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https://github.com/igopalakrishna/ann-for-regression


https://github.com/igopalakrishna/ann-for-regression

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# ANN-for-Regression

The objective is to create a data model that predicts the net hourly electrical energy output (EP) of the plant using available hourly average ambient variables.

This complex, real-world Deep Learning challenge that covers everything from data preprocessing to building and training an ANN, while utilizing the Machine Learning library, Tensorflow 2.0, and Google Colab, the free, browser-based notebook environment that runs completely in the cloud.

Steps:

Part 1: Data Preprocessing

Importing the dataset

Splitting the dataset into the training set and test set

Part 2: Building an ANN

Initializing the ANN

Adding the input layer and the first hidden layer

Adding the output layer

Compiling the ANN

Part 3: Training the ANN

Training the ANN model on the training set

Predicting the results of the test set

More about Combined-Cycle Power Plants

A combined-cycle power plant is an electrical power plant in which a Gas Turbine (GT) and a Steam Turbine (ST) are used in combination to produce more electrical energy from the same fuel than that would be possible from a single cycle power plant.

The gas turbine compresses air and mixes it with a fuel heated to a very high temperature. The hot air-fuel mixture moves through the blades, making them spin. The fast-spinning gas turbine drives a generator to generate electricity. The exhaust (waste) heat escaped through the exhaust stack of the gas turbine is utilized by a Heat Recovery Steam Generator (HSRG) system to produce steam that spins a steam turbine. This steam turbine drives a generator to produce additional electricity. CCCP is assumed to produce 50% more energy than a single power plant.