Nw For a single layer I-H-O net with...

7 years ago | 0

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dealing imbalanced data in neural network
There many ways to deal with unbalanced classes when there is no more real data available. Over the decades I have used the foll...

7 years ago | 1

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Shape recognition by neural network
1.You have erroneouslyy defined PO and PT with P1 2. I think the argument in reshape should be (Pm,23,40000) 3. You have 2 hi...

7 years ago | 0

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Answered
Fit an equation with trained neural network
The single hidden layer feedforward net is a UNIVERSAL APPROXIMATOR! In the default mode it's equation is y = B...

7 years ago | 0

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