为了对网络参数进行优化，本文提出了一种一般单纯形算法，这种方法比单纯形法收敛速度要快。
In order to optimize the parameters of the network, we propose the General Simplex Method, which converges more quickly than the Simplex Method.
方法引入了金属铣削加工参数多目标优化模型，应用目标达到法对模型求解，又基于神经网络建立了金属铣削参数自动获取模型。
It introduces the multi-objected optimization model of the metal milling process parameters and applies the goal attainment method to ask for the explanation for the model.
研究了具有参数优化的核函数法及其在聚类问题中的应用。
It studies kernel function method with parameters optimized and its application in pattern clustering.
应用推荐