968 resultados para Computational prediction
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ABSTRACT Monitoring analyses aim to understand the processes that drive changes in forest structure and, along with prediction studies, may assist in the management planning and conservation of forest remnants. The objective of this study was to analyze the forest dynamics in two Atlantic rainforest fragments in Pernambuco, Brazil, and to predict their future forest diameter structure using the Markov chain model. We used continuous forest inventory data from three surveys in two forest fragments of 87 ha (F1) and 388 ha (F2). We calculated the annual rates of mortality and recruitment, the mean annual increment, and the basal area for each of the 3-year periods. Data from the first and second surveys were used to project the third inventory measurements, which were compared to the observed values in the permanent plots using chi-squared tests (a = 0.05). In F1, a decrease in the number of individuals was observed due to mortality rates being higher than recruitment rates; however, there was an increase in the basal area. In this fragment, the fit to the Markov model was adequate. In F2, there was an increase in both the basal area and the number of individuals during the 6-year period due to the recruitment rate exceeding the mortality rate. For this fragment, the fit of the model was unacceptable. Hence, for the studied fragments, the demographic rates influenced the stem density more than the floristic composition. Yet, even with these intense dynamics, both fragments showed active growth.
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Linear programming models are effective tools to support initial or periodic planning of agricultural enterprises, requiring, however, technical coefficients that can be determined using computer simulation models. This paper, presented in two parts, deals with the development, application and tests of a methodology and of a computational modeling tool to support planning of irrigated agriculture activities. Part I aimed at the development and application, including sensitivity analysis, of a multiyear linear programming model to optimize the financial return and water use, at farm level for Jaíba irrigation scheme, Minas Gerais State, Brazil, using data on crop irrigation requirement and yield, obtained from previous simulation with MCID model. The linear programming model outputted a crop pattern to which a maximum total net present value of R$ 372,723.00 for the four years period, was obtained. Constraints on monthly water availability, labor, land and production were critical in the optimal solution. In relation to the water use optimization, it was verified that an expressive reductions on the irrigation requirements may be achieved by small reductions on the maximum total net present value.
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Techniques of evaluation of risks coming from inherent uncertainties to the agricultural activity should accompany planning studies. The risk analysis should be carried out by risk simulation using techniques as the Monte Carlo method. This study was carried out to develop a computer program so-called P-RISCO for the application of risky simulations on linear programming models, to apply to a case study, as well to test the results comparatively to the @RISK program. In the risk analysis it was observed that the average of the output variable total net present value, U, was considerably lower than the maximum U value obtained from the linear programming model. It was also verified that the enterprise will be front to expressive risk of shortage of water in the month of April, what doesn't happen for the cropping pattern obtained by the minimization of the irrigation requirement in the months of April in the four years. The scenario analysis indicated that the sale price of the passion fruit crop exercises expressive influence on the financial performance of the enterprise. In the comparative analysis it was verified the equivalence of P-RISCO and @RISK programs in the execution of the risk simulation for the considered scenario.
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Tämä taktiikan tutkimus keskittyy tietokoneavusteisen simuloinnin laskennallisiin menetelmiin, joita voidaan käyttää taktisen tason sotapeleissä. Työn tärkeimmät tuotokset ovat laskennalliset mallit todennäköisyyspohjaisen analyysin mahdollistaviin taktisen tason taistelusimulaattoreihin, joita voidaan käyttää vertailevaan analyysiin joukkue-prikaatitason tarkastelutilanteissa. Laskentamallit keskittyvät vaikuttamiseen. Mallit liittyvät vahingoittavan osuman todennäköisyyteen, jonka perusteella vaikutus joukossa on mallinnettu tilakoneina ja Markovin ketjuina. Edelleen näiden tulokset siirretään tapahtumapuuanalyysiin operaation onnistumisen todennäköisyyden osalta. Pienimmän laskentayksikön mallinnustaso on joukkue- tai ryhmätasolla, jotta laskenta-aika prikaatitason sotapelitarkasteluissa pysyisi riittävän lyhyenä samalla, kun tulokset ovat riittävän tarkkoja suomalaiseen maastoon. Joukkueiden mies- ja asejärjestelmävahvuudet ovat jakaumamuodossa, eivätkä yksittäisiä lukuja. Simuloinnin integroinnissa voidaan käyttää asejärjestelmäkohtaisia predictor corrector –parametreja, mikä mahdollistaa aika-askelta lyhytaikaisempien taistelukentän ilmiöiden mallintamisen. Asemallien pohjana ovat aiemmat tutkimukset ja kenttäkokeet, joista osa kuuluu tähän väitöstutkimukseen. Laskentamallien ohjelmoitavuus ja käytettävyys osana simulointityökalua on osoitettu tekijän johtaman tutkijaryhmän ohjelmoiman ”Sandis”- taistelusimulointiohjelmiston avulla, jota on kehitetty ja käytetty Puolustusvoimien Teknillisessä Tutkimuslaitoksessa. Sandikseen on ohjelmoitu karttakäyttöliittymä ja taistelun kulkua simuloivia laskennallisia malleja. Käyttäjä tai käyttäjäryhmä tekee taktiset päätökset ja syöttää nämä karttakäyttöliittymän avulla simulointiin, jonka tuloksena saadaan kunkin joukkuetason peliyksikön tappioiden jakauma, keskimääräisten tappioiden osalta kunkin asejärjestelmän aiheuttamat tappiot kuhunkin maaliin, ammuskulutus ja radioyhteydet ja niiden tila sekä haavoittuneiden evakuointi-tilanne joukkuetasolta evakuointisairaalaan asti. Tutkimuksen keskeisiä tuloksia (kontribuutio) ovat 1) uusi prikaatitason sotapelitilanteiden laskentamalli, jonka pienin yksikkö on joukkue tai ryhmä; 2) joukon murtumispisteen määritys tappioiden ja haavoittuneiden evakuointiin sitoutuvien taistelijoiden avulla; 3) todennäköisyyspohjaisen riskianalyysin käyttömahdollisuus vertailevassa tutkimuksessa sekä 4) kokeellisesti testatut tulen vaikutusmallit ja 5) toimivat integrointiratkaisut. Työ rajataan maavoimien taistelun joukkuetason todennäköisyysjakaumat luovaan laskentamalliin, kenttälääkinnän malliin ja epäsuoran tulen malliin integrointimenetelmineen sekä niiden antamien tulosten sovellettavuuteen. Ilmasta ja mereltä maahan -asevaikutusta voidaan tarkastella, mutta ei ilma- ja meritaistelua. Menetelmiä soveltavan Sandis -ohjelmiston malleja, käyttötapaa ja ohjelmistotekniikkaa kehitetään edelleen. Merkittäviä jatkotutkimuskohteita mallinnukseen osalta ovat muun muassa kaupunkitaistelu, vaunujen kaksintaistelu ja maaston vaikutus tykistön tuleen sekä materiaalikulutuksen arviointi.
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The draft forces of soil engaging tines and theoretical analysis compared to existing mathematical models, have yet not been studied in Rio Grande do Sul soils. From the existing models, those which can get the closest fitting draft forces to real measure on field have been established for two of Rio Grande do Sul soils. An Albaqualf and a Paleudult were evaluated. From the studied models, those suggested by Reece, so called "Universal Earthmoving Equation", Hettiaratchi and Reece, and Godwin and Spoor were the best fitting ones, comparing the calculated results with those measured "in situ". Allowing for the less complexity of Reece's model, it is suggested that this model should be used for modeling draft forces prediction for narrow tines in Albaqualf and Paleudut.
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The interaction between the soil and tillage tool can be examined using different parameters for the soil and the tool. Among the soil parameters are the shear stress, cohesion, internal friction angle of the soil and the pre-compression stress. The tool parameters are mainly the tool geometry and depth of operation. Regarding to the soils of Rio Grande do Sul there are hardly any studies and evaluations of the parameters that have importance in the use of mathematical models to predict tensile loads. The objective was to obtain parameters related to the soils of Rio Grande do Sul, which are used in soil-tool analysis, more specifically on mathematical models that allow the calculation of tractive effort for symmetric and narrow tools. Two of the main soils of Rio Grande do Sul, an Albaqualf and a Paleudult were studied. Equations that relate the cohesion, internal friction angle of the soil, adhesion, soil-tool friction angle and pre-compression stress as a function of water content in the soil were obtained, leading to important information for use of mathematical models for tractive effort calculation.
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The goal of this study was to develop a fuzzy model to predict the occupancy rate of free-stalls facilities of dairy cattle, aiding to optimize the design of projects. The following input variables were defined for the development of the fuzzy system: dry bulb temperature (Tdb, °C), wet bulb temperature (Twb, °C) and black globe temperature (Tbg, °C). Based on the input variables, the fuzzy system predicts the occupancy rate (OR, %) of dairy cattle in free-stall barns. For the model validation, data collecting were conducted on the facilities of the Intensive System of Milk Production (SIPL), in the Dairy Cattle National Research Center (CNPGL) of Embrapa. The OR values, estimated by the fuzzy system, presented values of average standard deviation of 3.93%, indicating low rate of errors in the simulation. Simulated and measured results were statistically equal (P>0.05, t Test). After validating the proposed model, the average percentage of correct answers for the simulated data was 89.7%. Therefore, the fuzzy system developed for the occupancy rate prediction of free-stalls facilities for dairy cattle allowed a realistic prediction of stalls occupancy rate, allowing the planning and design of free-stall barns.
