4605. Data management and data science
Title | 4605. Data management and data science |
---|---|
Parent | 46. Information and Computing Sciences |
Latest research outputs
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Anchored Vertex Exploration for Community Engagement in Social Networks
Cai, Taotao, Li, Jianxin, Hasan Haldar, Nur Al, Mian, Ajmal, Yearwood, John and Sellis, Timos. 2020. "Anchored Vertex Exploration for Community Engagement in Social Networks ." 2020 IEEE 36th International Conference on Data Engineering (ICDE). Dallas, United States 20 - 24 Apr 2020 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICDE48307.2020.00042Paper
Investigating website features quality using three online techniques on the lead generation website - a case study
Al-Gburi, Hamzah Mohammed Kadhim. 2020. Investigating website features quality using three online techniques on the lead generation website - a case study. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/q18g-3f53PhD Thesis
Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models
Kisi, Ozgur, Choubin, Bahram, Deo, Ravinesh C. and Yaseen, Zaheer Mundher. 2019. "Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models." Hydrological Sciences Journal. 64 (10), pp. 1240-1252. https://doi.org/10.1080/02626667.2019.1632460Article
Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms
Ali, Mumtaz, Deo, Ravinesh C., Maraseni, Tek and Downs, Nathan J.. 2019. "Improving SPI-derived drought forecasts incorporating synoptic-scale climate indices in multi-phase multivariate empirical mode decomposition model hybridized with simulated annealing and kernel ridge regression algorithms." Journal of Hydrology. 576, pp. 164-184. https://doi.org/10.1016/j.jhydrol.2019.06.032Article
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/en12122407Article
PMT: new analytical framework for automated evaluation of geo-environmental modelling approaches
Rahmati, Omid, Kornejady, Aiding, Samadi, Mahmood, Deo, Ravinesh C., Conoscenti, Christian, Lombardo, Luigi, Dayal, Kavina, Taghizadeh-Mehrjardi, Ruhollah, Pourghasemi, Hamid Reza, Kumar, Sandeep and Bui, Dieu Tien. 2019. "PMT: new analytical framework for automated evaluation of geo-environmental modelling approaches." Science of the Total Environment. 664, pp. 296-311. https://doi.org/10.1016/j.scitotenv.2019.02.017Article
Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: a new approach
Deo, Ravinesh C., Sahin, Mehmet, Adamowski, Jan F. and Mi, Jianchun. 2019. "Universally deployable extreme learning machines integrated with remotely sensed MODIS satellite predictors over Australia to forecast global solar radiation: a new approach." Renewable and Sustainable Energy Reviews. 104, pp. 235-261. https://doi.org/10.1016/j.rser.2019.01.009Article
Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems
Wen, Xiaohu, Feng, Qi, Deo, Ravinesh C., Wu, Min, Yin, Zhenliang, Yang, Linshan and Singh, Vijay P.. 2019. "Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems." Journal of Hydrology. 570, pp. 167-184. https://doi.org/10.1016/j.jhydrol.2018.12.060Article
PAX: using pseudonymization and anonymization to protect patients’ identities and data in the healthcare system
Al-Zubaidie, Mishall, Zhang, Zhongwei and Zhang, Ji. 2019. "PAX: using pseudonymization and anonymization to protect patients’ identities and data in the healthcare system." International Journal of Environmental Research and Public Health. 16 (1490), pp. 1-36. https://doi.org/10.3390/ijerph16091490Article
Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches
Maroufpoor, Saman, Sanikhani, Hadi, Kisi, Ozgur, Deo, Ravinesh C. and Yaseen, Zaher Mundher. 2019. "Long-term modelling of wind speeds using six different heuristic artificial intelligence approaches." International Journal of Climatology. 39 (8), pp. 3543-3557. https://doi.org/10.1002/joc.6037Article
Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system
Roshni, Thendiyath, Jha, Madan K., Deo, Ravinesh C. and Vandana, A.. 2019. "Development and evaluation of hybrid artificial neural network architectures for modeling spatio-temporal groundwater fluctuations in a complex aquifer system." Water Resources Management. 33 (7), pp. 2381-2397. https://doi.org/10.1007/s11269-019-02253-4Article
A novel social network hybrid recommender system based on hypergraph topologic structure
