4602. Artificial intelligence
| Title | 4602. Artificial intelligence |
|---|---|
| Parent | 46. Information and Computing Sciences |
Latest research outputs
Sort by Date Title
An End-to-End Hierarchical Classification Approach for Similar Gesture Recognition
Wu, Di, Sharma, Nabin and Blumenstein, Michael. 2019. "An End-to-End Hierarchical Classification Approach for Similar Gesture Recognition." 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ). Auckland, New Zealand 19 - 21 Nov 2018 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/IVCNZ.2018.8634660Paper
Similar Gesture Recognition using Hierarchical Classification Approach in RGB Videos
Wu, Di, Sharma, Nabin and Blumenstein, Michael. 2019. "Similar Gesture Recognition using Hierarchical Classification Approach in RGB Videos." 2018 Digital Image Computing: Techniques and Applications (DICTA). Canberra, Australia 10 - 13 Dec 2018 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/DICTA.2018.8615804Paper
Adversarial action data augmentation for similar gesture action recognition
Wu, Di, Chen, Junjun, Sharma, Nabin, Pan, Shirui, Long, Guodong and Blumenstein, Michael. 2019. "Adversarial action data augmentation for similar gesture action recognition." 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.2019.8851993Paper
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
Poisoning attack in federated learning using generative adversarial nets
Zhang, Jiale, Chen, Junjun, Wu, Di, Chen, Bing and Yu, Shui. 2019. "Poisoning attack in federated learning using generative adversarial nets." 2019 18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE). Rotorua, New Zealand 05 - 08 Aug 2018 United States. IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/TrustCom/BigDataSE.2019.00057Paper
Network anomaly detection by using a time-decay closed frequent pattern
Zhao, Ying, Chen, Junjun, Wu, Di, Teng, Jian, Sharma, Nabin, Sajjanhar, Atul and Blumenstein, Michael. 2019. "Network anomaly detection by using a time-decay closed frequent pattern." Information (Basel). 10 (8). https://doi.org/10.3390/info10080262Article
Multi-task network anomaly detection using federated learning
Zhao, Ying, Chen, Junjun, Wu, Di, Teng, Jian and Yu, Shui. 2019. "Multi-task network anomaly detection using federated learning." 10th international symposium on information and communication technology (SoICT 2019). Hanoi, Viet Nam 04 - 06 Dec 2019 United States. Association for Computing Machinery (ACM). https://doi.org/10.1145/3368926.3369705Paper
Power System Disturbance Localization Using Recurrence Quantification Analysis And Minimum-volume-enclosing Ellipsoid: US 10371740 B2
Cui, Yi, Bai, Feifei, Yao, Wenxuan, Liu, Yong, Wu, Ling and Liu, Yilu. 2019. Power System Disturbance Localization Using Recurrence Quantification Analysis And Minimum-volume-enclosing Ellipsoid: US 10371740 B2. 10371740Patent
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
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
Navigation
460201. Artificial life and complex adaptive systems
460202. Autonomous agents and multiagent systems
460203. Evolutionary computation
460206. Knowledge representation and reasoning
460207. Modelling and simulation
460208. Natural language processing
460209. Planning and decision making