Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation

Article

Prasad, Ramendra, Ali, Mumtaz, Kwan, Paul and Khan, Huma. 2019. "Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation." Applied Energy. 236, pp. 778-792. https://doi.org/10.1016/j.apenergy.2018.12.034
Article Title

Designing a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest model to forecast monthly solar radiation

ERA Journal ID4005
Article CategoryArticle
AuthorsPrasad, Ramendra (Author), Ali, Mumtaz (Author), Kwan, Paul (Author) and Khan, Huma (Author)
Journal TitleApplied Energy
Journal Citation236, pp. 778-792
Number of Pages15
Year2019
PublisherElsevier
Place of PublicationUnited Kingdom
ISSN0306-2619
1872-9118
Digital Object Identifier (DOI)https://doi.org/10.1016/j.apenergy.2018.12.034
Web Address (URL)https://www.sciencedirect.com/science/article/pii/S030626191831849X
Abstract

Solar energy is an alternative renewable energy resource that has the potential of cleanly addressing the increasing demand for electricity in the modern era to overcome future energy crises. In this paper, a multi-stage multivariate empirical mode decomposition coupled with ant colony optimization and random forest (i.e., MEMD-ACO-RF) is designed to forecast monthly solar radiation (Rn). In the first stage, the proposed multi-stage MEMD-ACO-RF model, the MEMD algorithm demarcates the multivariate climate data from January 1905 to June 2018 into resolved signals i.e., intrinsic mode functions (IMFs) and a residual component. After computing the multivariate IMFs, the ant colony optimization (ACO) algorithm is used to determine the best IMFs based features for model development by incorporating the historical lagged data at (t − 1) in the second stage. The RF model at the third stage is applied to the selected IMFs to forecast monthly Rn. The results are benchmarked with M5 tree (M5tree) and minimax probability machine regression (MPMR) models integrated with MEMD and ACO, to develop the comparative hybrid MEMD-ACO-M5tree and MEMD-ACO-MPMR models respectively. The multi-stage MEMD-ACO-RF model is also evaluated against the standalone RF, M5tree and MPMR models. The proposed multi-stage MEMD-ACO-RF with comparative models is tested geographically in three locations of the Queensland state, in Australia. Based on robust evaluation metrics, the proposed multi-stage MEMD-ACO-RF model outperformed models that were compared during the testing phase and has shown the prospects of an accurate forecasting tool. The proposed multi-stage MEMD-ACO-RF model can be considered as a pertinent decision-support framework for monthly Rn forecasting.

Keywordssolar radiation; energy; multivariate empirical mode decomposition; ant colony optimization; random forest
ANZSRC Field of Research 2020419999. Other environmental sciences not elsewhere classified
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Byline AffiliationsSchool of Agricultural, Computational and Environmental Sciences
University of New England
University of Management and Technology, Pakistan
Institution of OriginUniversity of Southern Queensland
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https://research.usq.edu.au/item/q5043/designing-a-multi-stage-multivariate-empirical-mode-decomposition-coupled-with-ant-colony-optimization-and-random-forest-model-to-forecast-monthly-solar-radiation

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Thanh, Nguyen Dang, Son, Le Hoang and Ali, Mumtaz. 2017. "Neutrosophic Recommender System for Medical Diagnosis Based on Algebraic Similarity Measure and Clustering." 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). Naples, Italy 09 - 12 Jul 2017 Piscataway, United States. https://doi.org/10.1109/FUZZ-IEEE.2017.8015387
An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis
