Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Controlador preditivo não linear aplicado ao controle de golfadas em processos de produção de petróleo

Slugging is a well-known slugging phenomenon in multiphase flow, which may cause problems such as vibration in pipeline and high liquid level in the separator. It can be classified according to the place of its occurrence. The most severe, known as slugging in the riser, occurs in the vertical pipe which feeds the platform. Also known as severe slugging, it is capable of causing severe pressure fluctuations in the flow of the process, excessive vibration, flooding in separator tanks, limited production, nonscheduled stop of production, among other negative aspects that motivated the production of this work . A feasible solution to deal with this problem would be to design an effective method for the removal or reduction of the system, a controller. According to the literature, a conventional PID controller did not produce good results due to the high degree of nonlinearity of the process, fueling the development of advanced control techniques. Among these, the model predictive controller (MPC), where the control action results from the solution of an optimization problem, it is robust, can incorporate physical and /or security constraints. The objective of this work is to apply a non-conventional non-linear model predictive control technique to severe slugging, where the amount of liquid mass in the riser is controlled by the production valve and, indirectly, the oscillation of flow and pressure is suppressed, while looking for environmental and economic benefits. The proposed strategy is based on the use of the model linear approximations and repeatedly solving of a quadratic optimization problem, providing solutions that improve at each iteration. In the event where the convergence of this algorithm is satisfied, the predicted values of the process variables are the same as to those obtained by the original nonlinear model, ensuring that the constraints are satisfied for them along the prediction horizon. A mathematical model recently published in the literature, capable of representing characteristics of severe slugging in a real oil well, is used both for simulation and for the project of the proposed controller, whose performance is compared to a linear MPC

Esverdeamento em cultivares de batata avaliado pela escala visual e índice spad

Foi avaliado o esverdeamento em tubérculos de cultivares de batata utilizando dois métodos de determinação (escala visual de notas e índice spad). Utilizou-se o delineamento experimental inteiramente casualizado, com quatro repetições, em esquema fatorial 18 x 5, constituído por cultivares (Agata, Apuã (IAC-5977), Aracy (IAC-2), IAC Aracy Ruiva, Asterix, Bintje, Dali, Clone IAC-6090, Itararé (IAC-5986), Laguna, Remarka, Liseta, Mondial, Novita, Oscar, Picasso, Santana e Solide) e tempo de armazenamento (5; 10; 15; 20 e 25 dias). Todas as cultivares apresentaram desempenho linear e crescente pelo índice spad, com excecão da Bintje, com spad médio de 1,23. Pela escala visual, as cultivares apresentaram desempenho quadrático e linear. A cultivar Bintje é resistente ao esverdeamento determinado pelos dois métodos. O índice spad pode ser utilizado para determinação do esverdeamento do 10º ao 25º dia de armazenamento.

Crescimento aéreo e radicular de arroz de terras altas em função da adubação fosfatada e bioestimulante

The use of plant regulators that stimulate root growth can increase phosphorus uptake by upland rice. The objective of this study was to evaluate shoot and root growth of upland rice fertilized with different phosphorus doses with and without biostimulant. The experiment was carried out in greenhouse in the Faculdade de Ciencias Agronomicas-UNESP, in Botucatu-SP. The treatments consisted of six phosphorus doses applied in sowing (0, 12,5, 25, 50, 100 and 200 mg dm(-3)), with and without Stimulate (R) applied in the seeds (cv. Primavera). The plants were grown for 78 days and then cut at soil level to evaluate leaf area and leaves and collar dry matter. Root samples that were harvested on the same day had their root diameter and dry matter evaluated. The experimental design was the completely randomized, with three replications, arranged as a factorial 2x6. Variance analysis and regression were used to data evaluation. Linear and quadratic equations were adjusted at a probability level of 5%, using those with higher determination coefficient (R(2)). The increase on the phosphorus dose contributed to the lower matter production and leaf area of the plants when the biostimulant was applied. For shoot phosphorus accumulation and root evaluations, the same behavior was observed. It was concluded that the use of Stimulate (R) in seeds, for fitomass production or root system evaluation, was only efficient in low phosphorus doses.