Zheng, Xiaoyao, Luo, Yonglong, Sun, Liping, Ding, Xintao and Zhang, Ji. 2018. "A novel social network hybrid recommender system based on hypergraph topologic structure." World Wide Web. 21 (4), pp. 985-1013. https://doi.org/10.1007/s11280-017-0494-5Article
Logic connectives of complex fuzzy sets
Ngan, Tran Thi, Lan, Luong Thi Hong, Ali, Mumtaz, Tamir, Dan, Son, Le Hoang, Tuan, Tran Manh, Rishe, Naphtali and Kandel, Abe. 2018. "Logic connectives of complex fuzzy sets." Romanian Journal of Information Science and Technology. 21 (4), pp. 344-357.Article
Feature-dependent graph convolutional autoencoders with adversarial training methods
Wu, Di, Hu, Ruiqi, Zheng, Yu, Jiang, Jing, Sharma, Nabin and Blumenstein, Michael. 2019. "Feature-dependent graph convolutional autoencoders with adversarial training methods." 2019 International Joint Conference on Neural Networks (IJCNN). Budapest, Hungary 14 - 19 Jul 2019 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IJCNN.2019.8852314Paper
Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties
Kouadio, Louis, Deo, Ravinesh C., Byrareddy, Vivekananda, Adamowski, Jan F., Mushtaq, Shahbaz and Nguyen, Van Phuong. 2018. "Artificial intelligence approach for the prediction of Robusta coffee yield using soil fertility properties." Computers and Electronics in Agriculture. 155, pp. 324-338. https://doi.org/10.1016/j.compag.2018.10.014Article
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
An evaluation of the performance of a NoSQL document database in a simulation of a large scale Electronic Health Record (EHR) system
Ercan, Mehmet Zahid. 2017. An evaluation of the performance of a NoSQL document database in a simulation of a large scale Electronic Health Record (EHR) system. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/5c09b7aff0cc4PhD Thesis
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
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
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
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
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
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
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
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
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
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
On secure wireless communications for IoT under eavesdropper collusion
Zhang, Yuanyu, Shen, Yulong, Wang, Hua, Yong, Jianming and Jiang, Xiaohong. 2016. "On secure wireless communications for IoT under eavesdropper collusion." IEEE Transactions on Automation Science and Engineering. 13 (3), pp. 1281-1293. https://doi.org/10.1109/TASE.2015.2497663Article
Holistic Influence Maximization for Targeted Advertisements in Spatial Social Networks
Li, Jianxin, Cai, Taotao, Mian, Ajmal, Li, Rong-Hua, Sellis, Timos and Yu, Jeffrey Xu. 2018. "Holistic Influence Maximization for Targeted Advertisements in Spatial Social Networks ." 2018 IEEE 34th International Conference on Data Engineering (ICDE). Paris, France 16 - 19 Apr 2018 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/ICDE.2018.00145Paper
Complex networks approach for EEG signal sleep stages classification
Diykh, Mohammed and Li, Yan. 2016. "Complex networks approach for EEG signal sleep stages classification." Expert Systems with Applications. 63, pp. 241-248. https://doi.org/10.1016/j.eswa.2016.07.004Article
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
Instance independent concurrency control for semistructured databases
Dekeyser, Stijn, Hidders, Jan and Paredaens, Jan. 2003. "Instance independent concurrency control for semistructured databases." Flesca, Sergio and Sacca, Domenico (ed.) 11th Italian Symposium on Advanced Database Systems. Cetraro, Italy 24 - 27 Jun 2003Paper
Modeling users' web search behavior and their cognitive styles
Kinley, Khamsum, Tjondronegoro, Dian, Partridge, Helen and Edwards, Sylvia. 2014. "Modeling users' web search behavior and their cognitive styles." American Journal of Information Science and Technology. 65 (6), pp. 1107-1123. https://doi.org/10.1002/asi.23053Article
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460501. Data engineering and data science
460502. Data mining and knowledge discovery
460503. Data models, storage and indexing
460506. Graph, social and multimedia data
460507. Information extraction and fusion
460508. Information retrieval and web search
460509. Query processing and optimisation
460511. Stream and sensor data
460599. Data management and data science not elsewhere classified