Based on exact penalty function, a new neural network for solving the L1-norm optimization problem is proposed. In comparison with Kennedy and Chua’s network(1988), it has better properties.Based on Bandler’s fault ...Based on exact penalty function, a new neural network for solving the L1-norm optimization problem is proposed. In comparison with Kennedy and Chua’s network(1988), it has better properties.Based on Bandler’s fault location method(1982), a new nonlinearly constrained L1-norm problem is developed. It can be solved with less computing time through only one optimization processing. The proposed neural network can be used to solve the analog diagnosis L1 problem. The validity of the proposed neural networks and the fault location L1 method are illustrated by extensive computer simulations.展开更多
基金Supported by Doctoral Special Fund of State Education Commissionthe National Natural Science Foundation of China,Grant No.59477001 and No.59707002
文摘Based on exact penalty function, a new neural network for solving the L1-norm optimization problem is proposed. In comparison with Kennedy and Chua’s network(1988), it has better properties.Based on Bandler’s fault location method(1982), a new nonlinearly constrained L1-norm problem is developed. It can be solved with less computing time through only one optimization processing. The proposed neural network can be used to solve the analog diagnosis L1 problem. The validity of the proposed neural networks and the fault location L1 method are illustrated by extensive computer simulations.
文摘在分析影响集装箱的装载效率时,考虑场内拖车在码头堆场和岸边装卸桥之间的移动距离,将配载问题看成是以码头堆场B ay位上的集装箱为供给、船舶B ay上的空箱位为需求的运输问题,以场内拖车将码头堆场集装箱送到岸边装卸桥所运行的距离最短为目标,建立配载模型并应用Hop fie ld神经网络模型进行计算机模拟.模拟结果说明,所提出的优化模型可以减少场内拖车运行的距离,提高集装箱装载效率,为合理进行集装箱船配载提供了一个参考模型.
