Evaluation of multivariate adaptive regression splines and artificial neural network for prediction of mean sea level trend around northern Australian coastlines

Article


Raj, Nawin and Gharineiat, zahra. 2021. "Evaluation of multivariate adaptive regression splines and artificial neural network for prediction of mean sea level trend around northern Australian coastlines." Mathematics. 9 (21), pp. 1-20. https://doi.org/10.3390/math9212696
Article Title

Evaluation of multivariate adaptive regression splines and artificial neural network for prediction of mean sea level trend around northern Australian coastlines

ERA Journal ID213646
Article CategoryArticle
AuthorsRaj, Nawin (Author) and Gharineiat, zahra (Author)
Journal TitleMathematics
Journal Citation9 (21), pp. 1-20
Article Number2696
Number of Pages20
Year2021
PublisherMDPI AG
Place of PublicationBasel, Switzerland
ISSN2227-7390
Digital Object Identifier (DOI)https://doi.org/10.3390/math9212696
Web Address (URL)https://www.mdpi.com/2227-7390/9/21/2696
Abstract

Mean sea level rise is a significant emerging risk from climate change. This research paper is based on the use of artificial intelligence models to assess and predict the trend on mean sea level around northern Australian coastlines. The study uses sea-level times series from four sites (Broom, Darwin, Cape Ferguson, Rosslyn Bay) to make the prediction. Multivariate adaptive regression splines (MARS) and artificial neural network (ANN) algorithms have been implemented to build the prediction model. Both models show high accuracy (R2 > 0.98) and low error values (RMSE < 27%) overall. The ANN model showed slightly better performance compared to MARS over the selected sites. The ANN performance was further assessed for modelling storm surges associated with cyclones. The model reproduced the surge profile with the maximum correlation coefficients ~0.99 and minimum RMS errors ~4 cm at selected validating sites. In addition, the ANN model predicted the maximum surge at Rosslyn Bay for cyclone Marcia to within 2 cm of the measured peak and the maximum surge at Broome for cyclone Narelle to within 7 cm of the measured peak. The results are comparable with a MARS model previously used in this region; however, the ANN shows better agreement with the measured peak and arrival time, although it suffers from slightly higher predictions than the observed sea level by tide gauge station.

KeywordsANN; MARS; mean sea level; prediction; Australia; tide gauge
ANZSRC Field of Research 2020370803. Physical oceanography
370603. Geodesy
461104. Neural networks
Public Notes

Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Byline AffiliationsSchool of Sciences
School of Civil Engineering and Surveying
Institution of OriginUniversity of Southern Queensland
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Ahmed, A. A. Masrur, Deo, Ravinesh C., Ghahramani, Afshin, Raj, Nawin, Feng, Qi, Yin, Zhenliang and Yang, Linshan. 2021. "LSTM integrated with Boruta-random forest optimiser for soil moisture estimation under RCP4.5 and RCP8.5 global warming scenarios." Stochastic Environmental Research and Risk Assessment. 35, pp. 1851-1881. https://doi.org/10.1007/s00477-021-01969-3
Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity
Ahmed, A. A. Masrur, Deo, Ravinesh C., Feng, Qi, Ghahramani, Afshin, Raj, Nawin, Yin, Zhenliang and Yang, Linshan. 2021. "Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity." Journal of Hydrology. 599, pp. 1-23. https://doi.org/10.1016/j.jhydrol.2021.126350
An EEMD-BiLSTM algorithm integrated with Boruta random forest optimiser for significant wave height forecasting along coastal areas of Queensland, Australia
Raj, Nawin and Brown, Jason. 2021. "An EEMD-BiLSTM algorithm integrated with Boruta random forest optimiser for significant wave height forecasting along coastal areas of Queensland, Australia." Remote Sensing. 13 (8), pp. 1-20. https://doi.org/10.3390/rs13081456
Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning
Gunasekara, C., Lokuge, W., Keskic, M., Raj, N., Law, D. W. and Setunge, S.. 2020. "Design of Alkali-Activated Slag-Fly Ash Concrete Mixtures Using Machine Learning." ACI Materials Journal. 117 (5), pp. 263-278. https://doi.org/10.14359/51727019
Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra, Parisi, Alfio and Raj, Nawin. 2020. "Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks." IEEE Access. 8, pp. 209503-209516. https://doi.org/10.1109/ACCESS.2020.3039002
Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji
Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji." Stochastic Environmental Research and Risk Assessment. 35 (7), pp. 1387-1402. https://doi.org/10.1007/s00477-020-01899-6
Plantar Pressure Characteristics in Obese Individuals: A Proposed Methodology
Al-Daffaie, Kadhem, Chong, Albert K. and Gharineiat, Zahra. 2019. "Plantar Pressure Characteristics in Obese Individuals: A Proposed Methodology." 2019 3rd International Conference on Imaging, Signal Processing and Communication (ICISPC). Singapore 27 - 29 Jul 2019 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICISPC.2019.8935691
Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network
Huynh, Anh Ngoc‐Lan, Deo, Ravinesh C., An-Vo, Duc-Anh, Ali, Mumtaz, Raj, Nawin and Abdulla, Shahab. 2020. "Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network." Energies. 13 (14). https://doi.org/10.3390/en13143517
Spectral Analysis of Satellite Altimeters and Tide Gauges Data around the Northern Australian Coast
Gharineiat, Zahra and Deng, Xiaoli. 2020. "Spectral Analysis of Satellite Altimeters and Tide Gauges Data around the Northern Australian Coast." Remote Sensing. 12 (1), pp. 1-15. https://doi.org/10.3390/rs12010161
Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Wavelet-based 3-phase hybrid SVR model trained with satellite-derived predictors, particle swarm optimization and maximum overlap discrete wavelet transform for solar radiation prediction." Renewable and Sustainable Energy Reviews. 113, pp. 1-19. https://doi.org/10.1016/j.rser.2019.109247
Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms." Applied Energy. 253, pp. 1-20. https://doi.org/10.1016/j.apenergy.2019.113541
Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction
Ghimire, Sujan, Deo, Ravinesh C., Raj, Nawin and Mi, Jianchun. 2019. "Deep Learning Neural Networks Trained with MODIS Satellite-Derived Predictors for Long-Term Global Solar Radiation Prediction." Energies. 12 (12), pp. 1-42. https://doi.org/10.3390/en12122407
Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia
Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2019. "Global solar radiation prediction by ANN integrated with European Centre for medium range weather forecast fields in solar rich cities of Queensland Australia." Journal of Cleaner Production. 216, pp. 288-310. https://doi.org/10.1016/j.jclepro.2019.01.158
Description and assessment of regional sea-level trends and variability from altimetry and tide gauges at the northern Australian coast
Gharineiat, Zahra and Deng, Xiaoli. 2018. "Description and assessment of regional sea-level trends and variability from altimetry and tide gauges at the northern Australian coast." Advances in Space Research. 61 (10), pp. 2540-2554. https://doi.org/10.1016/j.asr.2018.02.038
Coastal altimetry for sea level changes in Northern Australian coastal oceans
Gharineiat, Zahra. 2017. Coastal altimetry for sea level changes in Northern Australian coastal oceans. PhD Thesis Doctor of Philosophy. University of Newcastle.
Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model
Deo, Ravinesh C., Ghimire, Sujan, Downs, Nathan J. and Raj, Nawin. 2018. "Optimization of windspeed prediction using an artificial neural network compared with a genetic programming model." Kim, Dookie, Roy, Sanjiban Sekhar, Lansivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) Handbook of research on predictive modeling and optimization methods in science and engineering. Hershey, United States. IGI Global. pp. 328-359
Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region
Mouatadid, Soukayna, Raj, Nawin, Deo, Ravinesh C. and Adamowski, Jan F.. 2018. "Input selection and data-driven model performance optimization to predict the Standardized Precipitation and Evaporation Index in a drought-prone region." Atmospheric Research. 212, pp. 130-149. https://doi.org/10.1016/j.atmosres.2018.05.012
Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities
Ghimire, Sujan, Deo, Ravinesh C., Downs, Nathan J. and Raj, Nawin. 2018. "Self-adaptive differential evolutionary extreme learning machines for long-term solar radiation prediction with remotely-sensed MODIS satellite and Reanalysis atmospheric products in solar-rich cities." Remote Sensing of Environment: an interdisciplinary journal. 212, pp. 176-198. https://doi.org/10.1016/j.rse.2018.05.003
Adiabatic decay of internal solitons due to Earth’s rotation within the framework of the Gardner–Ostrovsky equation
Obregon, Maria, Raj, Nawin and Stepanyants, Yury. 2018. "Adiabatic decay of internal solitons due to Earth’s rotation within the framework of the Gardner–Ostrovsky equation." Chaos: an interdisciplinary journal of nonlinear science. 28 (3), pp. 1-11. https://doi.org/10.1063/1.5021864
Observing and modelling the high water level from satellite radar altimetry during tropical cyclones
Deng, Xiaoli, Gharineiat, Zahra, Andersen, Ole B. and Stewart, Mark G.. 2016. "Observing and modelling the high water level from satellite radar altimetry during tropical cyclones." Rizos, Chris and Willis, Pascal (ed.) 2013 IAG Scientific Assembly. Postdam, Germany 01 - 06 Sep 2013 Switzerland. https://doi.org/10.1007/1345_2015_108
Adiabatic decay of internal solitons in a rotating ocean
Obregon, M. A., Raj, N. and Stepanyants, Y. A.. 2016. "Adiabatic decay of internal solitons in a rotating ocean." 20th Australasian Fluid Mechanics Conference (AFMC 2016). Perth, Australia 05 - 08 Dec 2016 Australia.
Application of the multi adaptive regression splines to integrate sea level data from altimetry and tide gauges for monitoring extreme sea level events
Gharineiat, Zahra and Deng, Xiaoli. 2015. "Application of the multi adaptive regression splines to integrate sea level data from altimetry and tide gauges for monitoring extreme sea level events." Marine Geodesy. 38 (3), pp. 261-276. https://doi.org/10.1080/01490419.2015.1036183
Nonlinear vector waves of a flexural mode in a chain model of atomic particles
Nikitenkova, S. P., Raj, N. and Stepanyants, Y. A.. 2015. "Nonlinear vector waves of a flexural mode in a chain model of atomic particles." Communications in Nonlinear Science and Numerical Simulation. 20 (3), pp. 731-742. https://doi.org/10.1016/j.cnsns.2014.05.031
Nonlinear spectra of shallow water waves
Giovanangeli, J. -P., Kharif, C., Raj, N. and Stepanyants, Y.. 2013. "Nonlinear spectra of shallow water waves." Oceans - San Diego, 2013. San Diego, United States 23 - 26 Sep 2013 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.23919/OCEANS.2013.6741132
Numerical study of nonlinear wave processes by means of discrete chain models
Obregon, M., Raj, N. and Stepanyants, Y.. 2012. "Numerical study of nonlinear wave processes by means of discrete chain models." Gu, Y. T. and Saha, Suvash C. (ed.) 4th International Conference on Computational Methods (ICCM 2012). Gold Coast, Australia 25 - 28 Nov 2012 Brisbane, Australia.