KnoX method, or Knowledge eXtraction from neural network model. Case study on the Lez karst aquifer (southern France)

2013 ◽  
Vol 507 ◽  
pp. 19-32 ◽  
Author(s):  
Line Kong-A-Siou ◽  
Kévin Cros ◽  
Anne Johannet ◽  
Valérie Borrell-Estupina ◽  
Séverin Pistre
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Karst Aquifer ◽  
Knowledge Extraction ◽  
Model Case ◽  
Southern France

scholarly journals Prioritization of Air Pollutant Removal (VOC) Scenarios from Refinery R.O.P Units Using Artificial Neural Network Model (Case Study: Abadan Oil Refinery)

2020 ◽  
Vol 8 (1) ◽  
pp. 1-16
Author(s):  
Ladan Khajeh Hoseini ◽  
◽  
Reza Jalilzadeh Yengejeh ◽  
Maryam Mohammadi Rouzbahani ◽  
Sima Sabz alipour ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Air Pollutant ◽  
Pollutant Removal ◽  
Oil Refinery ◽  
Model Case

scholarly journals Identification of Potential Landslide Disaster in East Java Using Neural Network Model (Case Study: District of Ponogoro)

2019 ◽  
Vol 1366 ◽  
pp. 012095
Author(s):  
Alvina Khairun Nisa’ ◽  
Mohammad Isa Irawan ◽  
Danar Guruh Pratomo
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Model Case ◽  
Study District ◽  
Landslide Disaster

scholarly journals PV Power Prediction, Using CNN-LSTM Hybrid Neural Network Model. Case of Study: Temixco-Morelos, México

Energies ◽  
2020 ◽  
Vol 13 (24) ◽  
pp. 6512
Author(s):  
Mario Tovar ◽  
Miguel Robles ◽  
Felipe Rashid
Keyword(s):  
Neural Network ◽  
Hybrid Model ◽  
Network Model ◽  
Neural Network Model ◽  
Short Term Memory ◽  
Lasso Regression ◽  
Neural Network Models ◽  
Model Case ◽  
Hybrid Neural Network ◽  
Photovoltaic Power

Due to the intermittent nature of solar energy, accurate photovoltaic power predictions are very important for energy integration into existing energy systems. The evolution of deep learning has also opened the possibility to apply neural network models to predict time series, achieving excellent results. In this paper, a five layer CNN-LSTM model is proposed for photovoltaic power predictions using real data from a location in Temixco, Morelos in Mexico. In the proposed hybrid model, the convolutional layer acts like a filter, extracting local features of the data; then the temporal features are extracted by the long short-term memory network. Finally, the performance of the hybrid model with five layers is compared with a single model (a single LSTM), a CNN-LSTM hybrid model with two layers and two well known popular benchmarks. The results also shows that the hybrid neural network model has better prediction effect than the two layer hybrid model, the single prediction model, the Lasso regression or the Ridge regression.

A neural-network model to retrieve CDOM absorption from in situ measured hyperspectral data in an optically complex lake: Lake Taihu case study

2011 ◽  
Vol 32 (14) ◽  
pp. 4005-4022 ◽  
Author(s):  
De Yong Sun ◽  
Yun Mei Li ◽  
Qiao Wang ◽  
Heng Lu ◽  
Cheng Feng Le ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Lake Taihu ◽  
Hyperspectral Data

Artificial Neural Network Model for Rainfall-Runoff -A Case Study

2016 ◽  
Vol 9 (3) ◽  
pp. 263-272 ◽  
Author(s):  
P.Sundara Kumar ◽  
T. V. Praveen ◽  
M. Anjanaya Prasad
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Rainfall Runoff ◽  
Artificial Neural
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