Data fitting with neural network
Data fitting is the process of building a curve or a mathematical function that has the best match with a set of previously collected points. The curve fitting can relate to both interpolations, where exact data points are required, and smoothing, where a flat function is built that approximates the data. The approximate curves obtained from the data fitting can be used to help display data, to predict the values of a function where no data is available, and to summarize the relationship between two or more variables. In the following figure is shown a linear interpolation of collected data:
Data fitting is the process of training a neural network on a set of inputs in order to produce an associated set of target outputs. Once the neural network has fit the data, it forms a generalization of the input-output relationship and can be used to generate outputs for inputs it was not trained on.
The fuel consumption of vehicles has always been studied by the major...
