4699. Other information and computing sciences
| Title | 4699. Other information and computing sciences |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
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Information Experience: A Domain and Object of Study
Maybee, Clarence, Abdi, Elham Sayyad, Davis, Kate and Conrad, Lettie. 2019. "Information Experience: A Domain and Object of Study." 82nd Association for Information Science and Technology Annual Meeting: Information...Anyone, Anywhere, Any Time, Any Way. Melbourne, Australia 19 - 23 Oct 2019 United States. John Wiley & Sons. https://doi.org/10.1002/pra2.88Paper
ICT skill frameworks: do they achieve their goals and users’ expectations?
Brown, Jason and Parr, Alan. 2018. "ICT skill frameworks: do they achieve their goals and users’ expectations?" Advanced Journal of Professional Practice. 1 (2), pp. 38-47.Article
An intelligent recommender system based on short-term disease risk prediction for patients with chronic diseases in a telehealth environment
Lafta, Raid Luaibi. 2018. An intelligent recommender system based on short-term disease risk prediction for patients with chronic diseases in a telehealth environment . PhD Thesis Doctor of Philosophy. University of Southern Queensland.PhD Thesis
High-resolution image generation using warping transformations
Scarmana, Gabriel. 2009. "High-resolution image generation using warping transformations." Assuncao, P. and Faria, S. (ed.) 2009 International Conference on Signal Processing and Multimedia Applications (SIGMAP 2009) . Milan, Italy 07 - 10 Jul 2009 Milan, Italy. https://doi.org/10.5220/0002225900490056Paper
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
The La Trobe e-Sanctuary: building a cross-reality wildlife sanctuary
Loke, Seng W., Thai, Ba Son, Torabi, Torab, Chan, Ka, Deng, Dennis, Rahayu, Wenny and Stocker, Andrew. 2015. "The La Trobe e-Sanctuary: building a cross-reality wildlife sanctuary." 11th International Conference on Intelligent Environments (IE´15). Prague, Czech Republic 15 - 17 Jul 2015 New York, United States. https://doi.org/10.1109/IE.2015.36Paper
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
Seasonal climate forecasts and decision support systems for drought prone agriculture: a case study based on the development and application of the Rainman climate analysis software
Clewett, J. F.. 2003. "Seasonal climate forecasts and decision support systems for drought prone agriculture: a case study based on the development and application of the Rainman climate analysis software." Yokoyama, S. and Concepcion, R. N. (ed.) Coping against El Nino for stabilizing rainfed agriculture: lessons from Asia and the Pacific . CGPRT Centre, Bogor, Indonesia. United Nations. pp. 37-55Edited book (chapter)
Optimising farm dam irrigation in response to climatic risk
Clewett, J. F., Howden, S. M., McKeon, G. M. and Rose, C. W.. 1991. "Optimising farm dam irrigation in response to climatic risk." Muchow, Russell C. and Bellamy, Jennifer A. (ed.) Climatic risk in crop production: models and management for the semiarid tropics and subtropics. Wallingford, Oxon, United Kingdom. CABI. pp. 307-328Edited book (chapter)
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. 328-359Edited book (chapter)
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)
Geospatial crowdsourced data fitness analysis for spatial data infrastructure based disaster management actions
Koswatte, Saman. 2017. Geospatial crowdsourced data fitness analysis for spatial data infrastructure based disaster management actions . PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/5c09fc67f0cd3PhD Thesis
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
Relevance assessment of crowdsourced data (CSD) using semantics and geographic information retrieval (GIR) techniques
Koswatte, Saman, McDougall, Kevin and Liu, Xiaoye. 2018. "Relevance assessment of crowdsourced data (CSD) using semantics and geographic information retrieval (GIR) techniques." ISPRS International Journal of Geo-Information. 7 (7), pp. 1-18. https://doi.org/10.3390/ijgi7070256Article
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
A Framework for Analyzing and Evaluating Architectures and Control Strategies in Distributed Remote Laboratories
Maiti, Ananda, Zutin, Danilo G., Wuttke, Heinz-Dietrich, Henke, Karsten, Maxwell, Andrew D. and Kist, Alexander A.. 2018. "A Framework for Analyzing and Evaluating Architectures and Control Strategies in Distributed Remote Laboratories." IEEE Transactions on Learning Technologies. 11 (4), pp. 441-455. https://doi.org/10.1109/TLT.2017.2787758Article
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
Image fusion and enhancement using triangulated irregular networks
Scarmana, G.. 2017. "Image fusion and enhancement using triangulated irregular networks." Remondino, Fabio and Shortis, Mark R. (ed.) Videometrics, Range Imaging and Applications XIV Conference . Munich, Germany 26 - 29 Jun 2017 Bellingham, Washington, United States. https://doi.org/10.1117/12.2279443Paper
Matlab code for implementing SS-OFDM
Alhasnawi, Mohammad and Addie, Ron. 2018. Matlab code for implementing SS-OFDM.Other
Epileptic EEG signal classification using optimum allocation based power spectral density estimation
Al Ghayab, Hadi Ratham, Li, Yan, Siuly, Siuly and Abdulla, Shahab. 2018. "Epileptic EEG signal classification using optimum allocation based power spectral density estimation." IET Signal Processing. 12 (6), pp. 738-747. https://doi.org/10.1049/iet-spr.2017.0140Article
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)
Preface - Proceedings of the 2017 IEEE/WIC/ACM international conference on web intelligence
Alt, Rainer, Tao, Xiaohui and Unland, Rainer. 2017. "Preface - Proceedings of the 2017 IEEE/WIC/ACM international conference on web intelligence." 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2017). Leipzig, Germany 23 - 26 Aug 2017 New York, United States.Paper
Exploring the value of big data analysis of Twitter tweets and share prices
Wlodarczak, Peter. 2017. Exploring the value of big data analysis of Twitter tweets and share prices. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/5c05cde0d30ccPhD Thesis
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
Knowing when to target students with timely academic learning support: not a minefield with data mining
McCarthy, Elizabeth. 2017. "Knowing when to target students with timely academic learning support: not a minefield with data mining." Partridge, H., Davis, K. and Thomas, J. (ed.) 34th International Conference on Innovation, Practice and Research in the Use of Educational Technologies in Tertiary Education (ASCILITE 2017). Toowoomba, Australia 04 - 06 Dec 2017 Toowoomba, Australia.Paper
An analysis system detecting epileptic seizure from EEG
Kabir, Enamul and Wang, Hua. 2017. "An analysis system detecting epileptic seizure from EEG." 2017 Young Statisticians Conference: Modelling Our Future. Tweed Heads, Australia 26 - 27 Sep 2017 Australia.Presentation
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.2018.05.003Article
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
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