R. Khatibi

发表

ACTIF best practice – Understanding and reducing uncertainty in flood forecasting

R. Khatibi, E. Todini, M. Butts, 2005 .

Groundwater Remediation through Pump-Treat-Inject Technology Using Optimum Control by Artificial Intelligence (OCAI)

Y. Hassanzadeh, R. Khatibi, S. Sadeghfam, 2019, Water Resources Management.

Inter-comparison of time series models of lake levels predicted by several modeling strategies

M. Ghorbani, R. Khatibi, V. Jothiprakash, 2014 .

Relative importance of parameters affecting wind speed prediction using artificial neural networks

M. Ghorbani, M. Bilgili, R. Khatibi, 2013, Theoretical and Applied Climatology.

Modeling river discharge time series using support vector machine and artificial neural networks

Mohammad Ali Ghorbani, Rahman Khatibi, Arun Goel, 2016, Environmental Earth Sciences.

A study of friction factor formulation in pipes using artificial intelligence techniques and explicit equations

Mohammad Ali Ghorbani, Rahman Khatibi, Farzin Salmasi, 2012 .

BEST PRACTICE PAPER – UNDERSTANDING AND REDUCING UNCERTAINTY IN FLOOD FORECASTING

P. Samuels, E. Todini, A. Weerts, 2006 .

Identification Problem of Open-Channel Friction Parameters

Rahman Khatibi, Peter R. Wormleaton, P. R. Wormleaton, 1997 .

An investigation into seasonal variations of groundwater nitrate by spatial modelling strategies at two levels by kriging and co-kriging models.

B. Pradhan, R. Khatibi, V. Karimi, 2020, Journal of environmental management.

A study of subsidence hotspots by mapping vulnerability indices through innovatory ‘ALPRIFT’ using artificial intelligence at two levels

B. Feizizadeh, R. Khatibi, A. Nadiri, 2020, Bulletin of Engineering Geology and the Environment.

AM Parsimonious Catchment and River Flow Modelling

M. J. Booij, G. Boyce, R. Khatibi, 2018 .

Introducing a new framework for mapping subsidence vulnerability indices (SVIs): ALPRIFT.

R. Khatibi, A. Nadiri, Ghodrat Barzegari, 2018, The Science of the total environment.

Investigating reduction of uplift forces by longitudinal drains with underlined canals

R. Khatibi, F. Salmasi, B. Nourani, 2018 .

Forced Hydraulic Jumps Described by Classic Hydraulic Equations Reproducing Cusp Catastrophe Features

M. Ghorbani, Y. Hassanzadeh, R. Khatibi, 2017 .

The problem of identifying arsenic anomalies in the basin of Sahand dam through risk-based 'soft modelling'.

R. Khatibi, A. Nadiri, A. Asghari Moghaddam, 2018, The Science of the total environment.

Evolutionary systemic modelling of practices on flood risk

Rahman Khatibi, R. Khatibi, 2011 .

A study of land subsidence problems by ALPRIFT for vulnerability indexing and risk indexing and treating subjectivity by strategy at two levels

R. Khatibi, S. Sadeghfam, R. Daneshfaraz, 2020 .

Systemic nature of, and diversification in systems exposed to, flood risk

R. Khatibi, 2008 .

The role of flood forecasting and warning in sustainability of flood defence

J. Haywood, R. Khatibi, 2002 .

Investigating meteorological/groundwater droughts by copula to study anthropogenic impacts

R. Khatibi, R. Mirabbasi, S. Sadeghfam, 2022, Scientific Reports.

Heuristic Contextualisation of Arithmetic Calculus by a New Network Based on the Difference Table

R. Khatibi, 2017 .

Introducing "Arithmetic Calculus" with Some Applications: New Terms, Definitions, Notations and Operators

R. Khatibi, 2014 .

Evolutionary transitions in data science by Generalised Theory of Evolution and Arithmetic Calculus

R. Khatibi, 2018 .

MUTUAL INCLUSION IN FLOOD FORECASTING

R. Khatibi, 2005 .

Formulating a strategy to combine artificial intelligence models using Bayesian model averaging to study a distressed aquifer with sparse data availability

Rahman Khatibi, Yousef Hassanzadeh, Sina Sadeghfam, 2019, Journal of Hydrology.

