997 resultados para Offline optimization


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This paper describes the optimization of dose of methyltestosteronei (MT) hormone for masculinization of tilapia (Oreochromis niloticus). Five treatments (i.e. T1 T2, T2, T4 and T5) with different doses such as 0, 40, 50, 60 and 65 mg of MT hormone were mixed with per kg of feed for each treatment and fed the fry four times a day up to satiation for a period of 30 days. The stocking density was maintained 10 spawn/liter of water. The growth of fry at different treatments was recorded weekly and mortality was recorded daily. At the end of hormone feeding the fry were reared in hapas fixed in ponds for another 70 days and at the 100th day the fish were sexed by the gonad squashing and aceto-carmine staining method. The analysis of growth data did not show any significant variation in length and weight of fish among the different treatments. High mortality of fry ranging 66% to 81.6% was observed in different treatments and highest mortality was observed during the first twelve days of the experiment. The sex ratio analysis showed that T2 (40 mg/kg) and T5 (65 mg/kg) produced 93.33% of sex reversed male and T3 (50 mg/kg) and T4 (60 mg/kg) produced 96.66% sex reversed male, and these ratios were significantly (p<0.05) different from 1:1 male: female sex ratio. The control, T1 (0 mg/kg) contained 43.33% male progeny. From these results it is suggested that either 50 mg/kg or 60 mg/kg of MT with a feeding period of 30 days could be considered as an optimum dose for masculinization of tilapia (O. niloticus).

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Detailed investigations of the effectiveness of three widely adopted optical orthogonal frequency division multiplexing (OOFDM) adaptive loading algorithms, including power loading (PL), bit loading (BL), and bit-and-power loading (BPL), are undertaken, over < 100km single-mode fibre (SMF) system without incorporating inline optical amplification and chromatic dispersion (CD) compensation. It is shown that the BPL (PL) algorithm always offers the best (worst) transmission performance. The absolute transmission capacity differences between these algorithms are independent of transmission distance and launched optical power. Moreover, it is shown that in comparison with the most sophisticated BPL algorithm, the simplest PL algorithm is effective in escalating the OOFDM SMF links performance to its maximum potential. On the other hand, when employing a large number of subcarriers and a high digital-to-analogue DAC)/analogue-to-digital (ADC) sampling rate, the sophisticated BPL algorithm has to be adopted. © 2011 IEEE.

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Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.