Search

The purpose of the optimum designs is to determine the optimal experimental conditions in terms of minimum variance of the estimated vector of parameters, so that statistical inferences can be generated as accurate as possible. This theory presupposes knowledge of the function relating the explanatory variables with the response variable. In this situation, usually get designs with support points as parameters in the model. Since p-point designs assume that the model function is known, these could not be optimal in some practical situations because they do not allow to test the goodness of fit of the assumed model. In this paper we present a generalization of the methodology proposed by to increase the number of support points in D-optimality criterion. An expression for the variance of the predicted response in terms of a constant δ will be provided, which allow to determine the points to be added to the D-optimal design. We propose a strategy for choosing δ. Finally we provide a pseudo-optimal design with (p + s) support points. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for optimal relocation of transformers in distribution systems. The problem is formulated as an optimization model of multiobjective non-linear integer type, which considers investment and operating costs, and the benefit of the concept of assets to be recognized by usage charges as stipulated in Resolution CREG 097 of 2008. The model is solved using the multiobjective optimization algorithm NSGA II. To check the validity of the methodology, a real distribution system belonging to an electric utility in Colombia is used, which takes into account both single and three phase distribution transformers. The results compared with respect to the case without considering the relocation of distribution transformers, reflect the importance of this methodology and its benefits to the distribution companies, and serves as a support tool for compliance with the standards set by regulatory bodies that define the appropriate chargeability of distribution transformers. [ABSTRACT FROM AUTHOR]

In this paper we identified the best conditions for the removal of Acid Blue 9 dye (AB9) using flower wastes (FW) as an adsorbent were determined using a full factorial 2³ and a Box-Behnken design for further optimization. Adsorbent dose (D), dye concentration (C) and contact time (t), were the assessed variables. The dye content was quantified by UV-Vis spectrometry. The statistical model presented an adequate adjustment coefficient (R² = 99,18%), allowing to achieve a removal of 98,5% with a dosage of 7,8 gL-1, dye concentration of 7,11 mgL-1 and contact time of 104 min. These results suggest that flowers wastes are an alternative and potential adsorbent material for the treatment of dissolved acid dyes. [ABSTRACT FROM AUTHOR]

PCA and LDA are two of most widely used techniques for face recognition with IR images. In this paper we report the results obtained by using Genetics Algorithms for optimization the characteristic vector generated by these techniques, by assignation of weights to each vector according its performance in the classification task. It shows that, under the proposed scheme, is able to obtain a lower classification error compared to conventional method. [ABSTRACT FROM AUTHOR]