Prediction of Spatial Fluoride Concentrations by a Hybrid Artificial Neural Network in Complex Aquifers

F. Tsai, R. Khatibi, A. Nadiri, 2019, GIS and Geostatistical Techniques for Groundwater Science.

A study of health risk from accumulation of metals in commercial edible fish species at Tuticorin coasts of southern India

R. Khatibi, S. Chung, A. Nadiri, 2020 .

Systemic knowledge management in hydraulic systems: I. A postulate on paradigm shifts as a methodological tool

Rahman H. Khatibi, R. Khatibi, 2003 .

Strategies for Learning Groundwater Potential Modelling Indices under Sparse Data with Supervised and Unsupervised Techniques

R. Khatibi, D. Tien Bui, V. Karimi, 2020, Water Resources Management.

Mapping groundwater potential field using catastrophe fuzzy membership functions and Jenks optimization method: a case study of Maragheh-Bonab plain, Iran

Rahman Khatibi, Yousef Hassanzadeh, Sina Sadeghfam, 2016, Environmental Earth Sciences.

Chaos-based multigene genetic programming: A new hybrid strategy for river flow forecasting

Mohammad Ali Ghorbani, Rahman Khatibi, Ali Danandeh Mehr, 2018, Journal of Hydrology.

Inter-Comparison of an Evolutionary Programming Model of Suspended Sediment Time-Series with Other Local Models

Mohammad Ali Ghorbani, Rahman Khatibi, Hakimeh Asadi, 2012 .

Investigating chaos in river stage and discharge time series

Mohammad Ali Ghorbani, Ozgur Kisi, Rahman Khatibi, 2012 .

Dynamics of hourly sea level at Hillarys Boat Harbour, Western Australia: a chaos theory perspective

Mohammad Ali Ghorbani, Dina Makarynska, Rahman Khatibi, 2011 .

Investigating ‘risk’ of groundwater drought occurrences by using reliability analysis

Rahman Khatibi, Sina Sadeghfam, Rasoul Daneshfaraz, 2018, Ecological Indicators.

Predictive groundwater levels modelling by Inclusive Multiple Modelling (IMM) at multiple levels

Rahman Khatibi, Ata Allah Nadiri, Zahra Sedghi, 2021, Earth Science Informatics.

A framework for ‘Inclusive Multiple Modelling’ with critical views on modelling practices – Applications to modelling water levels of Caspian Sea and Lakes Urmia and Van

Vahid Karimi, Rahman Khatibi, Mohammad A. Ghorbani, 2020 .

Qualitative risk aggregation problems for the safety of multiple aquifers exposed to nitrate, fluoride and arsenic contaminants by a ‘Total Information Management’ framework

R. Khatibi, A. Nadiri, Zahra Sedghi, 2021 .

A study of uncertainties in groundwater vulnerability modelling using Bayesian model averaging (BMA)

R. Khatibi, S. Sadeghfam, A. Nadiri, 2022, Journal of Environmental Management.

Modelling groundwater level variations by learning from multiple models using fuzzy logic

Rahman Khatibi, Keyvan Naderi, Ata Allah Nadiri, 2019, Hydrological Sciences Journal.

Mapping vulnerability of multiple aquifers using multiple models and fuzzy logic to objectively derive model structures.

Rahman Khatibi, Ata Allah Nadiri, Maryam Gharekhani, 2017, The Science of the total environment.

Assessment of groundwater vulnerability using supervised committee to combine fuzzy logic models

Rahman Khatibi, Asghar Asghari Moghaddam, Ata Allah Nadiri, 2017, Environmental Science and Pollution Research.

Spatial Prediction of Groundwater Level Using Models Based on Fuzzy Logic and Geostatistical Methods

A A Nadiri, Rahman Khatibi, Fatemeh Vahedi, 2019, GIS and Geostatistical Techniques for Groundwater Science.

Sea water level forecasting using genetic programming and comparing the performance with Artificial Neural Networks

Mohammad Ali Ghorbani, Rahman Khatibi, Jalal Shiri, 2010, Comput. Geosci..

Developing a predictive tropospheric ozone model for Tabriz

Rahman Khatibi, Hadi Arvanaghi, Mohammad A. Ghorbani, 2013 .

Continuous monitoring of suspended sediment concentrations using image analytics and deriving inherent correlations by machine learning

V. Singh, B. Sivakumar, M. Ghorbani, 2020, Scientific Reports.

Next Stages in Aquifer Vulnerability Studies by Integrating Risk Indexing with Understanding Uncertainties by using Generalised Likelihood Uncertainty Estimation

R. Khatibi, S. Sadeghfam, A. Nadiri, 2021, Exposure and Health.

Transforming subsidence vulnerability indexing based on ALPRIFT into risk indexing using a new fuzzy-catastrophe scheme

Rahman Khatibi, Sina Sadeghfam, Ata Allah Nadiri, 2020 .

