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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...

quasi 8 anni fa | 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...

quasi 8 anni fa | 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

quasi 8 anni fa | 0

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Domanda

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

quasi 8 anni fa | 1 risposta | 0

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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...

quasi 8 anni fa | 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 ...

quasi 8 anni fa | 0

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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...

quasi 8 anni fa | 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...

quasi 8 anni fa | 1

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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...

quasi 8 anni fa | 1

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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...

quasi 8 anni fa | 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...

quasi 8 anni fa | 0

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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 = ...

quasi 8 anni fa | 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...

quasi 8 anni fa | 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...

quasi 8 anni fa | 0

Domanda

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...

quasi 8 anni fa | 1 risposta | 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...

quasi 8 anni fa | 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 ...

quasi 8 anni fa | 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...

quasi 8 anni fa | 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...

quasi 8 anni fa | 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

quasi 8 anni fa | 0

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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 ...

quasi 8 anni fa | 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...

quasi 8 anni fa | 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...

quasi 8 anni fa | 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...

quasi 8 anni fa | 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...

circa 8 anni fa | 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...

circa 8 anni fa | 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...

circa 8 anni fa | 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...

circa 8 anni fa | 0

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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...

circa 8 anni fa | 0

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