Dynamic cost forecasting model based on extreme learning machine - A case study in steel plant

Ou, Tsung-Yin; Cheng, Chen-Yang; Chen, Po‐Jung; Perng, Chyuan

doi:10.1016/j.cie.2016.09.012

Cited by 33 publications

(10 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Extreme learning machine (ELM) is a fast learning machine with a higher level of generalization capability that is constructed with a single-hidden layer feed-forward neural network [33], [49]- [51]. The hidden layer is made up of a suitable number of hidden nodes which is an important hyperparameter of the learning method.…”

Section: E Univariate Time Series Modelsmentioning

confidence: 99%

See 1 more Smart Citation

Healthcare Operations and Black Swan Event for COVID-19 Pandemic: A Predictive Analytics

Persis

Manimuthu

Sreedharan

2023

IEEE Trans. Eng. Manage.

View full text Add to dashboard Cite

COVID-19 pandemic has questioned the way healthcare operations take place globally as the healthcare professionals face an unprecedented task of controlling and treating the COVID-19 infected patients with a highly straining and draining facility due to the erratic admissions of infected patients. However, COVID-19 is considered as a white swan event. Yet, the impact of the COVID-19 pandemic on healthcare operations is highly uncertain and disruptive making it as a black swan event. Therefore, the study explores the impact of the COVID-19 outbreak on healthcare operations and develops machine learning-based forecasting models using time series data to foresee the progression of COVID-19 and further using predictive analytics to better manage healthcare operations. The prediction error of the proposed model is found to be 0.039 for new cases and 0.006 for active COVID-19 cases with respect to mean absolute percentage error. The proposed simulated model further could generate predictive analytics and yielded future recovery rate, resource management ratios, and average cycle time of a patient tested COVID-19 positive. Further, the study will help healthcare professionals to devise better resilience and decision-making for managing uncertainty and disruption in healthcare operations.

show abstract

Section: E Univariate Time Series Modelsmentioning

confidence: 99%

“…. , ŷin ] T yield zero errors, then w i , β i , b i exist for every sample by applying Moore-Penrose generalized inverse [23], [33], [35], [51]- [53] of the hidden layer to output layer such a way that…”

Section: E Univariate Time Series Modelsmentioning

confidence: 99%

Healthcare Operations and Black Swan Event for COVID-19 Pandemic: A Predictive Analytics

Persis

Manimuthu

Sreedharan

2023

IEEE Trans. Eng. Manage.

View full text Add to dashboard Cite

show abstract

“…ELM neural network, called transfinite learning machine algorithm [12][13], is a typical single hidden layer feedforward neural network structure, which is composed of input layer, hidden layer, and output layer. The connection mode between the input layer and hidden layer, hidden layer and output layer neurons is full connection.…”

Section: 2elm Neural Networkmentioning

confidence: 99%

A Prediction Model of Alloy Yield in RH Furnace Based On SSA-ELM

Guo

Liu

Chai

2022

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Aiming at the problem that it is difficult to predict the alloy yield in the RH furnace refining process, an alloy yield prediction model based on a sparrow search algorithm (SSA) optimized ELM neural network is proposed. Firstly, because the dimensions of input parameters are different, 11 input features are reduced by factor analysis (FA), and 5 input features are obtained. Then, through the sparrow search algorithm with fast convergence, high precision, and good stability, the input weight value and threshold of the ELM neural network are optimized, the SSA-ELM alloy yield prediction model is established, the alloy yield is predicted, and the off-line operation of the model is realized, which provides a theoretical basis for the prediction of alloy yield in the actual production process. Finally, by comparing the simulation results with the actual production data, it is found that the prediction results of the target element alloy yield predicted by the SSA-ELM are within the error range, and the prediction accuracy is higher than that of the ELM prediction model, which verifies the feasibility and effectiveness of the model.

show abstract

“…Do modeli matematycznych zaliczają oni metody oparte na szeregach czasowych oraz drugą grupę modeli przyczynowo--skutkowych w postaci modeli ekonometrycznych. Do metod niematematycznych według autorów należą: modele heurystyczne, analogowe, zmiennych wiodących, scenariuszowe oraz modele, w których osoba wykonująca prognozę korzysta z sieci neuronowych (Cyplik, Pruska, Kupczyk, 2014, s. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17].…”

Section: Analiza Literatury Przedmiotu Badańunclassified

Forecasting of Total Costs in the Łukplast Enterprise for 2020

Kozicki

Tomaszewski²,

Dylak³

2020

SLW

View full text Add to dashboard Cite

<div class="contentJustify">W artykule poruszony został problem badawczy z zakresu analizy, oceny i prognozowania danych pierwotnych dotyczących zaewidencjonowanych kosztów w przedsiębiorstwie Łukplast w ujęciu dynamicznym. Przeprowadzono analizę literatury przedmiotu badań dotyczącą kosztów i ich podziału. Scharakteryzowano termin prognozowanie. Przeprowadzono wielowymiarową analizę danych pierwotnych. Poddano analizie szereg czasowy kosztów całkowitych oraz wykonano jego prognozowanie na 2020 rok w ujęciu miesięcznym. Uzyskana prognoza poddana została analizie i ocenie. Artykuł kończy się podsumowaniem i wnioskami.</div>

show abstract

Dynamic cost forecasting model based on extreme learning machine - A case study in steel plant

Cited by 33 publications

References 22 publications

Healthcare Operations and Black Swan Event for COVID-19 Pandemic: A Predictive Analytics

Healthcare Operations and Black Swan Event for COVID-19 Pandemic: A Predictive Analytics

A Prediction Model of Alloy Yield in RH Furnace Based On SSA-ELM

Forecasting of Total Costs in the Łukplast Enterprise for 2020

Contact Info

Product

Resources

About