An algorithm of Data Mining based on fuzzy neural net is proposed in the article. The algorithm creates a new fuzzy neural net, in which Gaussian-Function is used to calculate five fuzzy memberships in fuzzy layer. The average and variance required by Gaussian-Function can be calculated in advance through the data to be collected. Using of fuzzy inference from a Max-min operation to replace commonly multiply-add operation accelerates the speed of the network. In training stage, first the centre-of-gravity method is used to resist the fuzzy of the output of the fuzzy layer, and then BP idea is adopted to calculate the error and adjust the membership function parameters. To improve the accuracy and speed of fuzzy neural network, the net, using appropriate rules, crops redundant nodes and weights to extract and simplify the rules. A simulation is performed by using the control data from the intelligent temperature control system in industrial forging, the result shows that the algorithm has higher precision and stronger robustness.