Thao, Nguyen Xuan, Ali, Mumtaz and Smarandache, Florentin. 2019. "An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis." Journal of Intelligent and Fuzzy Systems. 36 (1), pp. 189-198. https://doi.org/10.3233/JIFS-181084
Linguistic Approaches to Interval Complex Neutrosophic Sets in Decision Making
Dat, Luu Quoc, Thong, Nguyen Tho, Son, Le Hoang, Ali, Mumtaz, Smarandache, Florentin, Abdel-Basset, Mohamed and Long, Hoang Viet. 2019. "Linguistic Approaches to Interval Complex Neutrosophic Sets in Decision Making." IEEE Access. 7, pp. 38902-38917. https://doi.org/10.1109/ACCESS.2019.2902841
Dynamic interval valued neutrosophic set: Modeling decision making in dynamic environments
Thong, Nguyen Tho, Dat, Luu Quoc, Son, Le Hoang, Hoa, Nguyen Dinh, Ali, Mumtaz and Smarandache, Florentin. 2019. "Dynamic interval valued neutrosophic set: Modeling decision making in dynamic environments." Computers in Industry. 108, pp. 45-52. https://doi.org/10.1016/j.compind.2019.02.009
Fuzzy and neutrosophic modeling for link prediction in social networks
Tuan, Tran Manh, Chuan, Pham Minh, Ali, Mumtaz, Ngan, Tran Thi, Mittal, Mamta and Son, Le Hoang. 2019. "Fuzzy and neutrosophic modeling for link prediction in social networks." Evolving Systems. 10, pp. 629-634. https://doi.org/10.1007/s12530-018-9251-y
Novel hybrid deep learning model for satellite based PM10 forecasting in the most polluted Australian hotspots
Sharma, Ekta, Deo, Ravinesh C., Soar, Jeffrey, Prasad, Ramendra, Parisi, Alfio V. and Raj, Nawin. 2022. "Novel hybrid deep learning model for satellite based PM10 forecasting in the most polluted Australian hotspots." Atmospheric Environment. 279, pp. 1-13. https://doi.org/10.1016/j.atmosenv.2022.119111
Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection
Malik, Anurag, Jamei, Mehdi, Ali, Mumtaz, Prasad, Ramendra, Karbasi, Masoud and Yaseen, Zaher Mundher. 2022. "Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection." Agricultural Water Management. 272. https://doi.org/https://doi.org/10.1016/j.agwat.2022.107812
Fuzzy Equivalence on Standard and Rough Neutrosophic Sets and Applications to Clustering Analysis
Thao, Nguyen Xuan, Son, Le Hoang, Cuong, Bui Cong, Ali, Mumtaz and Lan, Luong Hong. 2018. "Fuzzy Equivalence on Standard and Rough Neutrosophic Sets and Applications to Clustering Analysis." Bhateja, Vikrant, Nguyen, Bao Le, Nguyen, Nhu Gia, Satapathy, Suresh Chandra and Le, Dac-Nhuong (ed.) 4th International Conference on Information Systems Design and Intelligent Applications (INDIA 2017). Da Nang, Vietnam 15 - 17 Jun 2017 Singapore. https://doi.org/10.1007/978-981-10-7512-4_82
Development of data-driven models for wind speed forecasting in Australia
Neupane, Ananta, Raj, Nawin, Deo, Ravinesh and Ali, Mumtaz. 2021. "Development of data-driven models for wind speed forecasting in Australia." Deo, R., Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Netherlands. Elsevier. pp. 143-190
Multifractal characterization and cross correlations of reference evapotranspiration time series of India
Adarsh, S., Nityanjaly, L. J., Pham, Quoc Bao, Sarang, R., Ali, Mumtaz and Nandhineekrishna, P.. 2021. "Multifractal characterization and cross correlations of reference evapotranspiration time series of India." European Physical Journal: Special Topics. 230 (21-22), pp. 3845-3859. https://doi.org/10.1140/epjs/s11734-021-00325-4
Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Khan, Mohsin, Farooque, Aitazaz Ahsan, Zong, Tianrui and Yaseen, Zaher Mundher. 2021. "Variational mode decomposition based random forest model for solar radiation forecasting: New emerging machine learning technology." Energy Reports. 7, pp. 6700-6717. https://doi.org/10.1016/j.egyr.2021.09.113
Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong, Sankaran, Adarsh, Deo, Ravinesh C., Xiao, Fuyuan and Zhu, Shuyu. 2021. "Advanced extreme learning machines vs. deep learning models for peak wave energy period forecasting: A case study in Queensland, Australia." Renewable Energy. 177, pp. 1033-1044. https://doi.org/10.1016/j.renene.2021.06.052
Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition
Huynh, Anh Ngoc-Lan, Deo, Ravinesh C., Ali, Mumtaz, Abdulla, Shahab and Raj, Nawin. 2021. "Novel short-term solar radiation hybrid model: long short-term memory network integrated with robust local mean decomposition." Applied Energy. 298, pp. 1-19. https://doi.org/10.1016/j.apenergy.2021.117193
Self-supervised cross-iterative clustering for unlabeled plant disease images
Fang, Uno, Li, J., Lu, X., Gao, Longxiang, Ali, Mumtaz and Xiang, Yong. 2021. "Self-supervised cross-iterative clustering for unlabeled plant disease images." Neurocomputing. 456, pp. 36-48. https://doi.org/10.1016/j.neucom.2021.05.066
Spatiotemporal variability of multifractal properties of fineresolution daily gridded rainfall fields over India
Sankaran, Adarsh, Chavan, Sagar Rohidas, Ali, Mumtaz, Devarajan, Archana Devarajan, Dharan, Drisya Sasi and Khan, Muhammad Ismail. 2021. "Spatiotemporal variability of multifractal properties of fineresolution daily gridded rainfall fields over India." Natural Hazards. 106 (3), pp. 1951-1979. https://doi.org/10.1007/s11069-021-04523-0
Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh
Yaseen, Zaher Mundher, Ali, Mumtaz, Sharafati, Ahmad, Al-Ansari, Nadhir and Shahid, Shamsuddin. 2021. "Forecasting standardized precipitation index using data intelligence models: regional investigation of Bangladesh." Scientific Reports. 11 (1), pp. 1-25. https://doi.org/10.1038/s41598-021-82977-9
Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra, Parisi, Alfio and Raj, Nawin. 2020. "Deep Air Quality Forecasts: Suspended Particulate Matter Modeling With Convolutional Neural and Long Short-Term Memory Networks." IEEE Access. 8, pp. 209503-209516. https://doi.org/10.1109/ACCESS.2020.3039002
Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach
Ali, Mumtaz, Deo, Ravinesh C., Xiang, Yong, Li, Ya and Yaseen, Zaher Mundher. 2020. "Forecasting long-term precipitation for water resource management: a new multi-step data-intelligent modelling approach." Hydrological Sciences Journal. 65 (16), pp. 2693-2708. https://doi.org/10.1080/02626667.2020.1808219
Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji
Moishin, Mohammed, Deo, Ravinesh C., Prasad, Ramendra, Raj, Nawin and Abdulla, Shahab. 2021. "Development of Flood Monitoring Index for daily flood risk evaluation: case studies in Fiji." Stochastic Environmental Research and Risk Assessment. 35 (7), pp. 1387-1402. https://doi.org/10.1007/s00477-020-01899-6
Modeling wheat yield with data-intelligent algorithms: artificial neural network versus genetic programming and minimax probability machine regression
Ali, Mumtaz and Deo, Ravinesh C.. 2020. "Modeling wheat yield with data-intelligent algorithms: artificial neural network versus genetic programming and minimax probability machine regression." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 37-87
Short-term electrical energy demand prediction under heat island effects using emotional neural network integrated with genetic algorithm
Karalasingham, Sagthitharan, Deo, Ravinesh and Prasad, Ramendra. 2021. "Short-term electrical energy demand prediction under heat island effects using emotional neural network integrated with genetic algorithm." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 271-298
Multifractal Cross Correlation Analysis of Agro-Meteorological Datasets (Including Reference Evapotranspiration) of California, United States
Sankaran, A., Krzyszczak, Jaromir, Baranowski, Piotr, Devarajan Sindhu, Archana, Nandhineekrishna Pradeep, Kumar, Lija Jayaprakash, Nityanjali, Thankamani, Vandana and Ali, Mumtaz. 2020. "Multifractal Cross Correlation Analysis of Agro-Meteorological Datasets (Including Reference Evapotranspiration) of California, United States." Atmosphere. 11 (10), pp. 1-24. https://doi.org/10.3390/atmos11101116
Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan
Ali, Mumtaz. 2019. Probabilistic and artificial intelligence modelling of drought and agricultural crop yield in Pakistan. PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/S847-M467
Daily flood forecasts with intelligent data analytic models: multivariate empirical mode decomposition-based modeling methods
Prasad, Ramendra, Charan, Dhrishna, Joseph, Lionel, Nguyen-Huy, Thong, Deo, Ravinesh C. and Singh, Sanjay. 2021. "Daily flood forecasts with intelligent data analytic models: multivariate empirical mode decomposition-based modeling methods." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 359-381
Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction
Nguyen-Huy, Thong, Deo, Ravinesh C., Yaseen, Zaher Mundher, Mushtaq, Shahbaz and Prasad, Ramendra. 2021. "Bayesian Markov Chain Monte Carlo-based copulas: factoring the role of large-scale climate indices in monthly flood prediction." Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher (ed.) Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer. pp. 29-47
Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Deo, Ravinesh C.. 2020. "Near real-time significant wave height forecasting with hybridized multiple linear regression algorithms." Renewable and Sustainable Energy Reviews. 132. https://doi.org/10.1016/j.rser.2020.110003
Arithmetic Operations of Neutrosophic Sets, Interval Neutrosophic Sets and Rough Neutrosophic Sets
Smarandache, Florentin, Ali, Mumtaz and Khan, Mohsin. 2019. "Arithmetic Operations of Neutrosophic Sets, Interval Neutrosophic Sets and Rough Neutrosophic Sets." Kahraman, Cengiz and Otay, Irem (ed.) Fuzzy Multi-criteria Decision-Making Using Neutrosophic Sets. Cham, Switzerland. Springer. pp. 25-42
Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network
Huynh, Anh Ngoc‐Lan, Deo, Ravinesh C., An-Vo, Duc-Anh, Ali, Mumtaz, Raj, Nawin and Abdulla, Shahab. 2020. "Near real-time global solar radiation forecasting at multiple time-step horizons using the long short-term memory network." Energies. 13 (14). https://doi.org/10.3390/en13143517
Development of Advanced Computer Aid Model for Shear Strength of Concrete Slender Beam Prediction
Sharafati, Ahmad, Haghbin, Masoud, Aldlemy, Mohammed Suleman, Mussa, Mohamed H., Al Zand, Ahmed W., Ali, Mumtaz, Bhagat, Suraj Kumar, Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2020. "Development of Advanced Computer Aid Model for Shear Strength of Concrete Slender Beam Prediction." Applied Sciences. 10 (11), pp. 1-25. https://doi.org/10.3390/app10113811
A double decomposition-based modelling approach to forecast weekly solar radiation
Prasad, Ramendra, Ali, Mumtaz, Xiang, Yong and Khan, Huma. 2020. "A double decomposition-based modelling approach to forecast weekly solar radiation." Renewable Energy. 152, pp. 9-22. https://doi.org/10.1016/j.renene.2020.01.005
A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms
Sharma, Ekta, Deo, Ravinesh C., Prasad, Ramendra and Parisi, Alfio V.. 2020. "A hybrid air quality early-warning framework: an hourly forecasting model with online sequential extreme learning machines and empirical mode decomposition algorithms." Science of the Total Environment. 709, pp. 1-23. https://doi.org/10.1016/j.scitotenv.2019.135934
M-CFIS-R: Mamdani Complex Fuzzy Inference System with Rule Reduction Using Complex Fuzzy Measures in Granular Computing
Tuan, Tran Manh, Lan, Luong Thi Hong, Chou, Shuo-Yan, Ngan, Tran Thi, Son, Le Hoang, Giang, Nguyen Long and Ali, Mumtaz. 2020. "M-CFIS-R: Mamdani Complex Fuzzy Inference System with Rule Reduction Using Complex Fuzzy Measures in Granular Computing." Mathematics. 8 (5), pp. 1-24. https://doi.org/10.3390/math8050707
Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts
Ali, Mumtaz, Prasad, Ramendra, Xiang, Yong and Yaseen, Z.. 2020. "Complete ensemble empirical mode decomposition hybridized with random forest and kernel ridge regression model for monthly rainfall forecasts." Journal of Hydrology. 584, pp. 1-15. https://doi.org/10.1016/j.jhydrol.2020.124647
The Generalized Neutrosophic Cubic Aggregation Operators and Their Application to Multi-Expert Decision-Making Method
Khan, Majid, Gulistan, Muhammad, Ali, Mumtaz and Chammam, Wathek. 2020. "The Generalized Neutrosophic Cubic Aggregation Operators and Their Application to Multi-Expert Decision-Making Method." Symmetry. 12 (4), pp. 1-15. https://doi.org/10.3390/sym12040496
Prediction of evaporation in arid and semi-arid regions: a comparative study using different machine learning models
Yaseen, Zaher Mundher, Al-Juboori, Al-Juboori, Beyaztasc, Ufuk, Al-Ansari, Nadhir, Chau, Kwok-Wing, Qi, Chongchong, Ali, Mumtaz, Salih, Sinan Q. and Shahid, Shamsuddin. 2020. "Prediction of evaporation in arid and semi-arid regions: a comparative study using different machine learning models." Engineering Applications of Computational Fluid Mechanics. 14 (1), pp. 70-89. https://doi.org/10.1080/19942060.2019.1680576
Monthly rainfall forecasting with Markov Chain Monte Carlo simulations integrated with statistical bivariate copulas
Ali, Mumtaz, Deo, Ravinesh C., Downs, Nathan J. and Maraseni, Tek. 2020. "Monthly rainfall forecasting with Markov Chain Monte Carlo simulations integrated with statistical bivariate copulas." Samui, Pijush, Bui, Dieu Tien, Chakraborty, Subrata and Deo, Ravinesh C. (ed.) Handbook of probabilistic models. Oxford, United Kingdom. Elsevier. pp. 89-105
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.2019.06.032
Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition
Ali, Mumtaz and Prasad, Ramendra. 2019. "Significant wave height forecasting via an extreme learning machine model integrated with improved complete ensemble empirical mode decomposition." Renewable and Sustainable Energy Reviews. 104, pp. 281-295. https://doi.org/10.1016/j.rser.2019.01.014
Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach
Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2019. "Weekly soil moisture forecasting with multivariate sequential, ensemble empirical mode decomposition and Boruta-random forest hybridizer algorithm approach." Catena. 177, pp. 149-166. https://doi.org/10.1016/j.catena.2019.02.012
Streamflow and soil moisture forecasting with hybrid data intelligent machine learning approaches: case studies in the Australian Murray-Darling basin
Prasad, Ramendra. 2018. Streamflow and soil moisture forecasting with hybrid data intelligent machine learning approaches: case studies in the Australian Murray-Darling basin . PhD Thesis Doctor of Philosophy. University of Southern Queensland. https://doi.org/10.26192/5f6974e4dccd5
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.
A novel approach for fuzzy clustering based on neutrosophic association matrix
Long, Hoang Viet, Ali, Mumtaz, Son, Le Hoang, Khan, Mohsin and Tu, Doan Ngoc. 2019. "A novel approach for fuzzy clustering based on neutrosophic association matrix." Computers and Industrial Engineering. 127, pp. 687-697. https://doi.org/10.1016/j.cie.2018.11.007
Systematic review of decision making algorithms in extended neutrosophic sets
Khan, Mohsin, Son, Le Hoang, Ali, Mumtaz, Chau, Hoang Thi Minh, Na, Nguyen Thi Nhu and Smarandache, Florentin. 2018. "Systematic review of decision making algorithms in extended neutrosophic sets." Symmetry. 10 (8), pp. 1-28. https://doi.org/10.3390/sym10080314
Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model
Hou, Muzhou, Zhang, Tianle, Weng, Futian, Ali, Mumtaz, Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2018. "Global Solar Radiation Prediction Using Hybrid Online Sequential Extreme Learning Machine Model." Energies. 11 (12), pp. 1-19. https://doi.org/10.3390/en11123415
New Soft Set Based Class of Linear Algebraic Codes
