Ahadiyan J., Kiani S., Asiaban P., Azizi Nadian H., Omidvarinia M. (2023). 'Optimizing the dimensions of the agricultural water transfer system from the Karun 3 dam to the northeastern cities of Khuzestan province', Journal of New Approaches in Water Engineering and Environment, 1(2), pp. 112-126. doi: 10.22034/nawee.2023.367835.1030.
Alizadeh, M., Alizadeh, E., Asadollahpour Kotenaee, S., Shahabi, H., Beiranvand Pour, A., Panahi, M., Bin Ahmad, B., Saro, L., 2018. Social vulnerability assessment using artificial neural network (ANN) model for earthquake hazard in Tabriz city, Iran. Sustainability 10 (10), 3376.
Azareh, A., Rahmati, O., Rafiei-Sardooi, E., Sankey, J.B., Lee, S., Shahabi, H., Ahmad, B.B., 2019. Modelling gully-erosion susceptibility in a semi-arid region, Iran: Investigation of applicability of certainty factor and maximum entropy models. Sci. Total Environ. 655, 684–696.
Bui, D.T., Hoang, N.-D., Martínez-Álvarez, F., Ngo, P.-T.T., Hoa, P.V., Pham, T.D., Samui, P., Costache, R., 2019a. A novel deep learning neural network approach for predicting flash flood susceptibility: a case study at a high frequency tropical storm area. Sci. Total Environ. 701, 134413.
Bui, D.T., Moayedi, H., Gör, M., Jaafari, A., Foong, L.K., 2019b. Predicting slope stability failure through machine learning paradigms. ISPRS Int. J. Geo-Inform. 8 (9), 395.
Bui, D.T., Ngo, P.-T.T., Pham, T.D., Jaafari, A., Minh, N.Q., Hoa, P.V., Samui, P., 2019c. A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility mapping. Catena 179, 184–196
Bui, D.T., Panahi, M., Shahabi, H., Singh, V.P., Shirzadi, A., Chapi, K., Khosravi, K., Chen, W., Panahi, S., Li, S., 2018a. Novel hybrid evolutionary algorithms for spatial prediction of floods. Sci. Rep. 8 (1), 15364.
Bui, D.T., Shahabi, H., Shirzadi, A., Chapi, K., Pradhan, B., Chen, W., Khosravi, K., Panahi, M., Ahmad, B.B., Saro, L., 2018b. Land subsidence susceptibility mapping in South Korea using machine learning algorithms. Sensors. 18 (8), 2464.
Chen, W., Hong, H., Panahi, M., Shahabi, H., Wang, Y., Shirzadi, A., Pirasteh, S., Alesheikh, A.A., Khosravi, K., Panahi, S., 2019a. Spatial prediction of landslide susceptibility using GIS-based data mining techniques of ANFIS with whale optimization algorithm (WOA) and grey wolf optimizer (GWO). Appl. Sci. 9 (18), 3755.
Chen, W., Panahi, M., Tsangaratos, P., Shahabi, H., Ilia, I., Panahi, S., Li, S., Jaafari, A., Ahmad, B.B., 2019b. Applying population-based evolutionary algorithms and a neuro-fuzzy system for modeling landslide susceptibility. Catena 172, 212–231
Convertino, M., Annis, A., Nardi, F., 2019. Information-theoretic portfolio decision model for optimal flood management. Environ. Model Softw. 119, 258–274
Ebrahim Sharififard, Mohamad Azizipour, Javad Ahadiyan, Ali Haghighi; Determination of creep function coefficients of viscoelastic pipes using a transient-guided machine learning model. AQUA - Water Infrastructure, Ecosystems and Society 1 November 2024; 73 (11): 2132–2149. doi: https://doi.org/10.2166/aqua.2024.091.
Haynes, K., Coates, L., Van Den Honert, R., Gissing, A., Bird, D., Dimer De Oliveira, F., D’arcy, R., Smith, C., Radford, D., 2017. Exploring the circumstances surrounding flood fatalities in Australia—1900–2015 and the implications for policy and practice. Environ. Sci. Pol. 76, 165–176.
Jaafari, A., Gholami, D.M., Zenner, E.K., 2017. A Bayesian modeling of wildfire probability in the Zagros mountains, Iran. Ecol. Inform. 39, 32–44.
