Combined forecasting is a well-known forecasting technique of handling multiple forecasting methods. However, the previous combined forecasting approaches lack of inco orating the various possible opinions from several experts on an given forecasting problem. This paper proposes an MC2 linear programming approach to determining weighted coefficients of combined forecasting that involves multiple experts. The numerical example of the paper shows that the proposed appreach likely outperforms the current techniques of combined forecasting in dealing with the case of multiple experts.

This paper proposes a convergence theory of the ordinary differential equations ODE. method for finding the local optima of general constrained optimization. We prove that solutions starting from the neighbourhood of a critical point of the differential equations in this paper about part variables always converge to the feasible point of the problem. We also study the initial relationship between neural computation in optimization NCO. and ODE methods. Some detailed connections of the two methods in solving the linear and quadratic programming on Rqn are shown in this paper.

本文对变权组合预测（VWCF）的权函数进行研究，得到变权组合预测问题误差平方和J的表达形式；同时在选择逼近系数向量{Eik}———正交的条件下，推出权函数逼近系数之间的依赖关系，以及极小误差平方和J*落入的区间，最后给出的算例表明方法的有效性。