Ali, Mumtaz, Khan, Huma, Son, Le Hoang, Smarandache, Florentin and Kandasamy, W. B. Vasantha. 2018. "New Soft Set Based Class of Linear Algebraic Codes." Symmetry. 10 (10), pp. 1-10. https://doi.org/10.3390/sym10100510
H-max distance measure of intuitionistic fuzzy sets in decision making
Ngan, Roan Thi, Son, Le Hoang, Cuong, Bui Cong and Ali, Mumtaz. 2018. "H-max distance measure of intuitionistic fuzzy sets in decision making." Applied Soft Computing. 69, pp. 393-425. https://doi.org/10.1016/j.asoc.2018.04.036
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.2018.09.002
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.2018.07.013
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.2018.07.005
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.2018.05.035
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.2018.02.024
Ensemble committee-based data intelligent approach for generating soil moisture forecasts with multivariate hydro-meteorological predictors
Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2018. "Ensemble committee-based data intelligent approach for generating soil moisture forecasts with multivariate hydro-meteorological predictors." Soil and Tillage Research. 181, pp. 63-81. https://doi.org/10.1016/j.still.2018.03.021
Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm
Prasad, Ramendra, Deo, Ravinesh C., Li, Yan and Maraseni, Tek. 2017. "Input selection and performance optimization of ANN-based streamflow forecasts in the drought-prone Murray Darling Basin region using IIS and MODWT algorithm." Atmospheric Research. 197, pp. 42-63. https://doi.org/10.1016/j.atmosres.2017.06.014
Bipolar neutrosophic soft sets and applications in decision making
Ali, Mumtaz, Son, Le Hoang, Deli, Irfan and Tien, Nguyen Dang. 2017. "Bipolar neutrosophic soft sets and applications in decision making." Journal of Intelligent and Fuzzy Systems. 33 (6), pp. 4077-4087. https://doi.org/10.3233/JIFS-17999
Link prediction in co-authorship networks based on hybrid content similarity metric
Chuan, Pham Minh, Son, Le Hoang, Ali, Mumtaz, Khang, Tran Dinh, Huong, Le Thanh and Dey, Nilanjan. 2018. "Link prediction in co-authorship networks based on hybrid content similarity metric." Applied Intelligence. 48 (8), pp. 2470-2486. https://doi.org/10.1007/s10489-017-1086-x
A neutrosophic recommender system for medical diagnosis based on algebraic neutrosophic measures
Ali, Mumtaz, Son, Le Hoang, Thanh, Nguyen Dang and Minh, Nguyen Van. 2018. "A neutrosophic recommender system for medical diagnosis based on algebraic neutrosophic measures." Applied Soft Computing. 71, pp. 1054-1071. https://doi.org/10.1016/j.asoc.2017.10.012
Segmentation of dental X-ray images in medical imaging using neutrosophic orthogonal matrices
Ali, Mumtaz, Son, Le Hoang, Khan, Mohsin and Tung, Nguyen Thanh. 2017. "Segmentation of dental X-ray images in medical imaging using neutrosophic orthogonal matrices." Expert Systems with Applications. 91, pp. 434-441. https://doi.org/10.1016/j.eswa.2017.09.027
Interval Complex Neutrosophic Set: Formulation and Applications in Decision-Making
Ali, Mumtaz, Dat, Luu Quoc, Son, Le Hoang and Smarandache, Florentin. 2018. "Interval Complex Neutrosophic Set: Formulation and Applications in Decision-Making." International Journal of Fuzzy Systems. 20 (3), pp. 986-999. https://doi.org/10.1007/s40815-017-0380-4
δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis
Ngan, Roan Thi, Ali, Mumtaz and Son, Le Hoang. 2018. "δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis." Applied Intelligence. 48 (2), pp. 499-525. https://doi.org/10.1007/s10489-017-0986-0
A novel clustering algorithm in a neutrosophic recommender system for medical diagnosis
Thanh, Nguyen Dang, Ali, Mumtaz and Son, Le Hoang. 2017. "A novel clustering algorithm in a neutrosophic recommender system for medical diagnosis." Cognitive Computation. 9 (4), pp. 526-544. https://doi.org/10.1007/s12559-017-9462-8