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El Adlouni S.,Institute National Of Statistique Et Deconomie Appliquee | Bobee B.,INRS - Institute National de la Recherche Scientifique
IAHS-AISH Publication | Year: 2010

The estimation of flood flows is of major importance for the design and management of hydraulic structures. Two main classes of laws are used in hydrology frequency analysis: the class D of sub-exponential distributions and the class C of regularly varying distributions with a heavier tail. No criteria were available for the choice between these two classes of the most appropriate fit, especially at extreme values. A Decision Support System (DSS) based on the characterization of the right tail of probability distributions, used in frequency analysis, has been developed. The DSS allows us to discriminate between class C and D. Note that the class selection has a great importance for the extrapolation. The use of the DSS on the Potomac River flood (USA), shows that the maxima series is best represented by a distribution of the class C. Copyright © 2010 IAHS Press.

Kamali Nezhad M.,Hydro - Quebec | Ouarda T.B.M.J.,Canada Research Chair on the Estimation of Hydrometeorological Variables | Chokmani K.,Canada Research Chair on the Estimation of Hydrometeorological Variables | Barbet M.,Hydro - Quebec | And 2 more authors.
Hydrological Processes | Year: 2011

Various regional flood frequency analysis procedures are used in hydrology to estimate hydrological variables at ungauged or partially gauged sites. Relatively few studies have been conducted to evaluate the accuracy of these procedures and estimate the error induced in regional flood frequency estimation models. The objective of this paper is to assess the overall error induced in the residual kriging (RK) regional flood frequency estimation model. The two main error sources in specific flood quantile estimation using RK are the error induced in the quantiles local estimation procedure and the error resulting from the regional quantile estimation process. Therefore, for an overall error assessment, the corresponding errors associated with these two steps must be quantified. Results show that the main source of error in RK is the error induced into the regional quantile estimation method. Results also indicate that the accuracy of the regional estimates increases with decreasing return periods. © 2010 John Wiley & Sons, Ltd.

Dahmouni H.,Institute National des Postes et Telecommunications | Girard A.,INRS EMT | Ouzineb M.,Institute National Of Statistique Et Deconomie Appliquee | Sanso B.,Ecole Polytechnique de Montréal
IEEE Transactions on Network and Service Management | Year: 2012

Current network planning and design methods use the average delay, packet loss and throughput as metrics to optimize the network cost and performance. New multimedia applications, on the other hand, also have critical jitter requirements that are not taken into account by these methods. Here, we explore the impact on the network performance of adding these jitter constraints. We use a fast jitter calculation model to solve the optimal routing problem for flows subject to jitter or delay constraints. We find that the optimal routing is very different for the two kinds of flows: They should be routed on different paths, the jitter-constrained flows should not be split on multiple paths while the opposite conclusion is true for delay-constrained flows. © 2004-2012 IEEE.

Ouzineb M.,Institute National Of Statistique Et Deconomie Appliquee | Mhada F.,Mohammed V University | El Hallaoui I.,Ecole Polytechnique de Montréal | Pellerin R.,Ecole Polytechnique de Montréal
Proceedings of 2013 International Conference on Industrial Engineering and Systems Management, IEEE - IESM 2013 | Year: 2013

An unreliable single part type transfer line with fixed inter machine buffer sizes is considered. In general, imperfect machines operating with imperfect raw material, or partially processed raw material, will result in the production of a mix of conforming and non conforming parts. The problem of optimal joint assignment of buffer sizes and inspection station positions is here considered where we assume that defective parts are scrapped upon detection. The performance measure to be optimized is a combination of work in process storage and parts inspection costs, with an eye to determining the adequate number of inspection stations. We propose an exact method for solving this problem and large-scale numerical experiments are provided to demonstrate the efficiency of the proposed algorithm. Interesting properties of the problem are also denoted based on our empirical results. © 2013 International Institute for Innovation, Industrial Engineering and Entrepreneurship - I4e2.

Adlouni S.E.,Institute National Of Statistique Et Deconomie Appliquee | Ouarda T.B.M.J.,INRS - Institute National de la Recherche Scientifique
Geophysical Monograph Series | Year: 2010

The study of the rainfall probability distributions is important to estimate large events and their probability of occurrence. This paper presents the usefulness of extreme hydrological frequency analysis when the occurrences are independent in time to describe the likelihood of extreme events over the time horizon. Classical and recent developments are presented with illustrative examples. Copyright 2010 by the American Geophysical Union.

