460207. Modelling and simulation
| Title | 460207. Modelling and simulation |
|---|---|
| Parent | 4602. Artificial intelligence |
Latest research outputs
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Selection of representative feature training sets with self-organized maps for optimized time series modeling and prediction: application to forecasting daily drought conditions with ARIMA and neural network models
McCarthy, Elizabeth, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Selection of representative feature training sets with self-organized maps for optimized time series modeling and prediction: application to forecasting daily drought conditions with ARIMA and neural network models." 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. 446-464Edited book (chapter)
Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors
Sanikhani, Hadi, Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur, Mert, Chian, Mirabbasi, Rasoul, Gavili, Siavash and Yaseen, Zaher Mundher. 2018. "Survey of different data-intelligent modeling strategies for forecasting air temperature using geographic information as model predictors." Computers and Electronics in Agriculture. 152, pp. 242-260. https://doi.org/10.1016/j.compag.2018.07.008Article
Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition
Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Soil moisture forecasting by a hybrid machine learning technique: ELM integrated with ensemble empirical mode decomposition." Geoderma. 330, pp. 136-161. https://doi.org/10.1016/j.geoderma.2018.05.035Article
Modeling the joint influence of multiple synoptic-scale, climate mode indices on Australian wheat yield using a vine copula-based approach
Nguyen-Huy, Thong, Deo, Ravinesh C., Mushtaq, Shahbaz, An-Vo, Duc-Anh and Khan, Shahjahan. 2018. "Modeling the joint influence of multiple synoptic-scale, climate mode indices on Australian wheat yield using a vine copula-based approach." European Journal of Agronomy. 98, pp. 65-81. https://doi.org/10.1016/j.eja.2018.05.006Article
Non-tuned data intelligent model for soil temperature estimation: a new approach
Sanikhani, Hadi, Deo, Ravinesh C., Yaseen, Zaher Mundheer, Eray, Okan and Kisi, Ozgur. 2018. "Non-tuned data intelligent model for soil temperature estimation: a new approach." Geoderma. 330, pp. 52-64. https://doi.org/10.1016/j.geoderma.2018.05.030Article
Drought modelling based on artificial intelligence and neural network algorithms: a case study in Queensland, Australia
Dayal, Kavina, Deo, Ravinesh and Apan, Armando A.. 2017. "Drought modelling based on artificial intelligence and neural network algorithms: a case study in Queensland, Australia." Filho, Walter Leal (ed.) Climate change adaptation in Pacific countries:fostering resilience and improving the quality of life. Springer. pp. 177-198Edited book (chapter)
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.2018.05.012Article
Re-imagining standard timescales in forecasting precipitation events for Queensland’s grazing enterprises
McCarthy, E., Deo, R. C., Li, Y. and Maraseni, T.. 2017. "Re-imagining standard timescales in forecasting precipitation events for Queensland’s grazing enterprises." Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. (ed.) 22nd International Congress on Modelling and Simulation (MODSIM2017). Hobart, Australia 03 - 08 Dec 2017 Australia. Modelling and Simulation Society of Australia and New Zealand . https://doi.org/10.36334/modsim.2017.L1.mccarthyPaper
An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index." Atmospheric Research. 207, pp. 155-180. https://doi.org/10.1016/j.atmosres.2018.02.024Article
Wavelet analysis–artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China
Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Wu, Min and Si, Jianhua. 2017. "Wavelet analysis–artificial neural network conjunction models for multi-scale monthly groundwater level predicting in an arid inland river basin, northwestern China." Hydrology Research: an international journal. 48 (6), pp. 1710-1729. https://doi.org/10.2166/nh.2016.396Article
