| 1. | Short term load forecasting model and the influencing factors
短期负荷预测模型及其影响因素 |
| 2. | A support vector machine approach for short term load forecasting
基于模糊回归支持向量机的短期负荷预测 |
| 3. | Short term load forecasting using wavelet transform and svm based on similar - days
基于支持向量机混合模型的短期负荷预测方法 |
| 4. | Parameter optimization based on singularity in chaotic forecasting of short term load
用奇异性的短期负荷预测混沌方法优化参数 |
| 5. | Short term load forecasting based on fuzzy regression support vector machine
基于粗糙集属性约简算法和支持向量机的短期负荷预测 |
| 6. | Based on the short term load - forecast , this article uses genetic algorithm to calculate the optimal control schedule in a substation
本文在负荷预测的基础上将遗传算法应用于变电站电压无功控制。 |
| 7. | It is applied to short term load forecasting ; and the simulation results show that the proposed method can provide forecast precision as normal svm and supply more useful information
将其应用到电力系统短期负荷预测，仿真结果表明，所提方法不仅具有与支持向量机方法相同的预测精度，且提供了更多的有用信息。 |
| 8. | Short term load forecasting ( stlf ) is the precondition of economic and secure operation of power system , and because the power system are getting more and more marketable , stlf with high quality is getting more and more important and exigent
短期负荷预测是电力系统安全经济运行的前提，随着电力系统的市场化，高质量的短期负荷预测越来越显得重要和迫切。 |
| 9. | Based on the discussions of the conventional and recent methods of short term load forecasting such as time series , multiple regression approaches and artificial intelligence technologies , this paper presents a hybrid short term forecasting model which combines the artificial neural network ( ann ) and genetic algorithm ( ga ) . in order to improve the convergence speed and precision of the back - propagation ( bp ) , a new improved algorithm - the adapted learning algorithm based on quasi - newton method is given
本文首先分析比较了电力系统短期负荷预测的传统方法时间序列法和回归方法以及最近的专家系统和神经网络技术的优点和不足，然后针对人工神经网络bp算法的不足对其进行了改进，采用了基于拟牛顿的自适应算法，它提高了网络学习效率，具有较快的收敛速度和较高的精度。接着提出了改进的遗传算法来改善神经网络的局部收敛性。 |
| 10. | Applying the put forward model and the all - around classic genetic algorithm into the daqing medium - low level voltage distribution network to optimize the real power network , find classic project of reactive power equipment deploy . at the same time , analyze the ecnomic effect . the result shows that the put forward model and the all - around classic genetic algorithm has a lot of virtue , such as strong applicability , handy calculation , good ability of finding the best , easy spreading and applying into real power syatem short term load forecasting , and so on
5 )研究分析结果表明：论文提出的城市配电网无功优化补偿数学模型和全局最优遗传算法较全面、有效地解决了城市配电网无功优化补偿的问题，具有适用范围广、寻优能力强、计算简便、综合效益好等优点，为全局最优无功优化补偿提供了新的、科学的方法，易于在实际电网无功优化补偿中推广应用。 |