Groundwater DRASTIC vulnerability mapping by unsupervised and supervised techniques using a modelling strategy in two levels

Rahman Khatibi, Ata Allah Nadiri, Maryam Gharekhani, 2019, Journal of Hydrology.

Mapping specific vulnerability of multiple confined and unconfined aquifers by using artificial intelligence to learn from multiple DRASTIC frameworks.

Rahman Khatibi, Sina Sadeghfam, Ata Allah Nadiri, 2018, Journal of environmental management.

Introducing the risk aggregation problem to aquifers exposed to impacts of anthropogenic and geogenic origins on a modular basis using 'risk cells'.

Rahman Khatibi, Sina Sadeghfam, Ata Allah Nadiri, 2018, Journal of environmental management.

Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM).

Rahman Khatibi, Sina Sadeghfam, Asghar Asghari Moghaddam, 2017, The Science of the total environment.

Learning from Multiple Models Using Artificial Intelligence to Improve Model Prediction Accuracies: Application to River Flows

Zaher Mundher Yaseen, V. Karimi, M. A. Ghorbani, 2018, Water Resources Management.

An investigation into uncertainties within Human Health Risk Assessment to gain an insight into plans to mitigate impacts of arsenic contamination

M. Abdi, R. Khatibi, S. Sadeghfam, 2021 .

An investigation to human health risks from multiple contaminants and multiple origins by introducing ‘Total Information Management’

R. Khatibi, Venkatramanan Senapathi, S. Sekar, 2021, Environmental Science and Pollution Research.

Modelling Energy Dissipation Over Stepped-gabion Weirs by Artificial Intelligence

Mohammad Ali Ghorbani, Rahman Khatibi, Farzin Salmasi, 2014, Water Resources Management.

Stream flow predictions using nature-inspired Firefly Algorithms and a Multiple Model strategy - Directions of innovation towards next generation practices

Mohammad Ali Ghorbani, Rahman Khatibi, F. Akhoni Pourhosseini, 2017, Adv. Eng. Informatics.

Short-term wind speed predictions with machine learning techniques

R. Khatibi, M. A. Ghorbani, M. H. FazeliFard, 2016, Meteorology and Atmospheric Physics.

Statistical downscaling of precipitation using inclusive multiple modelling (IMM) at two levels

R. Khatibi, S. Sadeghfam, R. Daneshfaraz, 2021, Journal of Water and Climate Change.

Inclusive Multiple Models (IMM) for predicting groundwater levels and treating heterogeneity

Rahman Khatibi, Ata Allah Nadiri, R. Khatibi, 2021 .

Soil Cation Exchange Capacity Predicted by Learning From Multiple Modelling: Forming Multiple Models Run by SVM to Learn From ANN and Its Hybrid With Firefly Algorithm

Mohammad Ali Ghorbani, Rahman Khatibi, Rasoul Jani, 2018 .

Study of discontinuities in hydrological data using catastrophe theory

Mohammad Ali Ghorbani, Rahman Khatibi, Bellie Sivakumar, 2010 .

Introducing a risk aggregation rationale for mapping risks to aquifers from point- and diffuse-sources–proof-of-concept using contamination data from industrial lagoons

Rahman Khatibi, Yousef Hassanzadeh, Sina Sadeghfam, 2018, Environmental Impact Assessment Review.

Comparison of three artificial intelligence techniques for discharge routing

Mohammad Ali Ghorbani, Ozgur Kisi, Rahman Khatibi, 2011 .

Predictability of relative humidity by two artificial intelligence techniques using noisy data from two Californian gauging stations

M. Ghorbani, R. Khatibi, M. Aalami, 2013, Neural Computing and Applications.

Mathematical Treatment of Bimodality for the Safety Factor in Riverbank Stability Analysis Using Cusp Catastrophe

R. Khatibi, S. Sadeghfam, Marjan Moazamnia, 2023, International Journal of Geomechanics.

Barriers inherent in flood forecasting and their treatments

Rahman Khatibi, R. Khatibi, 2005 .

Hydraulic character of flood drainage systems. Part 2: case studies

R. Khatibi, 1997 .

A study of urban heat island effects using remote sensing and GIS techniques in Kancheepuram, Tamil Nadu, India

R. Khatibi, Venkatramanan Senapathi, S. Chung, 2023, Urban Climate.