基于模糊SOFM网分类的船舶电力负荷估算模型

提出了一种新的船舶电力负荷分类随机估算模型。将负荷的功率和工作概率作为分类的两项指标，利用模糊自组织特征映射（SOFM）网络对负荷进行分类，并基于分类给出了电力负荷的随机估算模型。由于分类保证了同一类中的负荷，其功率和工作概率均较接近，从而减小了因分类而导致的模型误差。给出了一个实例，其结果表明：模型精度高，计算简单，易于实现。

Estimation Model for Loads of Ship Power System based on Fuzzy SOFM Network

A classification based new stochastic estimation model for loads of ship power system is proposed in this paper. Firstly, regarding the power and the working probability as two classification attributes, the loads are classified by using fuzzy self organizing feature map (SOFM) network. Then, based on the classification, the load stochastic estimation model is presented. The classification can guarantee both the powers and working probabilities of all the loads in the same class are very close, which reduces the model error resulting from classification. Finally, a practical example is given. The result shows that the proposed model is highly accurate and easy to compute and implement.