Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning–based gamma test variable selection and empirical wavelet transform

Article

Heddam, Salim, Yaseen, Zaher Mundher, Falah, Mayadah W., Goliatt, Leonardo, Tan, Mou Leong, Sa’adi, Zulfaqar, Ahmadianfar, Iman, Saggi, Mandeep, Bhatia, Amandeep and Samui, Pijush. 2022. "Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning–based gamma test variable selection and empirical wavelet transform." Environmental Science and Pollution Research. 29 (51), pp. 77157-77187. https://doi.org/10.1007/s11356-022-21201-1
Article Title

Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning–based gamma test variable selection and empirical wavelet transform

ERA Journal ID5827
Article CategoryArticle
AuthorsHeddam, Salim, Yaseen, Zaher Mundher, Falah, Mayadah W., Goliatt, Leonardo, Tan, Mou Leong, Sa’adi, Zulfaqar, Ahmadianfar, Iman, Saggi, Mandeep, Bhatia, Amandeep and Samui, Pijush
Journal TitleEnvironmental Science and Pollution Research
Journal Citation29 (51), pp. 77157-77187
Number of Pages31
Year2022
PublisherSpringer
Place of PublicationGermany
ISSN0944-1344
1614-7499
Digital Object Identifier (DOI)https://doi.org/10.1007/s11356-022-21201-1
Web Address (URL)https://link.springer.com/article/10.1007/s11356-022-21201-1
Abstract

This study aims to evaluate the usefulness and effectiveness of four machine learning (ML) models for modelling cyanobacteria blue-green algae (CBGA) at two rivers located in the USA. The proposed modelling framework was based on establishing a link between five water quality variables and the concentration of CBGA. For this purpose, artificial neural network (ANN), extreme learning machine (ELM), random forest regression (RFR), and random vector functional link (RVFL) are developed. First, the four models were developed using only water quality variables. Second, based on the results of the first, a new modelling strategy was introduced based on preprocessing signal decomposition. Hence, the empirical mode decomposition (EMD), the variational mode decomposition (VMD), and the empirical wavelet transform (EWT) were used for decomposing the water quality variables into several subcomponents, and the obtained intrinsic mode functions (IMFs) and multiresolution analysis (MRA) components were used as new input variables for the ML models. Results of the present investigation show that (i) using single models, good predictive accuracy was obtained using the RFR model exhibiting an R and NSE values of ≈0.914 and ≈0.833 for the first station, and ≈0.944 and ≈0.884 for the second station, while the others models, i.e., ANN, RVFL, and ELM, have failed to provide a good estimation of the CBGA; (ii) the decomposition methods have contributed to a significant improvement of the individual models performances; (iii) among the thee decomposition methods, the EMD was found to be superior to the VMD and EWT; and (iv) the ANN and RFR were found to be more accurate compared to the ELM and RVFL models, exhibiting high numerical performances with R and NSE values of approximately ≈0.983, ≈0.967, and ≈0.989 and ≈0.976, respectively.

KeywordsModelling ; CBGA ; Water quality; ELM ; ANN ; RVFL ; RFR ; EMD ; VMD ; EWT
Public Notes

