Measurement Of The Artificial Neural Network And The Calorific Value Of Coal

Artificial neural network is a information system that is established by theoretically abstracting, simplifying and simulating the structure, function and some fundamental properties of human brain neural networks. A neural network derives its computing power through, first, its massively parallel distributed structure and, second, its ability to learn and therefore generalize.The coal quality analysis apparatus measures the count value of ash, water, density and temperature of coal sample with the y-ray sensor, capacitance sensor, pressure sensor and temperature sensor respectively, and inputs the four count values to the computer by pc-7606 data collection chip. The goal of this paper is establish the model of calorific value of coal and the count values to forecast the value quickly and exactly.To achieve this goal, this paper design a neural network with three layers in which the first layer play a classifier role and learn with the memory-based learning algorithm while the second and third layers learn with the error back-propagation algorithm. Finally, this paper generalize the model and testify that the model is rational.