A new approach to predict daily pH in rivers based on the 'a trous' redundant wavelet transform algorithm
Rajaee, Taher, Ravansalar, Masoud, Adamowski, Jan F. and Deo, Ravinesh C.. 2018. "A new approach to predict daily pH in rivers based on the 'a trous' redundant wavelet transform algorithm." Water, Air and Soil Pollution: an international journal of environmental pollution. 229 (3). https://doi.org/10.1007/s11270-018-3715-3Article
Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions and Research Directions
Fallah, Seyedeh Narjes, Deo, Ravinesh Chand, Shojafar, Mohammad, Conti, Mauro and Shamshirband, Shahaboddin. 2018. "Computational intelligence approaches for energy load forecasting in smart energy management grids: state of the art, future challenges, and research directions and Research Directions." Energies. 11 (3). https://doi.org/10.3390/en11030596Article
Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon electricity demand forecasting
Al-Musaylh, Mohanad S., Deo, Ravinesh C., Li, Yan and Adamowski, Jan F.. 2018. "Two-phase particle swarm optimized-support vector regression hybrid model integrated with improved empirical mode decomposition with adaptive noise for multiple-horizon electricity demand forecasting." Applied Energy. 217, pp. 422-439. https://doi.org/10.1016/j.apenergy.2018.02.140Article
Application of the hybrid artificial neural network coupled with rolling mechanism and grey model algorithms for streamflow forecasting over multiple time horizons
Yaseen, Zaher Mundher, Fu, Minglei, Wang, Chen, Mohtar, Wan Hanna Melini Wan, Deo, Ravinesh C. and El-Shafie, Ahmed. 2018. "Application of the hybrid artificial neural network coupled with rolling mechanism and grey model algorithms for streamflow forecasting over multiple time horizons." Water Resources Management. 32 (5), pp. 1883-1899. https://doi.org/10.1007/s11269-018-1909-5Article
Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia
Al-Musaylh, Mohanad S., Deo, Ravinesh C., Adamowski, Jan F. and Li, Yan. 2018. "Short-term electricity demand forecasting with MARS, SVR and ARIMA models using aggregated demand data in Queensland, Australia." Advanced Engineering Informatics: the science of supporting knowledge-intensive activities. 35 (C), pp. 1-16. https://doi.org/10.1016/j.aei.2017.11.002Article
Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms
Barzegar, Rahim, Moghaddam, Asghar Asghari, Deo, Ravinesh, Fijani, Elham and Tziritis, Evangelos. 2018. "Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms." Science of the Total Environment. 621, pp. 697-712. https://doi.org/10.1016/j.scitotenv.2017.11.185Article
An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia
Salcedo-sanz, Sancho, Deo, Ravinesh C., Cornejo-Bueno, Laura, Camacho-Gomez, Carlos and Ghimire, Sujan. 2018. "An efficient neuro-evolutionary hybrid modelling mechanism for the estimation of daily global solar radiation in the Sunshine State of Australia." Applied Energy. 209, pp. 79-94. https://doi.org/10.1016/j.apenergy.2017.10.076Article
Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference station data
Deo, Ravinesh C., Ghorbani, Mohammad Ali, Samadianfard, Saeed, Maraseni, Tek, Bilgili, Mehmet and Biazar, Mustafa. 2018. "Multi-layer perceptron hybrid model integrated with the firefly optimizer algorithm for windspeed prediction of target site using a limited set of neighboring reference station data." Renewable Energy. 116 (Part A), pp. 309-323. https://doi.org/10.1016/j.renene.2017.09.078Article
Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region
Allawi, Mohammed Falah, Jaafar, Othman, Hamzah, Firdaus Mohamad, Mohd, Nuruol Syuhadaa, Deo, Ravinesh C. and El-Shafie, Ahmed. 2018. "Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region." Theoretical and Applied Climatology. 134 (1-2), pp. 545-563. https://doi.org/10.1007/s00704-017-2292-5Article
Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey
Ghorbani, Mohammad Ali, Deo, Ravinesh C., Karimi, Vahid, Yaseen, Zaher Mundher and Terz, Ozlem. 2018. "Implementation of a hybrid MLP-FFA model for water level prediction of Lake Egirdir, Turkey." Stochastic Environmental Research and Risk Assessment. 32 (6), pp. 1683-1697. https://doi.org/10.1007/s00477-017-1474-0Article
Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran
Ghorbani, M. A., Deo, Ravinesh C., Yaseen, Zaher Mundher, Kashani, Mahsa H. and Mohammadi, Babak. 2018. "Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran." Theoretical and Applied Climatology. 133 (3-4), pp. 1119-1131. https://doi.org/10.1007/s00704-017-2244-0Article
Market share modelling and forecasting using Markov chains and alternative models
Chan, Ka Ching. 2015. "Market share modelling and forecasting using Markov chains and alternative models." International Journal of Innovative Computing Information and Control. 11 (4), pp. 1205-1218.Article
Forecasting evaporative loss by least-square support-vector regression and evaluation with genetic programming, Gaussian process, and minimax probability machine regression: case study of Brisbane City
Deo, Ravinesh C. and Samui, Pijush. 2017. "Forecasting evaporative loss by least-square support-vector regression and evaluation with genetic programming, Gaussian process, and minimax probability machine regression: case study of Brisbane City." Journal of Hydrologic Engineering. 22 (6), pp. 1-15. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001506Article
Comparative study of hybrid-wavelet artificial intelligence models for monthly groundwater depth forecasting in extreme arid regions, Northwest China
Yu, Haijiao, Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Si, Jianhua and Wu, Min. 2018. "Comparative study of hybrid-wavelet artificial intelligence models for monthly groundwater depth forecasting in extreme arid regions, Northwest China." Water Resources Management. 32 (1), pp. 301-323. https://doi.org/10.1007/s11269-017-1811-6Article
Predicting compressive strength of lightweight foamed concrete using extreme learning machine model
Yaseen, Zaher Mundher, Deo, Ravinesh C., Hilal, Ameer, Abd, Abbas M., Bueno, Laura Cornejo, Salcedo-sanz, Sancho and Nehdi, Moncef L.. 2018. "Predicting compressive strength of lightweight foamed concrete using extreme learning machine model." Advances in Engineering Software. 115, pp. 112-125. https://doi.org/10.1016/j.advengsoft.2017.09.004Article
Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model
Yaseen, Zaher Mundher, Ebtehaj, Isa, Bonakdari, Hossein, Deo, Ravinesh C., Mehr, Ali Danandeh, Mohtar, Wan Hanna Melini Wan, Diop, Lamine, El-Shafie, Ahmed and Singh, Vijay P.. 2017. "Novel approach for streamflow forecasting using a hybrid ANFIS-FFA model." Journal of Hydrology. 554, pp. 263-276. https://doi.org/10.1016/j.jhydrol.2017.09.007Article
Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA
Yaseen, Zaher Mundher, Ghareb, Mazen Ismaeel, Ebtehaj, Isa, Bonakdari, Hossein, Siddique, Ridwan, Heddam, Sali, Yusif, Ali A. and Deo, Ravinesh. 2018. "Rainfall Pattern Forecasting Using Novel Hybrid Intelligent Model Based ANFIS-FFA." Water Resources Management. 32 (1), pp. 105-122. https://doi.org/10.1007/s11269-017-1797-0Article
Synthetic retrieval of hourly net ecosystem exchange using the neural network model with combined MI and GOCI geostationary sensor datasets and ground-based measurements
Yeom, Jong-Min, Deo, Ravinesh, Chun, Junghwa, Hong, Jinkyu, Kim, Dong-Su, Han, Kyung-Soo and Cho, Jaeil. 2017. "Synthetic retrieval of hourly net ecosystem exchange using the neural network model with combined MI and GOCI geostationary sensor datasets and ground-based measurements." International Journal of Remote Sensing. 38 (23), pp. 7441-7456. https://doi.org/10.1080/01431161.2017.1375573Article
Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle