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Byline AffiliationsUniversity of 20 August 1955 of Skikda, Algeria
School of Mathematics, Physics and Computing
National University of Malaysia
Al-Ayen University, Iraq
Al-Mustaqbal University College, Iraq
Behbahan Khatam Alanbia University of Technology, Iran
University of Science, Malaysia
University of Technology Malaysia, Malaysia
Thapar Institute of Engineering and Technology, India
Thapar University, India
National Institute of Technology Patna, India
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Temperature and precipitation trend analysis of the Iraq Region under SRES scenarios during the twenty-first century
Hashim, Bassim Mohammed, Maliki, Ali Al, Alraheem, Esam Abd, Al-Janabi, Ahmed Mohammed Sami, Halder, Bijay and Yaseen, Zaher Mundher. 2022. "Temperature and precipitation trend analysis of the Iraq Region under SRES scenarios during the twenty-first century." Theoretical and Applied Climatology. 148 (3-4), pp. 881-898. https://doi.org/10.1007/s00704-022-03976-y
Delineation of urban expansion and drought-prone areas using vegetation conditions and other geospatial indices
Halder, Bijay, Tiyasha, Tiyasha, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2022. "Delineation of urban expansion and drought-prone areas using vegetation conditions and other geospatial indices." Theoretical and Applied Climatology. 149 (3-4), pp. 1277-1295. https://doi.org/10.1007/s00704-022-04108-2
Investigating the relationship between land alteration and the urban heat island of Seville city using multi-temporal Landsat data
Halder, Bijay, Karimi, Alireza, Mohammad, Pir, Bandyopadhyay, Jatisankar, Brown, Robert D. and Yaseen, Zaher Mundher. 2022. "Investigating the relationship between land alteration and the urban heat island of Seville city using multi-temporal Landsat data." Theoretical and Applied Climatology. 150 (1-2), pp. 613-635. https://doi.org/10.1007/s00704-022-04180-8
The impact of climate change on land degradation along with shoreline migration in Ghoramara Island, India
Halder, Bijay, Ameen, Ameen Mohammed Salih, Bandyopadhyay, Jatisankar, Khedher, Khaled Mohamed and Yaseen, Zaher Mundher. 2022. "The impact of climate change on land degradation along with shoreline migration in Ghoramara Island, India." Physics and Chemistry of the Earth. 126. https://doi.org/10.1016/j.pce.2022.103135
Grasshopper Optimization Algorithm with Crossover Operators for Feature Selection and Solving Engineering Problems
Ewees, Ahmed A., Gaheen, Marwa A., Yaseen, Zaher Mundher Yaseen and Ghoniem, Rania M.. 2022. "Grasshopper Optimization Algorithm with Crossover Operators for Feature Selection and Solving Engineering Problems." IEEE Access. 10, pp. 23304-23320. https://doi.org/10.1109/ACCESS.2022.3153038
Application of the ANOVA method in the optimization of a thermoelectric cooler-based dehumidification system
Eltaweel, Mahmoud, Heggy, Aya H., Yaseen, Zaher Mundher, Alawi, Omer A., Falah, Mayadah W., Hussein, Omar A., Ahmed, Waqar, Homod, Raad Z. and Abdelrazek, Ali H.. 2022. "Application of the ANOVA method in the optimization of a thermoelectric cooler-based dehumidification system." Energy Reports. 8, pp. 10533-10545. https://doi.org/10.1016/j.egyr.2022.08.193
Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt
Elmetwalli, Adel H., Mazrou, Yasser S. A., Tyler, Andrew N., Hunter, Peter D., Elsherbiny, Osama, Yaseen, Zaher Mundher and Elsayed, Salah. 2022. "Assessing the Efficiency of Remote Sensing and Machine Learning Algorithms to Quantify Wheat Characteristics in the Nile Delta Region of Egypt." Agriculture. 12 (3). https://doi.org/10.3390/agriculture12030332
Households’ perceptions and socio-economic determinants of climate change awareness: Evidence from Selangor Coast Malaysia
Ehsan, Sofia, Begum, Rawshan Ara, Maulud, Khairul Nizam Abdul and Yaseen, Zaher Mundher. 2022. "Households’ perceptions and socio-economic determinants of climate change awareness: Evidence from Selangor Coast Malaysia." Journal of Environmental Management. 316. https://doi.org/10.1016/j.jenvman.2022.115261
Surface water sodium (Na+) concentration prediction using hybrid weighted exponential regression model with gradient-based optimization
Ahmadianfar, Iman, Shirvani-Hosseini, Seyedehelham, Samadi-Koucheksaraee, Arvin and Yaseen, Zaher Mundher. 2022. "Surface water sodium (Na+) concentration prediction using hybrid weighted exponential regression model with gradient-based optimization." Environmental Science and Pollution Research. 29 (35), pp. 53456-53481. https://doi.org/10.1007/s11356-022-19300-0
