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題名:類神經網路應用於太陽能光電系統發電量預測研究
書刊名:弘光學報
作者:温修培盧信忠
作者(外文):Wen, Xiu-peiLu, Hsin-chung
出版日期:2021
卷期:87
頁次:頁17-31
主題關鍵詞:多重線性回歸類神經網路多重認知器太陽能Multiple linear regressionArtificial neural networksMultilayer perceptronSolar photovoltaic power
原始連結:連回原系統網址new window
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  • 被引用次數被引用次數:期刊(0) 博士論文(0) 專書(0) 專書論文(0)
  • 排除自我引用排除自我引用:0
  • 共同引用共同引用:0
  • 點閱點閱:4
期刊論文
1.Dibike, Y. B.、Solomatine, D.(2001)。River flow forecasting using artificial neural networks。EGS journal of Physics and Chemistry of the Earth,26,1-7。  new window
2.Kolehmainen, M.、Martikainen, H.、Ruuskanen, J.(2001)。Neural Networks and Periodic Components Used in Air Quality Forecasting。Atmospheric Environment,35,815-825。  new window
3.Yousif, J. H.、Kazem, H. A.、Boland, J.(2017)。Predictive models for photovoltaic electricity production in hot weather conditions。Energy,10,971-889。  new window
4.Gardner, M. W.、Dorling, S. R.(2000)。Meteorological adjusted trends in UK daily maximum surface ozone concentrations。Atmospheric Environment,34,171-176。  new window
5.Viotti, P.、Liuti, G.、Genova, P. D.(2002)。Atmospheric urban pollution: applications of an artificial neural network (ANN) to the city of Perugia。Ecological Modelling,48,27-46。  new window
6.Kukkonen, J.、Partanen, L.、Karppinnen, A.、Ruuskanen, J.、Junninen, H.、Kolehmainen, M.、Niska, H.、Dorling, S.、Chatterton, T.、Foxall, R.、Cawley, G.(2003)。Extensive evaluation of neural network models for the prediction of N02 and PMI0 concentrations, compared with a deterministic modelling system and measurements in central Helsinki。Atmospheric Environment,37,4539-4550。  new window
7.Wang, W.、Lu, W.、Wang, X.、Leung, A. Y.(2003)。Prediction of maximum daily ozone level using combined neural network and statistical characteristics。Atmospheric International,29,555-562。  new window
8.Lu, W.、Wang, W.、Wang, X.、Yan, S.、Lam, J. C.(2004)。Potential assessment of a neural network model with PCA/RBF Approach for forecasting pollutant trends in Mong Kok urban air, Hong Kong。Atmospheric Research,96,79-87。  new window
9.Gardner, M. W.、Dorling, S. R.(1999)。Neural network modelling and prediction of hourly NOx and NO2 concentrations in urban air in London。Atmospheric Environment,33(5),709-719。  new window
10.Perez, P.、Reyes, J.(2002)。Prediction of maximum of 24-h average of PM10 concentrations 30 h in advance in Santiago, Chile。Atmospheric Environment,36,4555-4561。  new window
11.Lin, G.、Chen, L.(2004)。A non-linear rainfall-runoff model using radial basis function network。J. of Hydrology,289,1-8。  new window
12.Moradkhani, H.、Hsu, K.、Gupta, H. V.、Sorooshian, S.(2004)。Improved streamflow forecasting using self-organizing radial basis function artificial neural networks。J. of Hydrology,295,240-262。  new window
13.Ferreira, P. M.、Faria, E. A.、Ruano, A. E.(2002)。Neural network models in greenhouse air temperature prediction。Neurocomputing,43,51-75。  new window
14.Han, H.、Felker, P.(1997)。Estimation of daily soil water evaporation using an artificial neural network。J. of Arid Environ,37,251-260。  new window
15.Lu, H. J.、Chang, G. W.(2018)。A hybrid approach for day-ahead forecast of PV power generation。IFAC PapersOnLine,51,634-638。  new window
16.Sivaneasan, B.、Yu, C. Y.、Goh, K. P.(2017)。Solar forecasting using ANN with fuzzy logic pre-processing。Engergy Procedia,143,727-732。  new window
會議論文
1.余定中、張孝澤、林雨澄(2010)。以類神經網路預估迴龍地區太陽能發電系統之發電量。第三十一屆電力工程研討會,(會議日期: 2010年12月3-4日)。  延伸查詢new window
學位論文
1.劉昱(2017)。以類神經網路建構四季太陽光電系統發電量預測模型之研究(碩士論文)。國立臺北科技大學。  延伸查詢new window
其他
1.EnergyTrend(2017)。太陽能話題持續延燒,2025年全球發電量預計將達到969GW,https://www.energytrend.com.tw/news/20171225-14308712.html。  延伸查詢new window
2.(2016)。太陽能2年推動計畫,http://mrpv.org.tw/page/f80b9aa7。  延伸查詢new window
 
 
 
 
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