Cost-Benefit Analysis in Multiple Time Series Prediction

Chamila Walgampaya (Autor)

Buch | Softcover

124 Seiten

2020
Scholars' Press (Verlag)
978-613-8-94331-0 (ISBN)

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We are proposing a new methodology to select optimum number of subset of sensors to predict energy production in a network of energy generation plants in the USA. Multiple time series data are collected for the period 2002-2004 from 200 power plants across the USA. Prediction models were generated using Support Vector Machines (SVM), Multilayer Perceptron (MLP), and Multiple Regression (MR) techniques. A cost benefit analysis was used to estimate the optimum number of measurements to be used to forecast the total energy generation that balances the expenses of the system with the prediction accuracy.

Walgampaya, Chamila Chamila Walgampaya is a Senior Lecturer in the Faculty of Engineering, University of Peradeniya, Sri Lanka. He received his B.Sc. degree from the Faculty of Engineering, University of Peradeniya in 2001. He earned his MS degrees in Computer Engineering from the University of Louisville, USA, in 2006.

Erscheinungsdatum	02.08.2021
Sprache	englisch
Maße	152 x 229 mm
Gewicht	191 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Analysis
Schlagworte	Multilayer Perceptron • multiple regression • Multiple Time Series • Support Vector Machines
ISBN-10	613-8-94331-7 / 6138943317
ISBN-13	978-613-8-94331-0 / 9786138943310
Zustand	Neuware