针对电力负荷的特点,综合考虑了温度及日期类型等因素对日最大负荷的影响,提出了一种采用模糊神经网络进行短期负荷预测的方法,并详细介绍了该方法的实现过程。通过对EUNITE(the European Network of Excellence on Intelligent Technologies for Smart Adaptive Systems)网络提供的实际数据进行详细分析确定了影响日最大负荷的相关因素,进而选择了合适的模糊输入以建立相应的模糊神经网络预测模型,并取得了较为理想的预测结果。算例分析结果充分证明了模糊神经网络在短期电力负荷预测方面具有较好的应用前景。
In this paper, we shall define a new concept, P map. Therefore the question which arises in will be answered satisfactorily, i.e. a frame map f: K→L from a T 2 frame K to a T 2 frame L can be uniquely extended to a frame map τf:τK→τL if and only if f is a P map.
In this paper we shall offer a separation axiom for frames inspired by the Hausdorff separation axiom for topological spaces. We call it separated condition. This is a condition on topology OX equivalent to the T O space X being Hausdorff. The class of separated frames includes that of strong Hausdorff frames and that of S frames. We shall show that the class of separated frames is a class closed under the formation of coproducts and subspaces, and the space Fil( L ) is Hausdorff for any separated frame L . Therefore there is a contravariant adjunction between the category TOP 2 of Hausdorff topological spaces and the category FRAM 2 of separated frames.
