Short term water level prediction based on C-Stacking ensemble model

Based on the measured water level data after the impound of Three Gorges reservoir, the water level short-term prediction model of income flow of Chenglingji, Han river and Hukou is constructed by multiple regression method. The comparative of measured water level and predicted water level indicated that, the prediction of income flow is accord with the real flow. Meanwhile, according to statistical analysis of the water level and flow, and considering the total inflow and the jacking of branch inflow, the water level short-term prediction model for middle stream Yangtze River is set up separately. Then, by using multiple regression model, the multiple regression formula for water level prediction is constructed , to applied to the river reach where branch inflowed or river reach jacked by the downstream. Compared with the field observation data, the prediction results are quite precisely.

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A sequential approach for short-term water level prediction using nonlinear autoregressive neural networks

2016 XI International Symposium on Telecommunications (BIHTEL) ◽

10.1109/bihtel.2016.7775713 ◽

2016 ◽

Cited By ~ 1

Author(s):

Adis Hamzic ◽

Zikrija Avdagic ◽

Samir Omanovic

Keyword(s):

Neural Networks ◽

Water Level ◽

Short Term ◽

Sequential Approach ◽

Nonlinear Autoregressive ◽

Water Level Prediction

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An Ensemble Model for Short-Term Wind Power Forecasting using Deep Learning and Gradient Boosting Algorithms

2020 21st National Power Systems Conference (NPSC) ◽

10.1109/npsc49263.2020.9331902 ◽

2020 ◽

Author(s):

Devesh Kumar ◽

Rishabh Abhinav ◽

Naran Pindoriya

Keyword(s):

Deep Learning ◽

Wind Power ◽

Gradient Boosting ◽

Ensemble Model ◽

Short Term ◽

Wind Power Forecasting ◽

Boosting Algorithms ◽

Power Forecasting

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Short term water level prediction based on C-Stacking ensemble model

Practical Usages of a Neuro-genetic Programming for Short-term Water Level Prediction

EXAMINATION OF SHORT-TERM WATER LEVEL PREDICTION MODEL IN LOW-LYING LAKES USING MACHINE LEARNING

Short-term water level prediction using different artificial intelligent models

Short-term water level prediction using neural networks and neuro-fuzzy approach

Short-term water level prediction of Hongze Lake by Prophet-LSTM combined model based on LAE

Water level prediction of Lake Poyang based on long short-term memory neural network

Downstream Water Level Prediction of Reservoir based on Convolutional Neural Network and Long Short-Term Memory Network

Short-Term Water Level Prediction in Middle Stream of Yangtze River

A sequential approach for short-term water level prediction using nonlinear autoregressive neural networks

An Ensemble Model for Short-Term Wind Power Forecasting using Deep Learning and Gradient Boosting Algorithms

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