**3. Artificial neural networks (ANNs) and their constituent parts**

Data inputs, weights, biases, activation functions, and outputs make up ANNs [4, 13, 21].


*Artificial Intelligence Approaches for Studying the* pp *Interactions at High Energy… DOI: http://dx.doi.org/10.5772/intechopen.111552*

4.The weighted average of the inputs and the bias used make up the activation functions. They make the decision on whether or not the data will move on to the network's next layer.

Artificial neurons are present in every layer of a NN and transmit data through them. There is bias in these neurons. Weighted channels are used to convey inputted data via the layers. The weighted value of the data is added to the bias and used within the activation mechanism when it reaches the neurons. The neuron may or may not be triggered according to the outcome of the function. If the neuron is active, the information will be transmitted to the following layer. The data will not move on to the next layer, though, if it's not active. Until an output is created, this process will be repeated across the layers. Decisions produced by the deep learning software are the outputs. DL system does not require human involvement to learn from their mistakes because of the various layers in the neural network. It represents a meager step toward creating an artificial general intelligence system that is capable of autonomous decision-making.