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This study aimed to investigate the potential use of magnetic susceptibility (MS) as pedotransfer function to predict soil attributes under two sugarcane harvesting management systems. For each area of 1 ha (one with green sugarcane mechanized harvesting and other one with burnt sugarcane manual harvesting), 126 soil samples were collected and subjected to laboratory analysis to determine soil physical, chemical and mineralogical attributes and for measuring of MS. Data were submitted to descriptive statistics by calculating the mean and coefficient of variation. In order to compare the means in the different harvesting management systems it was carried out the Tukey test at a significance level of 5%. In order to investigate the correlation of the MS with other soil properties it was made the correlation test and aiming to assess how the MS contributes to the prediction of soil complex attributes it was made the multiple linear regressions. The results demonstrate that MS showed, in both sugarcane harvesting management systems, statistical correlation with chemical, physical and mineralogical soil attributes and it also showed potential to be used as pedotransfer function to predict attributes of the studied oxisol.
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In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.
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Parameter estimation still remains a challenge in many important applications. There is a need to develop methods that utilize achievements in modern computational systems with growing capabilities. Owing to this fact different kinds of Evolutionary Algorithms are becoming an especially perspective field of research. The main aim of this thesis is to explore theoretical aspects of a specific type of Evolutionary Algorithms class, the Differential Evolution (DE) method, and implement this algorithm as codes capable to solve a large range of problems. Matlab, a numerical computing environment provided by MathWorks inc., has been utilized for this purpose. Our implementation empirically demonstrates the benefits of a stochastic optimizers with respect to deterministic optimizers in case of stochastic and chaotic problems. Furthermore, the advanced features of Differential Evolution are discussed as well as taken into account in the Matlab realization. Test "toycase" examples are presented in order to show advantages and disadvantages caused by additional aspects involved in extensions of the basic algorithm. Another aim of this paper is to apply the DE approach to the parameter estimation problem of the system exhibiting chaotic behavior, where the well-known Lorenz system with specific set of parameter values is taken as an example. Finally, the DE approach for estimation of chaotic dynamics is compared to the Ensemble prediction and parameter estimation system (EPPES) approach which was recently proposed as a possible solution for similar problems.
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The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.
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This thesis presents an approach for formulating and validating a space averaged drag model for coarse mesh simulations of gas-solid flows in fluidized beds using the two-fluid model. Proper modeling for fluid dynamics is central in understanding any industrial multiphase flow. The gas-solid flows in fluidized beds are heterogeneous and usually simulated with the Eulerian description of phases. Such a description requires the usage of fine meshes and small time steps for the proper prediction of its hydrodynamics. Such constraint on the mesh and time step size results in a large number of control volumes and long computational times which are unaffordable for simulations of large scale fluidized beds. If proper closure models are not included, coarse mesh simulations for fluidized beds do not give reasonable results. The coarse mesh simulation fails to resolve the mesoscale structures and results in uniform solids concentration profiles. For a circulating fluidized bed riser, such predicted profiles result in a higher drag force between the gas and solid phase and also overestimated solids mass flux at the outlet. Thus, there is a need to formulate the closure correlations which can accurately predict the hydrodynamics using coarse meshes. This thesis uses the space averaging modeling approach in the formulation of closure models for coarse mesh simulations of the gas-solid flow in fluidized beds using Geldart group B particles. In the analysis of formulating the closure correlation for space averaged drag model, the main parameters for the modeling were found to be the averaging size, solid volume fraction, and distance from the wall. The closure model for the gas-solid drag force was formulated and validated for coarse mesh simulations of the riser, which showed the verification of this modeling approach. Coarse mesh simulations using the corrected drag model resulted in lowered values of solids mass flux. Such an approach is a promising tool in the formulation of appropriate closure models which can be used in coarse mesh simulations of large scale fluidized beds.
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PURPOSE: The aim of this longitudinal study was to investigate the value of uterine artery Doppler sonography during the second and third trimesters in the prediction of adverse pregnancy outcome in low-risk women. METHODS: From July 2011 to August 2012, a total of 205 singleton pregnant women presenting at our antenatal clinic were enrolled in this prospective study and were assessed for baseline demographic and obstetric data. They underwent ultrasound evaluation at the time of second and third trimesters, both included Doppler assessment of bilateral uterine arteries to determine the values of the pulsatility index (PI) and resistance index (RI) and presence of early diastolic notch. The endpoint of this study was assessing the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of Doppler ultrasonography of the uterine artery, for the prediction of adverse pregnancy outcomes including preeclampsia, stillbirth, placental abruption and preterm labor. RESULTS: The mean age of cases was 26.4±5.11. The uterine artery PI and RI values for both second (PI: 1.1±0.42 versus 1.53±0.59, p=0.002; RI: 0.55±0.09 versus 0.72±0.13, p=0.000 respectively) and third-trimester (PI: 0.77±0.31 versus 1.09±0.46, p=0.000; RI: 0.46±0.10 versus 0.60±0.14, p=0.010 respectively) evaluations were significantly higher in patients with adverse pregnancy outcome than in normal women. Combination of PI and RI >95th percentile and presence of bilateral notch in second trimester get sensitivity and specificity of 36.1 and 97% respectively, while these measures were 57.5 and 98.2% in third trimester. CONCLUSIONS: According to our study, it seems that uterine artery Doppler may be a valuable tool for the prediction of a variety of adverse outcomes in second and third trimesters.