Chebana F.,INRS - Institute National de la Recherche Scientifique | Adlouni S.E.,Institute National Of Statistique Et Deconomie Appliquee | Bobee B.,INRS - Institute National de la Recherche Scientifique
Stochastic Environmental Research and Risk Assessment | Year: 2010

The Halphen family of distributions is a flexible and complete system to fit sets of observations independent and identically distributed. Recently, it is shown that this family of distributions represents a potential alternative to the generalized extreme value distributions to model extreme hydrological events. The existence of jointly sufficient statistics for parameter estimation leads to optimality of the method of maximum likelihood (ML). Nevertheless, the ML method requires numerical approximations leading to less accurate values. However, estimators by the method of moments (MM) are explicit and their computation is fast. Even though MM method leads to good results, it is not optimal. In order to combine the advantages of the ML (optimality) and MM (efficiency and fast computations), two new mixed methods were proposed in this paper. One of the two methods is direct and the other is iterative, denoted respectively direct mixed method (MMD) and iterative mixed method (MMI). An overall comparison of the four estimation methods (MM, ML, MMD and MMI) was performed using Monte Carlo simulations regarding the three Halphen distributions. Generally, the MMI method can be considered for the three Halphen distributions since it is recommended for a majority of cases encountered in hydrology. The principal idea of the mixed methods MMD and MMI could be generalized for other distributions with complicated density functions. © 2009 Springer-Verlag.

El Adlouni S.,Institute National Of Statistique Et Deconomie Appliquee | Chebana F.,INRS - Institute National de la Recherche Scientifique | Bobee B.,INRS - Institute National de la Recherche Scientifique
Journal of Hydrologic Engineering | Year: 2010

The Halphen system the generalized extreme-value (GEV) distributions are recommended for the estimation of the hydrological extreme events. The GEV system is widely used, whereas the Halphen distributions are less known by hydrologists. The objective of this study is to compare these two systems on the basis of various criteria. A simulation study was undertaken to assess the errors related to the fit of the Halphen distributions to samples generated by the GEV distribution vice versa. Results show that in the case of power-tail type, the Halphen type Inverse B (HIB) distribution is more adequate safer than the Fréchet (EV2) or Gumbel (EV1) distributions especially in the case of the small sample size. For subexponential class of distributions, both Halphen Type A (HA) Type B (HB) perform better than the Gumbel (EV1) distribution. When considering limiting distribution cases, results show a very similar behavior of EV1, gammainverse gamma distribution with a small advantage to the EV1 distribution. These results as well as the theoretical statistical properties of these systems of distributions indicate that the Halphen distributions can, in some cases, perform better than the GEV system are good candidate to fit extreme value variables. © 2010 ASCE.

Tramblay Y.,Montpellier University | Badi W.,Center National Of Recherche Meteorologiques | Driouech F.,Center National Of Recherche Meteorologiques | El Adlouni S.,University of Moncton | And 3 more authors.
Global and Planetary Change | Year: 2012

Morocco is a North African country highly vulnerable to extreme precipitation events. In the present study, past trends in extreme precipitation and future projections using an ensemble of regional climate models (RCM) are evaluated. The extreme precipitation distributions during the extended winter season (October to April) in 10 stations are fitted with Generalized Extreme Value models (GEV). The dependence of the GEV parameters with time, winter North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO) indexes have been tested. Results indicate no significant trends in extreme precipitation during the observation period 1961-2007. However, dependences between precipitation extremes and NAO or MO indexes are detected, in particular for the Atlantic stations. Then 15 RCM simulations provided by the ENSEMBLES European project ran with the A1B scenario are considered to provide future projections. The Cramér-von Mises (CM) statistic is introduced as a measure of adequacy between the observed extreme precipitation distributions at the different stations and the distributions simulated by the RCMs. The CM statistic can thus provide weights to build a multi-model ensemble of future projections based on model performance in the present climate. Even if some models exhibit good skills, there is a great variability in the RCM performances to reproduce the seasonal cycle and the extreme precipitation distributions at the different stations. The projected changes on extreme precipitation at the stations are evaluated with quantiles computed for different return periods, ranging from 2 to 40. years, during the control period 1961-2007 and two projection periods, 2020-2050 and 2070-2099. The climate change scaling factors on extreme quantiles provided by the different RCMs are averaged with equal weights, or with weights obtained from the inverse of the CM statistic. The climate change signal in the RCM simulations indicate a decrease in extreme precipitation quantiles, - 12% in average for the projection period 2070-2099 but a great variability and lower convergence between models is found for the projection period 2020-2050. Overall, there is a good model convergence towards a decrease for the Atlantic stations. For the Mediterranean stations, the projected changes are difficult to assess due to the great variability. The two weighting schemes tested for model outputs provide similar results. © 2011 Elsevier B.V.

Fakhar K.,Mohammed V University | El Aroussi M.,Mohammed V University | Saidi M.N.,Mohammed V University | Saidi M.N.,Institute National Of Statistique Et Deconomie Appliquee | Aboutajdine D.,Mohammed V University
Information (Switzerland) | Year: 2015

This paper presents a new biometric score fusion approach in an identification system using the upper integral with respect to Sugeno's fuzzy measure. First, the proposed method considers each individual matcher as a fuzzy set in order to handle uncertainty and imperfection in matching scores. Then, the corresponding fuzzy entropy estimates the reliability of the information provided by each biometric matcher. Next, the fuzzy densities are generated based on rank information and training accuracy. Finally, the results are aggregated using the upper fuzzy integral. Experimental results compared with other fusion methods demonstrate the good performance of the proposed approach. © 2015 by the authors.

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