Electricity Price Forecasting using Optimized Neural Network
This MATLAB code is for electricity price forecasting based on tuned weights and biases of neural network. The video for demo can be checked in the description below.
The machine learning approaches provides better solution in terms effective forecasting. A commonaly used tool Neural network promises to be an effective forecasting tool in an environment with high degree of non-linearity and uncertainty. But due to premature convergence in machine learning approache it can give erroneous results some time. So it has to be trained to full convergence. A hybrid optimization algorithm i.e. Bacterial foraging optimization (BFO) and particle swarm optimization (PSO) is used in our work to train neural network so that erroneous results can be avoided.
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