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排序方式： 共有201条查询结果，搜索用时 15 毫秒
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Abstract. In situ feeding habits of the cyclopoid copepods Oncaea venusta, Corycaeus amazonicus, Oithona plumifera , and O. simplex were investigated by scanning electron microscope examination of fecal pellets, the contents of which reflected copepod gut contents upon capture. Peilet contents were compared with assemblages of phytoplankton present in surface waters at times of copepod collection. All samples were from the northern Gulf of Mexico. All four copepods fed upon phytoplankton and O. venusta also ingested other crustaceans. Dominant components of fecal pellets generally did not mirror those of available phytoplankton assemblages. In some cases, O. venusta ingested primarily larger-sized particles even when these were not most abundant, and in other cases it did not ingest large cells even when they were present in bloom concentrations. The presence of small (< 2–5 urn diameter) centric diatoms in O. venusta pellets suggests the possibility of feeding by mechanisms other than suspension or raptorial feeding. Limited observations suggest that C. amazonicus and O. plumifera may feed raptorially on larger particles even when these are not particularly abundant, and that the small O. simplex (< 500 nm total length) feeds mainly upon nanoplankton. It appears that cyclopoid feeding mechanisms are complex, and likely more so than those of many calanoids. 相似文献
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The generalized model of differential hysteresis contains 13 control parameters with which it can curve‐fit practically any hysteretic trace. Three identification algorithms are developed to estimate the control parameters of hysteresis for different classes of inelastic structures. These algorithms are based upon the simplex, extended Kalman filter, and generalized reduced gradient methods. Novel techniques such as global search and internal constraints are incorporated to facilitate convergence and stability. Effectiveness of the devised algorithms is demonstrated through simulations of two inelastic systems with both pinching and degradation characteristics in their hysteretic traces. Owing to very modest computing requirements, these identification algorithms may become acceptable as a design tool for mapping the hysteretic traces of inelastic structures. Copyright © 2002 John Wiley & Sons, Ltd. 相似文献
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遗传算法与单纯形法组合的影像纹理分类方法 总被引：7，自引：3，他引：7
提出遗传算法(简称GA)与单纯形法组合的影像纹理分类方法(简称GASPX)。单纯形法是一种局部搜索方法，它通过反射，扩张，收缩操作，求得新的单纯形点，组成新单纯形，新单纯形比前一个单纯形更接近局部最优解。这种寻优方法收敛速度快，它与GA组合起来可以改善单独使用GA收敛速度慢的缺陷。由于在组合算法中是多个单纯形的局部区域的并行搜索，避免GA优化过程中过早收敛于局部最优解的现象出现。通过5种不同类别航空影像纹理识别的试验，并与GA的结果作对比，结果表明GASPX法优于GA法。 相似文献
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柏传志 《南京气象学院学报》2003,26(2):281-284
在一致凸Banach(巴拿赫)空间中研究了渐近非扩张映射的带误差的Ishikawa迭代序列的收敛性。结果推广了原来的定理。 相似文献
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K. Ponnambalam A. Vannelli T. E. Unny 《Stochastic Environmental Research and Risk Assessment (SERRA)》1989,3(1):17-29
Optimization of multi-reservoir systems operations is typically a very large scale optimization problem. The following are the three types of optimization problems solved using linear programming (LP): (i) deterministic optimization for multiple periods involving fine stage intervals, for example, from an hour to a week (ii) implicit stochastic optimization using multiple years of inflow data, and (iii) explicit stochastic optimization using probability distributions of inflow data. Until recently, the revised simplex method has been the most efficient solution method available for solving large scale LP problems. In this paper, we show that an implementation of the Karmarkar's interior-point LP algorithm with a newly developed stopping criterion solves optimization problems of large multi-reservoir operations more efficiently than the simplex method. For example, using a Micro VAX II minicomputer, a 40 year, monthly stage, two-reservoir system optimization problem is solved 7.8 times faster than the advanced simplex code in MINOS 5.0. The advantage of this method is expected to be greater as the size of the problem grows from two reservoirs to multiples of reservoirs. This paper presents the details of the implementation and testing and in addition, some other features of the Karmarkar's algorithm which makes it a valuable optimization tool are illuminated. 相似文献