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Mansouri Majdi

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Main Referenced Co-authors
Destain, Marie-France  (10)
Dumont, Benjamin  (9)
Leemans, Vincent  (2)
Bodson, Bernard  (1)
Destain, Jean-Pierre  (1)
Main Referenced Keywords
Crop model (6); LAI (4); Bayesian methods (3); crop model (2); Particle filter (2);
Main Referenced Disciplines
Engineering, computing & technology: Multidisciplinary, general & others (7)
Computer science (3)
Agriculture & agronomy (3)

Publications (total 10)

The most downloaded
920 downloads
Dumont, B., Leemans, V., Mansouri, M., Bodson, B., Destain, J.-P., & Destain, M.-F. (February 2014). Parameter identification of the STICS crop model, using an accelerated formal MCMC approach. Environmental Modelling and Software, 52, 121-135. doi:10.1016/j.envsoft.2013.10.022 https://hdl.handle.net/2268/160225

The most cited

54 citations (Scopus®)

Dumont, B., Leemans, V., Mansouri, M., Bodson, B., Destain, J.-P., & Destain, M.-F. (February 2014). Parameter identification of the STICS crop model, using an accelerated formal MCMC approach. Environmental Modelling and Software, 52, 121-135. doi:10.1016/j.envsoft.2013.10.022 https://hdl.handle.net/2268/160225

Mansouri, M., & Destain, M.-F. (2015). Predicting biomass and grain protein content using Bayesian methods. Stochastic Environmental Research and Risk Assessment. doi:10.1007/s00477-015-1038-0
Peer Reviewed verified by ORBi

Mansouri, M., Dumont, B., & Destain, M.-F. (2014). Predicting Grain Protein Content of Winter Wheat. In ESANN 2014 Proceedings.
Peer reviewed

Dumont, B., Leemans, V., Mansouri, M., Bodson, B., Destain, J.-P., & Destain, M.-F. (February 2014). Parameter identification of the STICS crop model, using an accelerated formal MCMC approach. Environmental Modelling and Software, 52, 121-135. doi:10.1016/j.envsoft.2013.10.022
Peer Reviewed verified by ORBi

Mansouri, M., Dumont, B., & Destain, M.-F. (February 2014). Bayesian methods for predicting and modelling winter wheat biomass [Poster presentation]. Modelling climate change impacts on crop production for food security, Oslo, Norway.

Mansouri, M., Dumont, B., Leemans, V., & Destain, M.-F. (2014). Bayesian methods for predicting LAI and soil water content. Precision Agriculture, 15 (2), 184-201. doi:10.1007/s11119-013-9332-7
Peer Reviewed verified by ORBi

Mansouri, M., Dumont, B., & Destain, M.-F. (2014). Predicting Winter Wheat Biomass And Grain Protein Content. In Proceedings of the 12th International Conference on Precision Agriculture.
Peer reviewed

Mansouri, M., Dumont, B., & Destain, M.-F. (2013). Prediction of non-linear time-variant dynamic crop model using bayesian methods. In John Stafford (Ed.), Precision agriculture '13 (pp. 507-513). Netherlands: Wageningen Academic Publishers.
Peer reviewed

Mansouri, M., Dumont, B., & Destain, M.-F. (2013). Prediction of non-linear time-variant dynamic crop model using bayesian methods. In J. V. Stafford (Ed.), Precision agriculture '13 (pp. 507-513). Wageningen, Netherlands: Wageningen Academic Publishers. doi:10.3920/978-90-8686-778-3_62
Peer reviewed

Mansouri, M., Dumont, B., & Destain, M.-F. (2013). Modeling and Prediction of Time-Varying Environmental Data Using Advanced Bayesian Methods. In A. Masegosa, P. Villacorta, C. Cruz-Corona, S. Garcia-Cascales, M. Lamata, ... J. Verdegay (Eds.), Exploring Innovative and Successful Applications of Soft Computing (pp. 112-137). Hershey PA, United States: IGI Global. doi:10.4018/978-1-4666-4785-5.ch007
Peer reviewed

Mansouri, M., Dumont, B., & Destain, M.-F. (2012). Bayesian methods for predicting LAI and soil moisture. In Proceedings of the 11th International Conference on Precision Agriculture.
Peer reviewed

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