DSpace Collection:http://hdl.handle.net/10174/6362024-03-29T14:05:48Z2024-03-29T14:05:48ZConstraint Modeling for Forest ManagementEloy, EduardoBushenkov, VladimirAbreu, Salvadorhttp://hdl.handle.net/10174/362422024-02-06T09:39:38Z2022-01-01T00:00:00ZTitle: Constraint Modeling for Forest Management
Authors: Eloy, Eduardo; Bushenkov, Vladimir; Abreu, Salvador
Editors: Tchemisova, Tatiana; Torres, Delfim; Plakhov, Alexander
Abstract: Forestmanagement is an activity of prime economic and ecological impor2
tance. Managed forest areas can span very large regions and their proper manage3
ment is paramount to an effective development, in terms both of economic and natural
4 resources planning. Amanaged activity consists of individual andmutually indepen5
dent policy choices which apply to distinct patches of land—named stands—which,
6 as a whole, make up the forest area. A forest management plan typically spans a
7 period of time on the order of a century and is normally geared towards the optimisa8
tion of economic or environmental metrics (e.g. total wood yield.) In this article we
9 present a method which uses a declarative programming approach to formalise and
10 solve a long-term forest management problem.We do so based on a freely available
11 state-of-the-art constraint programming system,whichwe extend to naturally express
12 concepts related to the core problem and efficiently compute solutions thereto.2022-01-01T00:00:00ZArtificial Stress Diffusion in Numerical Simulations of Viscoelastic Fluid FlowsPires, MaríliaBodnár, Tomáshttp://hdl.handle.net/10174/337312023-01-30T16:48:34Z2022-08-01T23:00:00ZTitle: Artificial Stress Diffusion in Numerical Simulations of Viscoelastic Fluid Flows
Authors: Pires, Marília; Bodnár, Tomás
Editors: Carapau, Fernando; Vaidya, Ashuwin
Abstract: Viscoelastic fluids are quite common in many areas of industrial, environmental, and biomedical fluid mechanics. There exist a number of models describing specific subclasses of these fluids, capturing their various distinct properties. Most of these models are rather complex, relating the stress tensor with the fluid rate of deformation tensor and its history. This is why the mathematical modeling and numerical simulations of viscoelastic fluid flows are some of the most challenging problems of contemporary computational fluid dynamics.2022-08-01T23:00:00ZA Generalized Mean Under a Non-Regular Framework and Extreme Value Index EstimationGomes, Maria IvetteHenriques-Rodrigues, LígiaPestana, Dinishttp://hdl.handle.net/10174/335862023-01-23T15:06:22Z2022-09-30T23:00:00ZTitle: A Generalized Mean Under a Non-Regular Framework and Extreme Value Index Estimation
Authors: Gomes, Maria Ivette; Henriques-Rodrigues, Lígia; Pestana, Dinis
Editors: Zafeiris, Konstantinos N.; Skiadas, Christos H.; Dimotikalis, Yiannis; Karagrigoriou, Alex; Karagrigoriou-Vonta, Christiana
Abstract: The Hill estimator, one of the most popular extreme value index (EVI) estimators under a heavy right-tail framework, i.e. for a positive EVI, here denoted by ξ, is an average of the log-excesses. Consequently, it can be regarded as the logarithm of the geometric mean or mean of order p = 0 of an adequate set of systematic statistics. We can thus more generally consider any real p, the mean of order p (MOp) of those same statistics and the associated MOp EVI-estimators, also called harmonic moment EVI-estimators. The normal asymptotic behavior of these estimators has been obtained for p < 1/(2ξ), with consistency achieved for p < 1/ξ. The non-regular framework, i.e. the case p ≥ 1/(2ξ), will be now considered. Consistency is no longer achieved for p > 1/ξ, but an almost degenerate behavior appears for p = 1/ξ. The results are illustrated on the basis of large-scale simulation studies. An algorithm providing an almost degenerate MOp EVI-estimation is suggested.2022-09-30T23:00:00ZEstimation of the Weibull tail coefficient through the power-mean-of-order pCaeiro, FredericoGomes, Maria IvetteHenriques-Rodrigues, Lígiahttp://hdl.handle.net/10174/335212023-01-17T12:16:47Z2022-11-29T00:00:00ZTitle: Estimation of the Weibull tail coefficient through the power-mean-of-order p
Authors: Caeiro, Frederico; Gomes, Maria Ivette; Henriques-Rodrigues, Lígia
Editors: Bispo, Regina; Henriques-Rodrigues, Lígia; Alpizar-Jara, Russell; de Carvalho, Miguel
Abstract: The Weibull tail coefficient (WTC) is the parameter θ
θ in a right-tail function of the type F¯:=1−F
F¯:=1−F, such that H:=−ln F¯ is a regularly varying function at infinity with an index of regular variation equal to θ∈R+. In a context of extreme value theory for maxima, it is possible to prove that we have an extreme value index (EVI) ξ=0, but usually a very slow rate of convergence. Most of the recent WTC-estimators are proportional to the class of Hill EVI-estimators, the average of the log-excesses associated with the k upper order statistics, 1≤k<n. The interesting performance of EVI-estimators based on generalized means leads us to base the WTC-estimation on the power mean-of-order-p (MOp) EVI-estimators. Consistency of the WTC-estimators is discussed and their performance, for finite samples, is illustrated through a small-scale Monte Carlo simulation study.2022-11-29T00:00:00Z