An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction
Ahmadianfar, Iman, Shirvani-Hosseini, Seyedehelham, He, Jianxun He, Samadi-Koucheksaraee, Arvin and Yaseen, Zaher Mundher. 2022. "An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction." Scientific Reports. 12 (1). https://doi.org/10.1038/s41598-022-08875-w
Thermal and Hydraulic Performances of Carbon and Metallic Oxides-Based Nanomaterials
Afan, Haitham Abdulmohsin, Aldlemy, Mohammed Suleman, Ahmed, Ali M., Jawad, Ali H., Naser, Maryam H., Homod, Raad Z., Mussa, Zainab Haider, Abdulkadhim, Adnan Hashim, Scholz, Miklas and Yaseen, Zaher Mundher. 2022. "Thermal and Hydraulic Performances of Carbon and Metallic Oxides-Based Nanomaterials." Nanomaterials. 12 (9). https://doi.org/10.3390/nano12091545
Different TiO2 Phases (Degussa/Anatase) Modified Cross-Linked Chitosan Composite for the Removal of Reactive Red 4 Dye: Box–Behnken Design
Abdulhameed, Ahmed Saud, Jawad, Ali H., Vigneshwaran, Sivakumar, ALOthman, Zeid A. and Yaseen, Zaher Mundher Yaseen. 2022. "Different TiO2 Phases (Degussa/Anatase) Modified Cross-Linked Chitosan Composite for the Removal of Reactive Red 4 Dye: Box–Behnken Design." Journal of Polymers and the Environment. 30 (12), pp. 5084-5099. https://doi.org/10.1007/s10924-022-02568-1
Chitosan/Carbon-Doped TiO2 Composite for Adsorption of Two Anionic Dyes in Solution and Gaseous SO2 Capture: Experimental Modeling and Optimization
Abdulhameed, Ahmed Saud, Jawad, Ali H., Ridwan, Muhammad, Khadiran, Tumirah, Wilson, Lee D. and Yaseen, Zaher Mundher. 2022. "Chitosan/Carbon-Doped TiO2 Composite for Adsorption of Two Anionic Dyes in Solution and Gaseous SO2 Capture: Experimental Modeling and Optimization." Journal of Polymers and the Environment. 30 (11), pp. 4619-4636. https://doi.org/10.1007/s10924-022-02532-z
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
Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions
Tao, Hai, Al-Khafaji, Zainab S., Qi, Chongchong, Zounemat-Kermani, Mohammad, Kisi, Ozgur, Tiyasha, Tiyasha, Chau, Kwok-Wing, Nourani, Vahid, Melesse, Assefa M., Elhakeem, Mohamed, Farooque, Aitazaz Ahsan, Nejadhashemi, A. Pouyan, Khedher, Khaled Mohamed, Alawi, Omer A., Deo, Ravinesh C., Shahid, Shamsuddin, Singh, Vijay P. and Yaseen, Zaher Mundher. 2021. "Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions." Engineering Applications of Computational Fluid Mechanics. 15 (1), pp. 1585-1612. https://doi.org/10.1080/19942060.2021.1984992
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
Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks
Ghimire, Sujan, Yaseen, Zaher Mundher, Farooque, Aitazaz A., Deo, Ravinesh C., Zhang, Ji and Tao, Xiaohui. 2021. "Streamflow prediction using an integrated methodology based on convolutional neural network and long short‑term memory networks." Scientific Reports. 11, pp. 1-26. https://doi.org/10.1038/s41598-021-96751-4
Climatology of Borneo vortices in the HadGEM3-GC3.1 General Circulation Model
Liang, Ju, Catto, Jennifer L., Hawcroft, Matthew, Hodges, Kevin I., Tan, Mou Leong and Haywood, James M.. 2021. "Climatology of Borneo vortices in the HadGEM3-GC3.1 General Circulation Model." Journal of Climate. 34 (9), pp. 3401-3419. https://doi.org/10.1175/JCLI-D-20-0604.1
Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models
Bayatvarkeshi, Maryam, Bhagat, Suraj Kumar, Mohammadi, Kourosh, Kisi, Ozgur, Farahani, M., Hasani, A., Deo, Ravinesh and Yaseen, Zaher Mundher. 2021. "Modeling soil temperature using air temperature features in diverse climatic conditions with complementary machine learning models." Computers and Electronics in Agriculture. 185. https://doi.org/10.1016/j.compag.2021.106158
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
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
Hybrid multilayer perceptron-firefly optimizer algorithm for modelling photosynthetic active solar radiation for biofuel energy exploration
Goundar, Harshna, Yaseen, Zaher Mundher and Deo, Ravinesh. 2021. "Hybrid multilayer perceptron-firefly optimizer algorithm for modelling photosynthetic active solar radiation for biofuel energy exploration." Deo, Ravinesh, Samui, Pijush and Roy, Sanjiban Sekhar (ed.) Predictive modelling for energy management and power systems engineering. Amsterdam, Netherlands. Elsevier. pp. 191-232
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
Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation
