电力科学与工程
電力科學與工程
전력과학여공정
INFORMATION ON ELECTRIC POWER
2015年
8期
1-7
,共7页
神经网络%遗传算法%潮位预测%潮汐发电
神經網絡%遺傳算法%潮位預測%潮汐髮電
신경망락%유전산법%조위예측%조석발전
neural network%genetic algorithm%tidal forecasting%tidal power generation
潮位预测对于潮汐电站日常运行、优化调度有着非常重要的作用。针对潮位受非周期性因素影响而具有非平稳性特点以及传统人工神经网络对潮位预测存在训练速度慢、收敛精度低、易陷入局部最优等缺陷，提出了一种改进实用的遗传神经网络潮位预测算法，首先通过潮位数据的异常值检测，采用均值替换法克服由观测记录产生的数据误差；然后通过神经网络拓扑结构合理设计、节点优选、遗传算法优化网络权值与阈值等措施，建立了潮位预测模型。通过实际港口潮位预测应用验证了算法的有效性。
潮位預測對于潮汐電站日常運行、優化調度有著非常重要的作用。針對潮位受非週期性因素影響而具有非平穩性特點以及傳統人工神經網絡對潮位預測存在訓練速度慢、收斂精度低、易陷入跼部最優等缺陷，提齣瞭一種改進實用的遺傳神經網絡潮位預測算法，首先通過潮位數據的異常值檢測，採用均值替換法剋服由觀測記錄產生的數據誤差；然後通過神經網絡拓撲結構閤理設計、節點優選、遺傳算法優化網絡權值與閾值等措施，建立瞭潮位預測模型。通過實際港口潮位預測應用驗證瞭算法的有效性。
조위예측대우조석전참일상운행、우화조도유착비상중요적작용。침대조위수비주기성인소영향이구유비평은성특점이급전통인공신경망락대조위예측존재훈련속도만、수렴정도저、역함입국부최우등결함，제출료일충개진실용적유전신경망락조위예측산법，수선통과조위수거적이상치검측，채용균치체환법극복유관측기록산생적수거오차；연후통과신경망락탁복결구합리설계、절점우선、유전산법우화망락권치여역치등조시，건립료조위예측모형。통과실제항구조위예측응용험증료산법적유효성。
For tidal power station , the tidal forecasting plays an important role in the daily operation and optimal scheduling .The paper proposes an improved genetic neural network prediction algorithm to forecast tidal level to tackle the non-stationary characteristics of tides caused by non-cyclical factors and the defects in traditional artificial neural network:such as slow training , low precision and proneness to local optimum .First, the abnormal value in tidal data was detected and the mean substitution method was adopted to overcome data error generated by the ob -servation records .The tidal forecasting model was built after the reasonable design of neural network topology , op-timal node selection , and setting of weights and thresholds to optimize network in genetic algorithms .The applica-tion of the algorithm to actual port tide forecasting demonstrated its effectiveness .
