2024年03月04日 13:37
一、基本情况
二、学术背景及工作经历
三、研究方向
四、担任课程
暂无
五、科研项目
(1)国家自然科学基金青年项目,New Methodology to Improve Streamflow Modeling Using Two-Phase Optimized Machine Learning And Deep Learning Methods,2024.01-2024.12,主持,在研;
(2)广东省基础与应用基础研究基金项目,基于集成全间隔多核学习的径流预测 方法研究,2023.01-2025.12,主持,在研;
(3)广州市博士后科研项目资助,机器学习和软计算方法在复杂系统建模中的应用,2022.01- 2024.12, 主持,
(4)广东省基础与应用基础研究基金项目,面向软件大数据的联邦深度预测模型与算法研究,2024.01-2026.12,主持,在研;
(5)广东省基础与应用基础研究基金项目,面向征信大数据的自适应多核学习及应用研究,2020.01-2022.12,参与人;
六、学术论文
Adnan, R. M., Khosravinia, P., Kisi, O., Nikpour, M. R., Dai, H. L., Osmani, M., & Ghazaei, S. A. (2024). Predicting discharge coefficient of weir–orifice in closed conduit using a neuro-fuzzy model improved by multi-phase PSOGSA. Applied Water Science, 14(3), 1-16. (JCR-Q1)
Adnan, R. M., Mostafa, R. R., Dai, H. L., Mansouri, E., Kisi, O., & Zounemat‐Kermani, M. (2024). Comparison of improved relevance vector machines for streamflow predictions. Journal of Forecasting, 43(1), 159-181. (JCR-Q2)
Adnan, R. M., Mirboluki, A., Mehraein, M., Malik, A., Heddam, S., & Kisi, O. (2024). Improved prediction of monthly streamflow in a mountainous region by Metaheuristic-Enhanced deep learning and machine learning models using hydroclimatic data. Theoretical and applied climatology, 155(1), 205-228. (JCR-Q2)
Sun, Y., Dai, H. L., Moayedi, H., Le, B. N., & Adnan, R. M. (2024). Predicting steady-state biogas production from waste using advanced machine learning-metaheuristic approaches. Fuel, 355, 129493. (JCR-Q1) Adnan, R. M., Mostafa, R. R., Dai, H. L., Heddam, S., Kuriqi, A., & Kisi, O. (2023). Pan evaporation estimation by relevance vector machine tuned with new metaheuristic algorithms using limited climatic data. Engineering Applications of Computational Fluid Mechanics, 17(1), 2192258. (JCR-1)
Adnan, R. M., Dai, H. L., Mostafa, R. R., Islam, A. R. M. T., Kisi, O., Heddam, S., & Zounemat-Kermani, M. (2023). Modelling groundwater level fluctuations by ELM merged advanced metaheuristic algorithms using hydroclimatic data. Geocarto International, 38(1), 2158951. (JCR-Q2)
Adnan, R. M., Dai, H. L., Kuriqi, A., Kisi, O., & Zounemat-Kermani, M. (2023). Improving drought modeling based on new heuristic machine learning methods. Ain Shams Engineering Journal, 14(10), 102168. (JCR-1)
Wang, M., Feng, S., Adnan, R. M.,, Chen, T., Sun, C., Chen, B., Rao, Q., Jin, H*. & Li, J. (2023). Assessing the Performance and Challenges of Low-Impact Development under Climate Change: A Bibliometric Review. Sustainability 15(18). (JCR-Q2)
Adnan, R. M., Dai, H. L., Kisi, O., Heddam, S., Kim, S., Kulls, C., & Zounemat-Kermani, M. (2023). Modelling biochemical oxygen demand using improved neuro-fuzzy approach by marine predators algorithm. Environmental Science and Pollution Research, 30(41), 94312-94333. (JCR-Q1)
Adnan, R. M., Mostafa, R. R., Dai, H. L., Heddam, S., Masood, A., & Kisi, O. (2023). Enhancing accuracy of extreme learning machine in predicting river flow using improved reptile search algorithm. Stochastic Environmental Research and Risk Assessment, 37(8), 3063-3083. (JCR-Q1)
Adnan, R. M., Cao, X., Parmar, K. S., Kisi, O., Shahid, S., & Zounemat-Kermani, M. (2023). Modeling Significant Wave Heights for Multiple Time Horizons Using Metaheuristic Regression Methods. Mathematics, 11(14), 3141. (JCR-Q1)
Adnan, R. M., Cao, X., Sadeghifar, T., Kuriqi, A., Kisi, O., & Shahid, S. (2023). Improving significant wave height prediction using a neuro-fuzzy approach and marine predators algorithm. Journal of Marine Science and Engineering, 11(6), 1163. (JCR-Q1)
Adnan, R. M., Khan, I., Moayedi, H., Ahmadi Dehrashid, A., Elkhrachy, I., & Nguyen Le, B. (2023). Novel evolutionary-optimized neural network for predicting landslide susceptibility. Environment, Development and Sustainability, 1-33.. (JCR-Q2)
