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An Extreme Learning Machine Algorithm for Higher Order Neural Network
conference contributionposted on 2023-05-23, 05:34 authored by Shuxiang XuShuxiang Xu
Artificial Neural Networks (ANN) have been widely used as powerful information processing models and adopted in applications such as bankruptcy prediction, predicting costs, forecasting revenue, forecasting share prices and exchange rates, processing documents and many more. This paper uses Extreme Learning Machine (ELM) algorithm for Higher Order Neural Network (HONN) models and applies it in several significant business cases. HONNs are neural networks in which the net input to a computational neuron is a weighted sum of products of its inputs. ELM algorithms randomly choose hidden layer neurons and then only adjust the output weights which connect the hidden layer and the output layer. The experimental results demonstrate that HONN models with ELM algorithm offer significant advantages over standard HONN models as well as traditional ANN models, such as reduced network size, faster training, as well improved simulation and forecasting errors.
Publication titleProceedings of the 23rd European Modeling & Simulation Symposium
EditorsA Bruzzone, MA Piera, F Longo, P Elfrey, M Affenzeller, O Balci
Department/SchoolSchool of Information and Communication Technology
PublisherDIPTEM Universita di Genova
Place of publicationItaly
Event title23rd European Modeling & Simulation Symposium
Event VenueRome, Italy
Date of Event (Start Date)2011-09-12
Date of Event (End Date)2011-09-14
Rights statementCopyright 2011 CAL-TEK S.r.l.