460207. Modelling and simulation
| Title | 460207. Modelling and simulation |
|---|---|
| Parent | 4602. Artificial intelligence |
Latest research outputs
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Design and implementation of a hybrid MLP-GSA model with multilayer perceptron-gravitational search algorithm for monthly lake water level forecasting
Ghorbani, Mohammad Ali, Deo, Ravinesh C., Karimi, Vahid, Kashani, Mahsa H. and Ghorbani, Shahryar. 2018. "Design and implementation of a hybrid MLP-GSA model with multilayer perceptron-gravitational search algorithm for monthly lake water level forecasting." Stochastic Environmental Research and Risk Assessment. 33 (1), pp. 125-147. https://doi.org/10.1007/s00477-018-1630-1Article
Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMI-rice model
Yeom, Jong-min, Jeong, Seungtaek, Jeong, Gwanyong, Ng, Chi Tim, Deo, Ravinesh C. and Ko, Jonghan. 2018. "Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMI-rice model." Scientific Reports. 8, pp. 1-15. https://doi.org/10.1038/s41598-018-34550-0Article
Artificial intelligence-based fast and efficient hybrid approach for spatial modelling of soil electrical conductivity
Ghorbani, Mohammad Ali, Deo, Ravinesh C., Kashani, Mahsa H., Shahabi, Mahmoud and Ghorbani, Shahryar. 2019. "Artificial intelligence-based fast and efficient hybrid approach for spatial modelling of soil electrical conductivity." Soil and Tillage Research. 186, pp. 152-164. https://doi.org/10.1016/j.still.2018.09.012Article
Adaptive Neuro-Fuzzy Inference System integrated with solar zenith angle for forecasting sub-tropical photosynthetically active radiation
Deo, Ravinesh C., Downs, Nathan J., Adamowski, Jan F. and Parisi, Alfio V.. 2018. "Adaptive Neuro-Fuzzy Inference System integrated with solar zenith angle for forecasting sub-tropical photosynthetically active radiation." Food and Energy Security. 8 (1). https://doi.org/10.1002/fes3.151Article
Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: a new hybrid copula-driven approach
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Cotton yield prediction with Markov Chain Monte Carlo-based simulation model integrated with genetic programing algorithm: a new hybrid copula-driven approach." Agricultural and Forest Meteorology. 263, pp. 428-448. https://doi.org/10.1016/j.agrformet.2018.09.002Article
Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment
Yin, Zhenliang, Feng, Qi, Wen, Xiaohu, Deo, Ravinesh C., Yang, Linshan, Si, Jianhua and He, Zhibin. 2018. "Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment." Stochastic Environmental Research and Risk Assessment. 32 (9), pp. 2457-2476. https://doi.org/10.1007/s00477-018-1585-2Article
Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Multi-stage committee based extreme learning machine model incorporating the influence of climate parameters and seasonality on drought forecasting." Computers and Electronics in Agriculture. 152, pp. 149-165. https://doi.org/10.1016/j.compag.2018.07.013Article
Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2018. "Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting." Atmospheric Research. 213, pp. 450-464. https://doi.org/10.1016/j.atmosres.2018.07.005Article
Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters
Fijani, Elham, Barzegar, Rahim, Deo, Ravinesh, Tziritis, Evangelos and Konstantinos, Skordas. 2019. "Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters." Science of the Total Environment. 648, pp. 839-853. https://doi.org/10.1016/j.scitotenv.2018.08.221Article
Hybrid data intelligent models and applications for water level prediction
Yaseen, Zaher Mundher, Deo, Ravinesh C., Ebtehaj, Isa and Bonakdari, Hossein. 2018. "Hybrid data intelligent models and applications for water level prediction." Kim, Dookie, Roy, Sanjiban Sekhar, Länsivaara, 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. 121-139Edited book (chapter)
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