This neural network consist of input neurons, hidden neurons, and output neurons. Hidden neurons are obtained by multiplying the inputs by the weights and taking the sum of each multiplication. Genetic Algorithms are used to search large data spaces. The three key terms that I will review are Genes , the Fitness Function , and Crossovers . A gene is a single bit of information.
Several genes make up an individual which is a certain location in a search space.
We use the fitness function to evaluate the quality of individuals and retain those individuals with higher probability of presenting a solution. Chapter twelve discusses the modification of two neural network structural elements. Knowing how to calculate the size of hidden neuron, you can come closer to the actual size according to the training data. It is necessary in some application to reduce the number of neurons and connection weights. This will optimize the runtime performance of a neural network for that application.