摘要
基于牛顿前向插值公式提出一种对任意阶多维函数可实现高精度逼近的新型联想记忆系统——NFI-AMS,详细讨论了其基本原理、插值算法及训练规则。利用NFI-AMS良好的非线性逼近能力建立了油田注水机组节能优化模型,实现机组节能优化。仿真结果表明基于NFI-AMS的节能优化策略具有较好的优化效果。
This paper proposes a novel high-order associative memory system based on the Newton's forward interpolation,which is capable of implementing error-free approximations to multi-variable polynomial functions of arbitrary order.The factor which influences energy saving of water-driving motor in oil field is complicated,so it is difficult to use precise mathematics model to describe the model of water-driving motor quantitatively.Energy saving optimization model of water-driving motor is proposed based on NFI-AMS,which is employed to optimize the water-driving motor.The simulation results show that the proposed method is effective and accurate enough.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第17期238-240,共3页
Computer Engineering and Applications
关键词
牛顿前向插值
联想记忆系统
注水机组
优化
Newton' s forward interpolation
associative memory system
water-driving motor
optimization