Deo, Ravinesh C., Samui, Pijush, Kisi, Ozgur and Yaseen, Zaher Mundher. 2021. Intelligent data analytics for decision-support systems in hazard mitigation: theory and practice of hazard mitigation. Singapore. Springer.
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
Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments
Salih, Sinan Q., Sharafati, Ahmad, Ebtehaj, Isa, Sanikhani, Hadi, Siddique, Ridwan, Deo, Ravinesh C., Bonakdari, Hossein, Shahid, Shamsuddin and Yaseen, Zaher Mundher. 2020. "Integrative stochastic model standardization with genetic algorithm for rainfall pattern forecasting in tropical and semi-arid environments." Hydrological Sciences Journal. 65 (7), pp. 1145-1157. https://doi.org/10.1080/02626667.2020.1734813
Global solar radiation estimation and climatic variability analysis using extreme learning machine based predictive model
Tao, Hai, Sharafati, Ahmad, Mohammed, Achite, Salih, Sinan Q., Deo, Ravinesh C., Al-Ansari, Nadhir and Yaseen, Zaher Mundher. 2020. "Global solar radiation estimation and climatic variability analysis using extreme learning machine based predictive model." IEEE Access. 8, pp. 12026-12042. https://doi.org/10.1109/ACCESS.2020.2965303
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
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
Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses
Deo, Ravinesh C., Yaseen, Zaher Mundher, Al-Ansari, Nadhir, Nguyen-Huy, Thong, Langlands, Trevor and Galligan, Linda. 2020. "Modern artificial intelligence model development for undergraduate student performance prediction: an investigation on engineering mathematics courses." IEEE Access. 8, pp. 136697-136724. https://doi.org/10.1109/ACCESS.2020.3010938
Designing a new data intelligence model for global solar radiation prediction: application of multivariate modeling scheme
Tao, Hai, Ebtehaj, Isa, Bonakdari, Hossein, Heddam, Salim, Voyant, Cyril, Al-Ansari, Nadhir, Deo, Ravinesh and Yaseen, Zaheer Mundher. 2019. "Designing a new data intelligence model for global solar radiation prediction: application of multivariate modeling scheme." Energies. 12 (7), pp. 1-24. https://doi.org/10.3390/en12071365
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/10.1080/02626667.2019.1632460
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.6037
An enhanced extreme learning machine model for river flow forecasting: state-of-the-art, practical applications in water resource engineering area and future research direction
Yaseen, Zaher Mundher, Sulaiman, Sadeq Oleiwi, Deo, Ravinesh C. and Chau, Kwok-Wing. 2019. "An enhanced extreme learning machine model for river flow forecasting: state-of-the-art, practical applications in water resource engineering area and future research direction." Journal of Hydrology. 569, pp. 387-408. https://doi.org/10.1016/j.jhydrol.2018.11.069
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
Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: a new approach
Yaseen, Zaheer Munder, Tran, Minh Tung, Kim, Sungwon, Bakhshpoori, Taha and Deo, Ravinesh C.. 2018. "Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: a new approach." Engineering Structures. 177, pp. 244-255. https://doi.org/10.1016/j.engstruct.2018.09.074
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. 121-139
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.2018.07.008
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.2018.05.030
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/s11269-018-1909-5
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/s00477-017-1474-0
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/s00704-017-2244-0
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.1943-5584.0001506
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.2017.09.004
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.2017.09.007
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/s11269-017-1797-0
Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
Yaseen, Zaher Mundher, Jaafar, Othman, Deo, Ravinesh C., Kisi, Ozgur, Adamowski, Jan, Quilty, John and El-Shafie, Ahmed. 2016. "Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq." Journal of Hydrology. 542, pp. 603-614. https://doi.org/10.1016/j.jhydrol.2016.09.035
Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models
Deo, Ravinesh C., Samui, Pijush and Kim, Dookie. 2016. "Estimation of monthly evaporative loss using relevance vector machine, extreme learning machine and multivariate adaptive regression spline models." Stochastic Environmental Research and Risk Assessment. 30 (6), pp. 1769-1784. https://doi.org/10.1007/s00477-015-1153-y