Ionic liquids: prediction of their melting points by a recursive neural network model

2008 ◽  
Vol 10 (3) ◽  
pp. 306 ◽  
Author(s):  
Riccardo Bini ◽  
Cinzia Chiappe ◽  
Celia Duce ◽  
Alessio Micheli ◽  
Roberto Solaro ◽  
...  
Keyword(s):  
Neural Network ◽  
Ionic Liquids ◽  
Network Model ◽  
Neural Network Model ◽  
Melting Points ◽  
Recursive Neural Network

Comparison of LSSVM model results with artificial neural network model for determination of the solubility of SO2 in ionic liquids

2020 ◽  
Vol 304 ◽  
pp. 112771 ◽  
Author(s):  
Hadi Mokarizadeh ◽  
Saeid Atashrouz ◽  
Hamed Mirshekar ◽  
Abdolhossein Hemmati-Sarapardeh ◽  
Ahmad Mohaddes Pour
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ionic Liquids ◽  
Network Model ◽  
Neural Network Model ◽  
Artificial Neural Network Model ◽  
Artificial Neural

Recursive neural network model for analysis and forecast of PM10 and PM2.5

2017 ◽  
Vol 8 (4) ◽  
pp. 652-659 ◽  
Author(s):  
Fabio Biancofiore ◽  
Marcella Busilacchio ◽  
Marco Verdecchia ◽  
Barbara Tomassetti ◽  
Eleonora Aruffo ◽  
...  
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Pm10 And Pm2.5 ◽  
Recursive Neural Network

RECURSIVE NEURAL NETWORK MODEL OF CATAMARAN MANOEUVRING

2021 ◽  
Vol 154 (A3) ◽  
Author(s):  
L Moreira ◽  
C Guedes Soares
Keyword(s):  
Neural Network ◽  
Mathematical Models ◽  
Simulation Model ◽  
Network Model ◽  
Neural Network Model ◽  
Full Scale ◽  
Passenger Transport ◽  
Recursive Neural Network ◽  
Rudder Angle ◽  
Scale Data

A neural network model to simulate catamaran manoeuvres is proposed as an alternative to the traditional methodology of developing manoeuvring mathematical models. Data obtained in full-scale trials with a real ship are used to train the model. By recording full-scale trials of catamaran manoeuvres it is possible to generate a neural network model which will allow the prediction of the catamaran manoeuvring performance under different conditions. A Recursive Neural Network (RNN) manoeuvring simulation model is proposed and applied to a catamaran in this specific case. Inputs to the simulation are the orders of rudder angle and ship’s speed and also the recursive outputs velocities of sway and yaw. Two types of manoeuvres are simulated: tactical circles and zigzags. The results between the full-scale data and the simulations are compared in order to analyze and determine the accuracy of the RNN. The study is performed for a catamaran operating in the Tagus estuary for passenger transport to and from Lisbon.

Recursive Neural Network Model Of Catamaran Manoeuvring

2012 ◽  
Vol 154 (A3) ◽  
Keyword(s):  
Neural Network ◽  
Mathematical Models ◽  
Simulation Model ◽  
Network Model ◽  
Neural Network Model ◽  
Full Scale ◽  
Passenger Transport ◽  
Recursive Neural Network ◽  
Rudder Angle ◽  
Scale Data

A neural network model to simulate catamaran manoeuvres is proposed as an alternative to the traditional methodology of developing manoeuvring mathematical models. Data obtained in full-scale trials with a real ship are used to train the model. By recording full-scale trials of catamaran manoeuvres it is possible to generate a neural network model which will allow the prediction of the catamaran manoeuvring performance under different conditions. A Recursive Neural Network (RNN) manoeuvring simulation model is proposed and applied to a catamaran in this specific case. Inputs to the simulation are the orders of rudder angle and ship’s speed and also the recursive outputs velocities of sway and yaw. Two types of manoeuvres are simulated: tactical circles and zigzags. The results between the full-scale data and the simulations are compared in order to analyze and determine the accuracy of the RNN. The study is performed for a catamaran operating in the Tagus estuary for passenger transport to and from Lisbon.

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