Applying wavelet transformation and artificial neural networks to develop forecasting-based reservoir operating rule curves

2020 ◽  
Vol 65 (12) ◽  
pp. 2007-2021
Author(s):  
Seyed Mohammad Ashrafi ◽  
Ehsan Mostaghimzadeh ◽  
Arash Adib
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wavelet Transformation ◽  
Rule Curves ◽  
Artificial Neural ◽  
Operating Rule ◽  
Operating Rule Curves

scholarly journals Inflow forecasting using Artificial Neural Networks for reservoir operation

2016 ◽  
Vol 373 ◽  
pp. 209-214 ◽  
Author(s):  
Chuthamat Chiamsathit ◽  
Adebayo J. Adeloye ◽  
Soundharajan Bankaru-Swamy
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Reservoir Operation ◽  
Multi Layer Perceptron ◽  
Reservoir Performance ◽  
Reservoir Simulations ◽  
Rule Curves ◽  
Inflow Forecasting ◽  
Artificial Neural ◽  
Storage Type

Abstract. In this study, multi-layer perceptron (MLP) artificial neural networks have been applied to forecast one-month-ahead inflow for the Ubonratana reservoir, Thailand. To assess how well the forecast inflows have performed in the operation of the reservoir, simulations were carried out guided by the systems rule curves. As basis of comparison, four inflow situations were considered: (1) inflow known and assumed to be the historic (Type A); (2) inflow known and assumed to be the forecast (Type F); (3) inflow known and assumed to be the historic mean for month (Type M); and (4) inflow is unknown with release decision only conditioned on the starting reservoir storage (Type N). Reservoir performance was summarised in terms of reliability, resilience, vulnerability and sustainability. It was found that Type F inflow situation produced the best performance while Type N was the worst performing. This clearly demonstrates the importance of good inflow information for effective reservoir operation.

scholarly journals Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation

2015 ◽  
Vol 107 ◽  
pp. 118-128 ◽  
Author(s):  
Xiao Feng ◽  
Qi Li ◽  
Yajie Zhu ◽  
Junxiong Hou ◽  
Lingyan Jin ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Wavelet Transformation ◽  
Air Mass ◽  
Artificial Neural ◽  
Air Mass Trajectory

Determination of S-N curves with the application of artificial neural networks

1999 ◽  
Vol 22 (8) ◽  
pp. 723-728 ◽  
Author(s):  
Artymiak ◽  
Bukowski ◽  
Feliks ◽  
Narberhaus ◽  
Zenner
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Artificial Neural

Artificial neural networks for diagnosis and prognosis in prostate cancer

2002 ◽  
Vol 20 (2) ◽  
pp. 89-95 ◽  
Author(s):  
Guido Schwarzer ◽  
Martin Schumacher
Keyword(s):  
Prostate Cancer ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Diagnosis And Prognosis ◽  
Artificial Neural
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