This indicator inputs the previous 150 closing prices in a simple two-layer neural network, normalizes the network inputs using a sigmoid function, uses a feedforward calculation to send it to the second layer, shows the MSE loss curve and uses both automatic and manual backpropagation (user input) to find the most likely forecast values and uses the analog...
Neural Network Synthesis - Trend and Valuation
Introduction
The Neural Network Synthesis (𝓝𝓝𝒮𝔂𝓷𝓽𝓱) indicator is an innovative technical analysis tool which leverages neural network concepts to synthesize market trend and valuation insights.
This indicator uses a bespoke neural network model to process various technical indicator inputs, providing an improved...
Simple Neural Network Transformed RSI
Introduction
The Simple Neural Network Transformed RSI (ɴɴᴛ ʀsɪ) stands out as a formidable tool for traders who specialize in lower timeframe trading.
It is an innovative enhancement of the traditional RSI readings with simple neural network smoothing techniques.
This unique blend results in fairly accurate signals,...
Introduction
Esqvair's Neural Reversal Probability Indicator is the indicator that shows probability of reversal.
Warning: This script should only be used on 1 minute chart.
How to use
When a signal appears (by default it is a green bar), a reversal should be expected.
The signal appears when the indicator value >= Threshold.
If you want more signals, you must...
Library "WIPNNetwork"
this is a work in progress (WIP) and prone to have some errors, so use at your own risk...
let me know if you find any issues..
Method for a generalized Neural Network.
network(x) Generalized Neural Network Method.
Parameters:
x : TODO: add parameter x description here
Returns: TODO: add what function returns
Library "FunctionNNPerceptron"
Perceptron Function for Neural networks.
function(inputs, weights, bias, activation_function, alpha, scale) generalized perceptron node for Neural Networks.
Parameters:
inputs : float array, the inputs of the perceptron.
weights : float array, the weights for inputs.
bias : float, default=1.0, the default bias...
Library "MLActivationFunctions"
Activation functions for Neural networks.
binary_step(value) Basic threshold output classifier to activate/deactivate neuron.
Parameters:
value : float, value to process.
Returns: float
linear(value) Input is the same as output.
Parameters:
value : float, value to process.
Returns: float
sigmoid(value) ...
This study is based on several Price Action parameters of :-
• Candle Pattern,
• Supply Demands,
• Support and Resistance ,
• Breakouts,
• Trend Series Forecasting,
• Average true Range,
• Neural Smoothing With Alpha, Beta Calculations for Filtering wrong trend breakouts.
► How To Use This Study ?
• This Study is for positional trading.
• Buy Whenever a GREEN Up...
Hello, this script consists of training candlesticks with Artificial Neural Networks (ANN).
In addition to the first series, candlesticks' bodies and wicks were also introduced as training inputs.
The inputs are individually trained to find the relationship between the subsequent historical value of all candlestick values 1.(High,Low,Close,Open)
The outputs...
This is a test of neural network with one layer.
Two layers will follow soon.
Signals are given by CCI or RSI.
Method 1 triggers a change of oscillator (buy if >0)
Method 2 triggers oscillator over 0 (for CCI only)
How to use:
1- launch the strategy on a chart,
2- open "Strategy Tester" tab
3- open startegy option panel
4- modify x11, x12, x13 and x14 to get...
Hi, this is the MACD version of the ANN BTC Multi Timeframe Script.
The MACD Periods were approximated to the Golden Cross values.
MACD Lengths :
Signal Length = 25
Fast Length = 50
Slow Length = 200
Regards.
Hi all, this script was created as a result of ANN training in all time frames of bitcoin data.
Trained data is built on Chris Moody's Sling Shot system.
CM Sling Shot System :
This system automatically generates the ANN output for all time periods.
Therefore, it has multi-time-frame feature.
Artificial Neural Networks training details:
Average Errors...
Hello , this script is the ANN Forecast version of my "Dependent Variable Odd Generator " script.
I went to simplify a bit because the deep learning calculations are too much for this command.
The latest instruments included:
WTI : West Texas Intermediate (WTICOUSD , USOIL , CL1! ) Average error : 0.007593
BRENT : Brent Crude Oil ( BCOUSD , UKOIL , BB1! )...
NOTE: Experimental. Pinescript implementation of Decimal to Binary and Binary to Decimal that is intended for use in the development of a neural network proof of concept.
Intended for use in as subcomponent in the development of a more complex/highly experimental prototype.
Protection/logic for edge cases above 11111111/255 (8bits) is NOT implemented.
...
In this script, I tried to integrate ANN Forecast Algorithm on Stochastic Oscillator.
It took me quite a while, but i guess it worth.
After selecting the ticker, select the instrument from the menu and the system will automatically turn on the appropriate Forecast Stoch system.
The system is trained with ANN values of ANN MACD 25 in 1.
The Forecast algorithm is...
![META: Edge AI Forecast [Edge Terminal]](https://s3.tradingview.com/x/XTRf6YfF_mid.png "Edge AI Forecast [Edge Terminal]")
![BTCUSD: Neural Network Synthesis: Trend and Valuation [QuantraAI]](https://s3.tradingview.com/x/XZalCILB_mid.png "Neural Network Synthesis: Trend and Valuation [QuantraAI]")
![BTCUSD: Simple Neural Network Transformed RSI [QuantraAI]](https://s3.tradingview.com/6/6qTxRYB1_mid.png "Simple Neural Network Transformed RSI [QuantraAI]")
![XBTUSD.P: ANN Forecast Stochastic Oscillator [Noldo]](https://s3.tradingview.com/y/YYw2DY9i_mid.png "ANN Forecast Stochastic Oscillator [Noldo]")