Adnan, R. M., Dai, H. L., Mostafa, R. R., Islam, A. R. M. T., Kisi, O., Elbeltagi, A., & Zounemat-Kermani, M. (2023). Application of novel binary optimized machine learning models for monthly streamflow prediction. Applied Water Science, 13(5), 110. (JCR-Q2)
Adnan, R. M., Dehrashid, A. A., Zhang, B., Chen, Z., Le, B. N., & Moayedi, H. (2023). A novel swarm intelligence: cuckoo optimization algorithm (COA) and SailFish optimizer (SFO) in landslide susceptibility assessment. Stochastic Environmental Research and Risk Assessment, 37(5), 1717-1743. (JCR-1)
Adnan, R. M., Hazarika, B. B., Gupta, D., Heddam, S., & Kisi, O. (2023). Streamflow prediction in mountainous region using new machine learning and data preprocessing methods: a case study. Neural Computing and Applications, 35(12), 9053-9070. (JCR-Q1)
Adnan, R. M., Sadeghifar, T., Alizamir, M., Azad, M. T., Makarynskyy, O., Kisi, O., & Ahmed, K. O. (2023). Short-term probabilistic prediction of significant wave height using bayesian model averaging: Case study of chabahar port, Iran. Ocean Engineering, 272, 113887. (JCR-Q2)
Kisi, O., Parmar, K. S., Mahdavi-Meymand, A., Adnan, R. M., Shahid, S., & Zounemat-Kermani, M. (2023). Water quality prediction of the yamuna river in India using hybrid neuro-fuzzy models. Water, 15(6), 1095.. (JCR-Q1)
Adnan, R. M., Meshram, S. G., Mostafa, R. R., Islam, A. R. M. T., Abba, S. I., Andorful, F., & Chen, Z. (2023). Application of advanced optimized soft computing models for atmospheric variable forecasting. Mathematics, 11(5), 1213. (JCR-Q1, ESI高被引论文)
Adnan, R. M., Mostafa, R. R., Chen, Z., Parmar, K. S., Kisi, O., & Zounemat-Kermani, M. (2023). Water temperature prediction using improved deep learning methods through reptile search algorithm and weighted mean of vectors optimizer. Journal of Marine Science and Engineering, 11(2), 259. (JCR-Q1)
Mostafa, R. R., Kisi, O., Adnan, R. M., Sadeghifar, T., & Kuriqi, A. (2023). Modeling potential evapotranspiration by improved machine learning methods using limited climatic data. Water, 15(3), 486. (JCR-Q2)
Adnan, R. M., Khan, I., Moayedi, H., Foong, L. K., & Le, B. N. (2023). Teaching-learning-based strategy to retrofit neural computing toward pan evaporation analysis. Smart Structures and Systems, 32(1), 37-47. (JCR-Q1)
Keshtegar, B., Piri, J., Hussan, W. U., Adnan, R. M.,., Yaseen, M., Kisi, O., & Waseem, M. (2023). Prediction of sediment yields using a data-driven radial M5 tree model. Water, 15(7), 1437. (JCR-Q2)
Adnan, R. M., Mostafa, R. R., Chen, Z., Islam, A. R. M. T., Kisi, O., Kuriqi, A., & Zounemat-Kermani, M. (2022). Advanced hybrid metaheuristic machine learning models application for reference crop evapotranspiration prediction. Agronomy, 13(1), 98.. (JCR-Q1, ESI高被引论文)
Adnan, R. M., Dai, H. L., Al-Bahrani, M., & Mamlooki, M. (2022). Prediction of the FRP reinforced concrete beam shear capacity by using ELM-CRFOA. Measurement, 205, 112230. (JCR-Q1)
Adnan, R. M., Ewees, A. A., Parmar, K. S., Yaseen, Z. M., Shahid, S., & Kisi, O. (2022). The viability of extended marine predators algorithm-based artificial neural networks for streamflow prediction. Applied Soft Computing, 131, 109739. (JCR-Q1)
Adnan, R. M., Dai, H. L., Ewees, A. A., Shiri, J., Kisi, O., & Zounemat-Kermani, M. (2022). Application of improved version of multi verse optimizer algorithm for modeling solar radiation. Energy Reports, 8, 12063-12080. (JCR-Q2)
Adnan, R. M., Goliatt, L., Kisi, O., Trajkovic, S., & Shahid, S. (2022). Covariance matrix adaptation evolution strategy for improving machine learning approaches in streamflow prediction. Mathematics, 10(16), 2971. (JCR-Q1)
Adnan, R. M., Yaseen, Z. M., Heddam, S., Shahid, S., Sadeghi-Niaraki, A., & Kisi, O. (2022). Predictability performance enhancement for suspended sediment in rivers: Inspection of newly developed hybrid adaptive neuro-fuzzy system model. International Journal of Sediment Research, 37(3), 383-398. (JCR-Q2)
