Because of the existence of the indefinite factors in power load forecasting, a new load forecasting model — the fuzzy inference forecasting is presented.

This paper,via the discussion of how to obtain prediction and inference development by such means as making use of learnt knowledge,attempts to help the students improve their listening comprehension with the help of necessary strategies.

Based on BP neural network algorithm,utilizing the experimental data of concrete under sulfate corrosion as the training samples,the models are proposed for inside and outside predicting the corrosion depth of concrete,which consider the influence factors of the concentration of sulfate radical in solution,the tensile and compressive stress levels of concrete and the corrosion time.

According to the example,the paper infers and forecasts systemically,and calculates the number for in formation entropy,then compare with maximum of Shannon to make sure the main reason which lead to "bad phenomenon" in engineering management in formation entropy.