Deo, Ravinesh C., Downs, Nathan, Parisi, Alfio V., Adamowski, Jan F. and Quilty, John M.. 2017. "Very short-term reactive forecasting of the solar ultraviolet index using an extreme learning machine integrated with the solar zenith angle." Environmental Research. 155, pp. 141-166. https://doi.org/10.1016/j.envres.2017.01.035Article
Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland
Deo, Ravinesh C. and Sahin, Mehmet. 2017. "Forecasting long-term global solar radiation with an ANN algorithm coupled with satellite-derived (MODIS) land surface temperature (LST) for regional locations in Queensland." Renewable and Sustainable Energy Reviews. 72, pp. 828-848. https://doi.org/10.1016/j.rser.2017.01.114Article
Big data in engineering applications
Roy, Sanjiban Sekhar, Samui, Pijushi, Deo, Ravinesh and Ntalampiras, Stalampiras (ed.) 2018. Big data in engineering applications. Singapore. Springer.Edited book
Handbook of research on predictive modeling and optimization methods in science and engineering
Kim, Dookie, Roy, Sanjiban Sekhar, Lansivaara, Tim, Deo, Ravinesh C. and Samui, Pijush (ed.) 2018. Handbook of research on predictive modeling and optimization methods in science and engineering. United States. IGI Global.Edited book
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
Yaseen, Zaher Mundher, Jaafar, Othman, Deo, Ravinesh C., Kisi, Ozgur, Adamowski, Jan, Quilty, John and El-Shafie, Ahmed. 2016. "Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq." Journal of Hydrology. 542, pp. 603-614. https://doi.org/10.1016/j.jhydrol.2016.09.035Article
Diverging importance of drought stress for maize and winter wheat in Europe
Webber, Heidi, Ewert, Frank, Olesen, Jørgen E., Müller, Christoph, Fronzek, Stefan, Ruane, Alex C., Bourgault, Maryse, Martre, Pierre, Ababaei, Behnam, Bindi, Marco, Ferrise, Roberto, Finger, Robert, Fodor, Nándor Fodor, Gabaldón-Leal, Clara, Gaiser, Thomas, Jabloun, Mohamed, Kersebaum, Kurt-Christian, Lizaso, Jon I., Lorite, Ignacio J., ..., Wallach, Daniel. 2018. "Diverging importance of drought stress for maize and winter wheat in Europe." Nature Communications. 9. https://doi.org/10.1038/s41467-018-06525-2Article
Numeric investigation of brain tumor influence on the current distributions during transcranial direct current stimulation
Song, Bo, Wen, Peng, Ahfock, Tony and Li, Yan. 2016. "Numeric investigation of brain tumor influence on the current distributions during transcranial direct current stimulation." IEEE Transactions on Biomedical Engineering. 63 (1), pp. 176-187. https://doi.org/10.1109/TBME.2015.2468672Article
An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland
Deo, Ravinesh C. and Sahin, Mehmet. 2016. "An extreme learning machine model for the simulation of monthly mean streamflow water level in eastern Queensland." Environmental Monitoring and Assessment. 188 (90). https://doi.org/10.1007/s10661-016-5094-9Article
Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model
Deo, Ravinesh C., Tiwari, Mukesh K., Adamowski, Jan F. and Quilty, John M.. 2017. "Forecasting effective drought index using a wavelet extreme learning machine (W-ELM) model." Stochastic Environmental Research and Risk Assessment. 31 (5), pp. 1211-1240. https://doi.org/10.1007/s00477-016-1265-zArticle
Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
Deo, Ravinesh C., Kisi, Ogzur and Singh, Vijay P.. 2017. "Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model." Atmospheric Research. 184, pp. 149-175. https://doi.org/10.1016/j.atmosres.2016.10.004Article
A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset
Deo, Ravinesh C., Wen, Xiaohu and Feng, Qi. 2016. "A wavelet-coupled support vector machine model for forecasting global incident solar radiation using limited meteorological dataset." Applied Energy. 168, pp. 568-593. https://doi.org/10.1016/j.apenergy.2016.01.130Article
Multihop compute-and-forward for generalised two-way relay channels
Wang, Gengkun, Xiang, Wei and Yuan, Jinhong. 2015. "Multihop compute-and-forward for generalised two-way relay channels ." Transactions on Emerging Telecommunications Technologies. 26 (3), pp. 448-460. https://doi.org/10.1002/ett.2644Article