Kisi, O., Heddam, S., Keshtegar, B., Piri, J., & Adnan, R. M. (2022). Predicting daily streamflow in a cold climate using a novel data mining technique: Radial M5 Model Tree. Water, 14(9), 1449. (JCR-Q2)
Adnan, R. M., Mostafa, R. R., Elbeltagi, A., Yaseen, Z. M., Shahid, S., & Kisi, O. (2022). Development of new machine learning model for streamflow prediction: Case studies in Pakistan. Stochastic Environmental Research and Risk Assessment, 1-35. (JCR-Q1)
Adnan, R. M., Dai, H. L., Mostafa, R. R., Parmar, K. S., Heddam, S., & Kisi, O. (2022). Modeling multistep ahead dissolved oxygen concentration using improved support vector machines by a hybrid metaheuristic algorithm. Sustainability, 14(6), 3470. (JCR-Q2)
Adnan, R. M., Kisi, O., Mostafa, R. R., Ahmed, A. N., & El-Shafie, A. (2022). The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction. Hydrological Sciences Journal, 67(2), 161-174. (JCR-Q2)
Adnan, R. M., Jaafari, A., Milan, S. G., Kisi, O., Heddam, S., & Zounemat-Kermani, M. (2022). Hybridized adaptive neuro-fuzzy inference system with metaheuristic algorithms for modeling monthly pan evaporation. Water, 14(21), 3549. (JCR-Q2)
Adnan, R. M., Mostafa, R. R., Islam, A. R. M. T., Gorgij, A. D., Kuriqi, A., & Kisi, O. (2021). Improving drought modeling using hybrid random vector functional link methods. Water, 13(23), 3379. (JCR-Q2)
Adnan, R. M., Mostafa, R. R., Islam, A. R. M. T., Kisi, O., Kuriqi, A., & Heddam, S. (2021). Estimating reference evapotranspiration using hybrid adaptive fuzzy inferencing coupled with heuristic algorithms. Computers and Electronics in Agriculture, 191, 106541. (JCR-Q1)
Adnan, R. M., Mostafa, R. R., Kisi, O., Yaseen, Z. M., Shahid, S., & Zounemat-Kermani, M. (2021). Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization. Knowledge-Based Systems, 230, 107379.. (JCR-Q1, ESI高被引论文, 热点论文)
Adnan, R. M., Jaafari, A., Mohanavelu, A., Kisi, O., & Elbeltagi, A. (2021). Novel ensemble forecasting of streamflow using locally weighted learning algorithm. Sustainability, 13(11), 5877. (JCR-Q2)
Adnan, R. M., Parmar, K. S., Heddam, S., Shahid, S., & Kisi, O. (2021). Suspended sediment modeling using a heuristic regression method hybridized with kmeans clustering. Sustainability, 13(9), 4648.. (JCR-Q2
Adnan, R. M., Liang, Z., Parmar, K. S., Soni, K., & Kisi, O. (2021). Modeling monthly streamflow in mountainous basin by MARS, GMDH-NN and DENFIS using hydroclimatic data. Neural Computing and Applications, 33, 2853-2871. (JCR-Q2)
Adnan, R. M., Khosravinia, P., Karimi, B., & Kisi, O. (2021). Prediction of hydraulics performance in drain envelopes using Kmeans based multivariate adaptive regression spline. Applied Soft Computing, 100, 107008. (JCR-Q1)
Adnan, R. M., Petroselli, A., Heddam, S., Santos, C. A. G., & Kisi, O. (2021). Short term rainfall-runoff modelling using several machine learning methods and a conceptual event-based model. Stochastic Environmental Research and Risk Assessment, 35(3), 597-616. (JCR-Q1)
Adnan, R. M., Petroselli, A., Heddam, S., Santos, C. A. G., & Kisi, O. (2021). Comparison of different methodologies for rainfall–runoff modeling: machine learning vs conceptual approach. Natural Hazards, 105, 2987-3011.. (JCR-Q2)
Adnan, R. M., Petroselli, A., Heddam, S., Santos, C. A. G., & Kisi, O. (2021). Comparison of different methodologies for rainfall–runoff modeling: machine learning vs conceptual approach. Natural Hazards, 105, 2987-3011.. (JCR-Q1)
Adnan, R. M., Heddam, S., Yaseen, Z. M., Shahid, S., Kisi, O., & Li, B. (2020). Prediction of potential evapotranspiration using temperature-based heuristic approaches. Sustainability, 13(1), 297.. (JCR-Q2)
