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61.
S. Gourvénec 《Analytica chimica acta》2004,519(1):11-21
Multivariate curve resolution (MCR) and especially the orthogonal projection approach (OPA) can be applied to spectroscopic data and were proved to be suitable for process monitoring. To improve the quality of the on-line monitoring of batch processes, it is interesting to get as many as possible spectra in a given period of time. Nevertheless, hardware limitations could lead to the fact that it is not possible to acquire more than a certain number of spectra in this given period of time. Wavelength selection could be a good way to limit this problem since it decreases size, and consequently the acquisition time, of each recorded spectrum. This paper details an industrial application of genetic algorithms (GA) coupled with a curve resolution method (OPA) for such purpose. 相似文献
62.
Priyanka Singh Kilari Jyothsna Devi Hiren Kumar Thakkar Jos Santamaría 《Entropy (Basel, Switzerland)》2021,23(12)
In the past decade, rapid development in digital communication has led to prevalent use of digital images. More importantly, confidentiality issues have also come up recently due to the increase in digital image transmission across the Internet. Therefore, it is necessary to provide high imperceptibility and security to digitally transmitted images. In this paper, a novel blind digital image watermarking scheme is introduced tackling secured transmission of digital images, which provides a higher quality regarding both imperceptibility and robustness parameters. A block based hybrid IWT- SVD transform is implemented for robust transmission of digital images. To ensure high watermark security, the watermark is encrypted using a Pseudo random key which is generated adaptively from cover and watermark images. An encrypted watermark is embedded in randomly selected low entropy blocks to increase the security as well as imperceptibility. Embedding positions within the block are identified adaptively using a Blum–Blum–Shub Pseudo random generator. To ensure higher visual quality, Initial Scaling Factor (ISF) is chosen adaptively from a cover image using image range characteristics. ISF can be optimized using Nature Inspired Optimization (NIO) techniques for higher imperceptibility and robustness. Specifically, the ISF parameter is optimized by using three well-known and novel NIO-based algorithms such as Genetic Algorithms (GA), Artificial Bee Colony (ABC), and Firefly Optimization algorithm. Experiments were conducted for the proposed scheme in terms of imperceptibility, robustness, security, embedding rate, and computational time. Experimental results support higher effectiveness of the proposed scheme. Furthermore, performance comparison has been done with some of the existing state-of-the-art schemes which substantiates the improved performance of the proposed scheme. 相似文献
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64.
Weighted voting systems are widely used in many practical fields such as target detection, human organization, pattern recognition, etc. In this paper, a new model for weighted voting systems with continuous state inputs is formulated. We derive the analytical expression for the reliability of the entire system under certain distribution assumptions. A more general Monte Carlo algorithm is also given to numerically analyze the model and evaluate the reliability. This paper further proposes a reliability optimization problem of weighted voting systems under cost constraints. A genetic algorithm is introduced and applied as the optimization technique for the model formulated. A numerical example is then presented to illustrate the ideas. 相似文献
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为了让证券投资者更好地按照自己的安全标准进行投资,根据PYLE H和TURNOVSKY S J提出的安全第一标准,给出在风险价值(VaR)度量下如何选取到最优证券组合的相关结果.其结论对投资者在选择证券投资组合时具有理论上的参考价值. 相似文献
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Network planning problem typically involves large capital investment and can be formulated as an optimization problem where the objective is minimization of the first installed cost. We consider a passive optical network (PON) planning problem based on a residential area in Adana (Turkey). There are four possible primary node locations, twenty possible secondary node locations, and twenty-eight customers. We use genetic algorithm and mathematical modeling techniques to optimize the position of the primary and secondary nodes, their split levels and assigning customers to secondary nodes and secondary nodes to primary nodes under some constraints such as system’s attenuations and technical characteristics of all the equipment. 相似文献
70.
《Analytical letters》2012,45(7):1145-1154
This paper reports the chemometric predictive models developed for near infrared spectroscopy (NIRS) for the quantitative determination of the kinematic viscosity (37.1–93.1 cSt) of lubricant oils for gear motors. The gear motor is a complete motive force system that consists of an electric motor and a reduction gear train integrated into one easy-to-mount and configure package. The method used for measuring the viscosity of the lubricating oil was ASTM D445, the Standard Test Method for Kinematic Viscosity of Transparent and Opaque Liquids. A comparison was made among several multivariate calibration techniques and algorithms for pre-processing and variable selection of data, including partial least squares, interval partial least squares (iPLS), a genetic algorithm (GA), and a successive projections algorithm. Finally, the results obtained for the root mean square errors of prediction in cSt and relative average error were, respectively, 1.86 and 2.97% (GA) and 2.36 and 2.97% (iPLS). The method proposed in this study is a useful alternative for the determination of the kinematic viscosity in oils for gear motors. 相似文献