ty -jour a2 -tombras，乔治S. au -sun，wei au -ye，minquan py -2015 da -2015/12/16 ti-基于小波变换的短期负载预测，最小二乘支持矢量机，由水果优化Fly Optimization Algorithm SP - 862185 VL - 2015 AB - Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM) which is optimized by fruit fly algorithm (FOA) for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system. SN - 2090-0147 UR - https://doi.org/10.1155/2015/862185 DO - 10.1155/2015/862185 JF - Journal of Electrical and Computer Engineering PB - Hindawi Publishing Corporation KW - ER -