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Pregled bibliografske jedinice broj: 1067082

Solver parameter influence on the results of multilayer perceptron for estimating power output of a combined cycle power plant


Prpić-Oršić, Jasna; Mrzljak, Vedran; Baressi Šegota, Sandi; Lorencin, Ivan
Solver parameter influence on the results of multilayer perceptron for estimating power output of a combined cycle power plant // V INTERNATIONAL SCIENTIFIC CONFERENCE - SUMMER SESSION - INDUSTRY 4.0 - 2020 - PROCEEDINGS / Popov, Georgi ; Ovtcharova, Jivka (ur.).
Sofia: Scientific technical union of mechanical engineering “Industry - 4.0”, 2020. str. 8-11 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1067082 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Solver parameter influence on the results of multilayer perceptron for estimating power output of a combined cycle power plant

Autori
Prpić-Oršić, Jasna ; Mrzljak, Vedran ; Baressi Šegota, Sandi ; Lorencin, Ivan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
V INTERNATIONAL SCIENTIFIC CONFERENCE - SUMMER SESSION - INDUSTRY 4.0 - 2020 - PROCEEDINGS / Popov, Georgi ; Ovtcharova, Jivka - Sofia : Scientific technical union of mechanical engineering “Industry - 4.0”, 2020, 8-11

Skup
V INTERNATIONAL SCIENTIFIC CONFERENCE - SUMMER SESSION - INDUSTRY 4.0 - 2020

Mjesto i datum
Varna, Bugarska, 24-27.06.2020

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Combined cycle power plant ; Multilayer perceptron ; Artificial neural networks ; Stochastic gradient descent ; Adam ; Solver algorithm

Sažetak
Previous work has determined the ability of using the Multilayer Perceptron (MLP) type of Artificial Neural Network (ANN) to estimate the power output of a Combined Cycle Power Plant (CCPP) in which optimization did not focus on the solver parameter optimization. In previous work, the solvers used the default parameters. Possibility exists that optimizing solver parameters will net better results. Two solver algorithm's parameters are optimized: Stochastic Gradient Descent (SGD) and Adam, with 140 and 720 parameter combinations respectively. Solutions are estimated through the use of Root Mean Square Error (RMSE). Lowest RMSE achieved is 4.275 [MW] for SGD and 4.259 [MW] for Adam, achieved with parameters: a=0.05, u=0.02, and nesterov=True for SGD and with parameters a=0.001, b1=0.95, b2=0.99, and amsgrad=False for Adam. Only a slight improvement is shown in comparison to previous results (RMSE=4.305 [MW]) which points towards the fact that solver parameter optimization with the goal of improving results does not justify the extra time taken for training.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Strojarstvo



POVEZANOST RADA


Projekti:
CEEPUS CIII-HR-0108
DATACROSS KK.01.1.1.01.0009
uniri‐tehnic‐18‐18‐1146
uniri-tehnic-18-275-1447
uniri-tehnic-18-14
HRZZ-IP-2018-01-3739 - Sustav potpore odlučivanju za zeleniju i sigurniju plovidbu brodova (DESSERT) (Prpić-Oršić, Jasna, HRZZ - 2018-01) ( POIROT)

Ustanove:
Tehnički fakultet, Rijeka

Profili:

Avatar Url Jasna Prpić-Oršić (autor)

Avatar Url Vedran Mrzljak (autor)

Avatar Url Ivan Lorencin (autor)

Citiraj ovu publikaciju

Prpić-Oršić, Jasna; Mrzljak, Vedran; Baressi Šegota, Sandi; Lorencin, Ivan
Solver parameter influence on the results of multilayer perceptron for estimating power output of a combined cycle power plant // V INTERNATIONAL SCIENTIFIC CONFERENCE - SUMMER SESSION - INDUSTRY 4.0 - 2020 - PROCEEDINGS / Popov, Georgi ; Ovtcharova, Jivka (ur.).
Sofia: Scientific technical union of mechanical engineering “Industry - 4.0”, 2020. str. 8-11 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Prpić-Oršić, J., Mrzljak, V., Baressi Šegota, S. & Lorencin, I. (2020) Solver parameter influence on the results of multilayer perceptron for estimating power output of a combined cycle power plant. U: Popov, G. & Ovtcharova, J. (ur.)V INTERNATIONAL SCIENTIFIC CONFERENCE - SUMMER SESSION - INDUSTRY 4.0 - 2020 - PROCEEDINGS.
@article{article, year = {2020}, pages = {8-11}, keywords = {Combined cycle power plant, Multilayer perceptron, Artificial neural networks, Stochastic gradient descent, Adam, Solver algorithm}, title = {Solver parameter influence on the results of multilayer perceptron for estimating power output of a combined cycle power plant}, keyword = {Combined cycle power plant, Multilayer perceptron, Artificial neural networks, Stochastic gradient descent, Adam, Solver algorithm}, publisher = {Scientific technical union of mechanical engineering “Industry - 4.0”}, publisherplace = {Varna, Bugarska} }
@article{article, year = {2020}, pages = {8-11}, keywords = {Combined cycle power plant, Multilayer perceptron, Artificial neural networks, Stochastic gradient descent, Adam, Solver algorithm}, title = {Solver parameter influence on the results of multilayer perceptron for estimating power output of a combined cycle power plant}, keyword = {Combined cycle power plant, Multilayer perceptron, Artificial neural networks, Stochastic gradient descent, Adam, Solver algorithm}, publisher = {Scientific technical union of mechanical engineering “Industry - 4.0”}, publisherplace = {Varna, Bugarska} }




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