Forecasting Model of Coal Requirement Quantity Based on Grey System Theory

The generally used methods of forecasting coal requirement quantity include the analogy method, the outside push method and the cause effect analysis method. However, the precision of forecasting results using these methods is lower. This paper uses the grey system theory, and sets up grey forecasting model GM (1, 3) to coal requirement quantity. The forecasting result for the Chinese coal requirement quantity coincides with the actual values, and this shows that the model is reliable. Finally, this model are used to forecast Chinese coal requirement quantity in the future ten years.

The Research and Application of the Multi-regression Technique in the Course of Enterprises＇ Marketing Decision-making

The reformation of the economy system has led the functional departments and status of the enterprises into the variance state. Under the condition of the market economy, the kernel of the enterprises＇ functional department has diverted to that of marketing decision-making, which faces to market and meets with the need of consumption. Assuredly, the kernel of marketing decision-making is to prognosticate the future market requirement quantity of the production of enterprises accurately, so that it can ensure and realize the maximum of the enterprises＇ profit to increase. Applying the proof to test demonstration analytical method of economics and adopting the multi-regression technique, this paper analyzes the enterprises＇ production requirement quantity decision-making of the GMC （Global Management Challenge） and changes a great many of uncontrollable factors to the controllable ones of the enterprises. So, it can make the forecast order form closer to the actual prices of the future market requirement quantity in the production marketing decision-making of the enterprises and realize the optimizing combination and the working object with the minimum of the cost and the maximum of the profit. And it can insure the realization of the profit increase of the enterorises mostly in the life-cvcle of the production.

Experimental study on f-ω regulation model under abnormal methane emission

In view of the difficulty of automatic adjustment, the recovery lag and the major accident potential of the mine ventilation system, an experimental model of the pipe net was established according to the typical one mine and one working face ventilation system of Daliuta coal mine. Using the best uniform approximation method of Chebyshev interpolation to fit the fan performance curve, we experimentally determined fan characteristics with different frequencies and establish the data base for the curves. Based on ventilation network monitoring theory, we designed a monitoring system for ventilation network parameter monitoring and fan operating frequency automatic control. Using the absolute methane emission quantity to predict the air quantity requirement of branch and fan frequency, we established a f-ω regulation model based on fan frequency and absolute methane emission quantity. After analysing methane emission and distribution characteristics, using CO_2 to simulate the methane emission characteristics from a working face, we verified the correctness and rationality of the f-ω regulation model. The fan operation frequency is adjusted by the method of air adjustment change with methane emission quantity and the curve searching method after determining air quantity requirements. The results show that the air quantity in a branch strictly changes according to the f-ω regulation model, in the airincreasing dilution by fan frequency regulation, the CO_2 concentration is limited to the set threshold value. The paper verifies the practicability of a frequency regulation system and the feasibility of the frequency adjustment scheme and provides guidance for the construction of automatic frequency conversion control system in coal mine ventilation networks.