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Saman Razavi
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2020 – today
- 2024
- [j20]Seyed Vahid Razavi Termeh, Abolghasem Sadeghi-Niaraki, Saman Razavi, Soo-Mi Choi:
Enhancing flood-prone area mapping: fine-tuning the K-nearest neighbors (KNN) algorithm for spatial modelling. Int. J. Digit. Earth 17(1) (2024) - [j19]Saman Razavi
, Daniel P. Ames, Min Chen:
EnviroFutures: Envisioning the next century of environmental sciences. Environ. Model. Softw. 171: 105880 (2024) - 2023
- [j18]Holger R. Maier
Exploding the myths: An introduction to artificial neural networks for prediction and forecasting. Environ. Model. Softw. 167: 105776 (2023) - [j17]Wenyan Wu, Leila Eamen, Graeme C. Dandy, Saman Razavi, George Kuczera, Holger R. Maier:
Beyond engineering: A review of reservoir management through the lens of wickedness, competing objectives and uncertainty. Environ. Model. Softw. 167: 105777 (2023) - [j16]Holger R. Maier
On how data are partitioned in model development and evaluation: Confronting the elephant in the room to enhance model generalization. Environ. Model. Softw. 167: 105779 (2023) - 2022
- [j15]Leila Eamen
Comparing the applicability of hydro-economic modelling approaches for large-scale decision-making in multi-sectoral and multi-regional river basins. Environ. Model. Softw. 152: 105385 (2022) - 2021
- [j14]Takuya Iwanaga
Socio-technical scales in socio-environmental modeling: Managing a system-of-systems modeling approach. Environ. Model. Softw. 135: 104885 (2021) - [j13]Saman Razavi
The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support. Environ. Model. Softw. 137: 104954 (2021) - [j12]Saman Razavi
Deep learning, explained: Fundamentals, explainability, and bridgeability to process-based modelling. Environ. Model. Softw. 144: 105159 (2021) - [j11]Andrea Saltelli
Sensitivity analysis: A discipline coming of age. Environ. Model. Softw. 146: 105226 (2021)
2010 – 2019
- 2019
- [j10]Razi Sheikholeslami, Saman Razavi
Global sensitivity analysis for high-dimensional problems: How to objectively group factors and measure robustness and convergence while reducing computational cost. Environ. Model. Softw. 111: 282-299 (2019) - [j9]Saman Razavi
VARS-TOOL: A toolbox for comprehensive, efficient, and robust sensitivity and uncertainty analysis. Environ. Model. Softw. 112: 95-107 (2019) - [j8]Saman Razavi
A multi-method Generalized Global Sensitivity Matrix approach to accounting for the dynamical nature of earth and environmental systems models. Environ. Model. Softw. 114: 1-11 (2019) - [j7]Holger R. Maier
Introductory overview: Optimization using evolutionary algorithms and other metaheuristics. Environ. Model. Softw. 114: 195-213 (2019) - [j6]Joseph H. A. Guillaume
Introductory overview of identifiability analysis: A guide to evaluating whether you have the right type of data for your modeling purpose. Environ. Model. Softw. 119: 418-432 (2019) - 2017
- [j5]Razi Sheikholeslami
Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models. Environ. Model. Softw. 93: 109-126 (2017) - [j4]Amin Haghnegahdar
Insights into sensitivity analysis of Earth and environmental systems models: On the impact of parameter perturbation scale. Environ. Model. Softw. 95: 115-131 (2017) - 2014
- [j3]Masoud Asadzadeh
Pre-emption strategies for efficient multi-objective optimization: Application to the development of Lake Superior regulation plan. Environ. Model. Softw. 54: 128-141 (2014) - 2012
- [j2]Saman Razavi
Numerical assessment of metamodelling strategies in computationally intensive optimization. Environ. Model. Softw. 34: 67-86 (2012) - 2011
- [j1]Saman Razavi
A New Formulation for Feedforward Neural Networks. IEEE Trans. Neural Networks 22(10): 1588-1598 (2011)
Coauthor Index
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