Jaafari, A., Najafi, A., Melón, M.G., 2015a. Decision-making for the selection of a best wood extraction method: an analytic network process approach. Forest Pol. Econ. 50, 200–209.
Jaafari, A., Najafi, A., Rezaeian, J., Sattarian, A., 2015b. Modeling erosion and sediment delivery from unpaved roads in the north mountainous forest of Iran. GEM – Int. J. Geomathematics. 6 (2), 343–356.
Jaafari, A., Panahi, M., Pham, B.T., Shahabi, H., Bui, D.T., Rezaie, F., Lee, S., 2019a. Meta optimization of an adaptive neuro-fuzzy inference system with grey wolf optimizer and biogeography-based optimization algorithms for spatial prediction of landslide susceptibility. Catena. 175, 430–445.
Jaafari, A., Razavi Termeh, S.V., Bui, D.T., 2019b. Genetic and firefly metaheuristic algorithms for an optimized neuro-fuzzy prediction modeling of wildfire probability. J. Environ. Manag. 243, 358–369.
Jaafari, A., Zenner, E.K., Panahi, M., Shahabi, H., 2019c. Hybrid artificial intelligence models based on a neuro-fuzzy system and metaheuristic optimization algorithms for spatial prediction of wildfire probability. Agric. For. Meteorol. 266, 198–207.
Jamali, B., Bach, P.M., Deletic, A., 2020. Rainwater harvesting for urban flood management – an integrated modelling framework. Water Res. 171, 115372.
Janizadeh, S., Avand, M., Jaafari, A., Phong, T.V., Bayat, M., Ahmadisharaf, E., Prakash, I., Pham, B.T., Lee, S., 2019. Prediction success of machine learning methods for flash flood susceptibility mapping in the Tafresh watershed, Iran. Sustainability 11 (19), 5426.
Khosravi, K., Pham, B.T., Chapi, K., Shirzadi, A., Shahabi, H., Revhaug, I., Prakash, I., Bui, D.T., 2018. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. Sci. Total Environ. 627, 744–755.
Khosravi, K., Shahabi, H., Pham, B.T., Adamowski, J., Shirzadi, A., Pradhan, B., Dou, J., Ly, H.B., Gróf, G., Ho, H.L., Hong, H., Chapi, K., Prakash, I., 2019. A comparative assessment of flood susceptibility modeling using multi-criteria decision-making analysis and machine learning methods. J. Hydrol. 573, 311–323.
Kianfard, M., Ahadiyan, J. (2016). 'Optimization of under pressure water supply network with transient flow using linear programming method', Iranian Water Researches Journal, 10(2), pp. 37-46. https://iwrj.sku.ac.ir/article_10477.html?lang=en.
Kumar, V., Kumar, R., Singh, J. and Kumar, P. (2019) Contaminants in Agriculture and Environment: Health Risks and Remediation. Agriculture and Environmental Science, India. https://doi.org/10.26832/AESA-2019-CAE
Lee, S., Oh, H.J., 2019. Landslide susceptibility prediction using evidential belief function, weight of evidence and artificial neural network models (Korean Journal of Remote Sensing). 35 (2), 299–316
Lennart Schmidt, Falk Heße, Sabine Attinger, Rohini Kumar, 2020, Challenges in Applying Machine Learning Models for Hydrological Inference: A Case Study for Flooding Events Across Germany,Water Resourse Researche, Volume56, Issue5,First published: 23 April 2020 https://doi.org/10.1029/2019WR025924
Olah C (2015) Understanding LSTM Networks.
Rahmati, O., Panahi, M., Kalantari, Z., Soltani, E., Falah, F., Dayal, K.S., Mohammadi, F., Deo, R.C., Tiefenbacher, J., Tien Bui, D., 2019. Capability and robustness of novel hybridized models used for drought hazard modeling in Southeast Queensland, Australia. Sci. Total Environ. 718, 134656
Sajjadi, S.M.; Barihi, S.; Ahadiyan, J.; Azizi Nadian, H.; Valipour, M.; Bahmanpouri, F.; Khedri, P. Redesigning the Fuse Plug, Emergency Spillway, and Flood Warning System: An Application of Flood Management. Water 2024, 16, 3694. https://doi.org/10.3390/w16243694.