Adnan, R. M., Liang, Z., & Kisi, O. (2020). Comments on “Predicting permeability changes with injecting CO2 in coal seams during CO2 geological sequestration: A comparative study among six SVM-based hybrid models” Science of the Total Environment, 705, 135941 (2020). Science of The Total Environment, 744, 139486.. (JCR-Q1)
Adnan, R. M., Liang, Z., Heddam, S., Zounemat-Kermani, M., Kisi, O., & Li, B. (2020). Least square support vector machine and multivariate adaptive regression splines for streamflow prediction in mountainous basin using hydro-meteorological data as inputs. Journal of Hydrology, 586, 124371.. (JCR-Q1)
Alizamir, M., Kisi, O., Adnan, R. M., & Kuriqi, A. (2020). Modelling reference evapotranspiration by combining neuro-fuzzy and evolutionary strategies. Acta Geophysica, 68, 1113-1126.. (JCR-Q2)
Adnan, R. M., Chen, Z., Yuan, X., Kisi, O., El-Shafie, A., Kuriqi, A., & Ikram, M. (2020). Reference evapotranspiration modeling using new heuristic methods. Entropy, 22(5), 547.. (JCR-Q2)
Bayatvarkeshi, M., Zhang, B., Fasihi, R., Adnan, R. M., Kisi, O., & Yuan, X. (2020). Investigation into the effects of climate change on reference evapotranspiration using the HadCM3 and LARS-WG. Water, 12(3), 666.. (JCR-Q2)
Adnan, R. M., Liang, Z., El-Shafie, A., Zounemat-Kermani, M., & Kisi, O. (2019). Prediction of suspended sediment load using data-driven models. Water, 11(10), 2060.. (JCR-Q2)
Adnan, R. M., Malik, A., Kumar, A., Parmar, K. S., & Kisi, O. (2019). Pan evaporation modeling by three different neuro-fuzzy intelligent systems using climatic inputs. Arabian Journal of Geosciences, 12, 1-14. (JCR-Q3)
Adnan, R. M., Liang, Z., El-Shafie, A., Zounemat-Kermani, M., & Kisi, O. (2019). Prediction of suspended sediment load using data-driven models. Water, 11(10), 2060.. (JCR-Q2)
Adnan, R. M., Liang, Z., Trajkovic, S., Zounemat-Kermani, M., Li, B., & Kisi, O. (2019). Daily streamflow prediction using optimally pruned extreme learning machine. Journal of Hydrology, 577, 123981. (JCR-Q1)
Adnan, R. M., Yuan, X., Kisi, O., Yuan, Y., Tayyab, M., & Lei, X. (2019, June). Application of soft computing models in streamflow forecasting. In Proceedings of the institution of civil engineers-water management (Vol. 172, No. 3, pp. 123-134). Thomas Telford Ltd. (JCR-Q3)
Adnan, R. M., Liang, Z., Yuan, X., Kisi, O., Akhlaq, M., & Li, B. (2019). Comparison of LSSVR, M5RT, NF-GP, and NF-SC models for predictions of hourly wind speed and wind power based on cross-validation. Energies, 12(2), 329. (JCR-Q2)
Adnan, R. M., Yuan, X., Kisi, O., Adnan, M., & Mehmood, A. (2018). Stream flow forecasting of poorly gauged mountainous watershed by least square support vector machine, fuzzy genetic algorithm and M5 model tree using climatic data from nearby station. Water Resources Management, 32, 4469-4486. (JCR-Q2)
Yuan, X., Chen, C., Lei, X., Yuan, Y., & Adnan, R. M., (2018). Monthly runoff forecasting based on LSTM–ALO model. Stochastic environmental research and risk assessment, 32, 2199-2212. (JCR-Q1)
Adnan, M., Nabi, G., Kang, S., Zhang, G., Adnan, R. M., Anjum, M. N., & Ali, A. F. (2017). Snowmelt Runoff Modelling under Projected Climate Change Patterns in the Gilgit River Basin of Northern Pakistan. Polish Journal of Environmental Studies, 26(2). (JCR-Q2)
Adnan, R. M., Yuan, X., Kisi, O., & Anam, R. (2017). Improving accuracy of river flow forecasting using LSSVR with gravitational search algorithm. Advances in Meteorology, 2017. (JCR-Q2)
七、主要获奖
2024.03,Hydrological Science Journal Reviewer Award 2024。
2023.10,Top 2% Scientist Award list issued by Stanford University。
2021.09,Best Researcher Award, 农业大学巴基斯坦。
2018.06,Best Research Paper Award, 农业大学巴基斯坦。
2017.06,Honorary Award Certificate On PhD Research, 华中科技大学。
2013.07,PhD Overseas HEC Scholarship Award, HEC巴基斯坦。
八、联系邮箱
rana@gzhu.edu.cn
(更新于2024年4月)