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Search Results: 1 - 10 of 37085 matches for " Limei Yan "
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Chance-constrained Portfolio Selection with Birandom Returns
Limei Yan
Modern Applied Science , 2009, DOI: 10.5539/mas.v3n4p161
Abstract: The aim of this paper is to solve the portfolio problem when security returns are birandom variables. Two types of portfolio selection based on chance measure are provided according to birandom theory. Since the proposed optimization problems are difficult to solve by traditional methods, a hybrid intelligent algorithm by integrating birandom simulation and genetic algorithm is designed. Finally, two numerical experiments are provided to illustrate the effectiveness of the algorithm.
One Type of Optimal Portfolio Selection in Birandom Environments
Limei Yan
Modern Applied Science , 2009, DOI: 10.5539/mas.v3n6p126
Abstract: In order to solve the portfolio problem when security returns are birandom variables, firstly we propose a new definition of risk, then one type of portfolio selection based on expected value and risk is provided according to birandom theory. Furthermore, A hybrid intelligent algorithm by integrating birandom simulation and genetic algorithm is designed. Finally, one numerical experiment is provided to illustrate the effectiveness of the hybrid intelligent algorithm.
Optimal Portfolio Selection Models with Uncertain Returns
Limei Yan
Modern Applied Science , 2009, DOI: 10.5539/mas.v3n8p76
Abstract: This paper provides two new models for portfolio selection in which the securities are assumed to be uncertain variables that are neither random nor fuzzy. Since there is no efficient method to solve the proposed models, the original problems are transformed into their crisp equivalents programming when the returns are chosen some special uncertain variables such as rectangular uncertain variable, triangular uncertain variable, trapezoidal uncertain variable and normal uncertain variable. Finally, its feasibility and effectiveness of the method is illustrated by numerical example.
Optimal Programming Models for Portfolio Selection with Uncertain Chance Constraint
Limei Yan
Modern Applied Science , 2009, DOI: 10.5539/mas.v3n9p84
Abstract: The paper is concerned with the portfolio selection problem about how to assign one’s money in security market in order to obtain the maximal profit. One type expected maximization programming model with chance constraint in which the security returns are uncertain variables are proposed in accordance with uncertainty theory. Since the provided models can not be solved by the traditional methods, the crisp equivalents of the corresponding models are discussed when the uncertain returns are chosen as some special cases such as linear uncertain variables, trapezoidal uncertain variables and normal uncertain variables. Two numerical examples with different types of uncertain variables are given in order to demonstrate the effectiveness and feasibility of the proposed programming models. Finally, the paper gives the conclusion.
Chance-constrained Programming Model for Portfolio Selection in Uncertain Environment
Limei Yan
Modern Applied Science , 2009, DOI: 10.5539/mas.v3n10p89
Abstract: The purpose of this paper is to solve the portfolio problem when security returns are uncertain variables. Two types of portfolio selection programming models based on uncertain measure are provided according to uncertain theory. Since the proposed optimization problems are generally difficult to solve by conventional methods, the models are converted to their crisp equivalents when the return rates are adopted some special uncertain variables such as linear uncertain variable, trapezoidal uncertain variable and normal uncertain variable. Thus the transformed models can be completed by the conventional methods. In the end of the paper, one numerical experiment is provided to illustrate the effectiveness of the method.
A Study on Research Teaching
Limei Yan
International Education Studies , 2010, DOI: 10.5539/ies.v3n1p192
Abstract: Starting with the significance and the conduction of research teaching, this paper further puts forward and analyzes several patterns of research teaching, discusses the particular role of teachers in these patterns and proposes some strategies as well as suggestions.
Risk Curve and Bifuzzy Portfolio Selection
Limei Yan
Journal of Mathematics Research , 2009, DOI: 10.5539/jmr.v1n2p193
Abstract: In order to solve the portfolio problem when security returns are bifuzzy variables, firstly we propose a new definition of risk, then one type of portfolio selection based on expected value and risk is provided according to bifuzzy theory. Furthermore, a hybrid intelligent algorithm by integrating bifuzzy simulation and genetic algorithm is designed. Finally, one numerical experiment is provided to illustrate effectiveness of the hybrid intelligent algorithm.
Development of High Efficient and Low Toxic Oil Spill Dispersants based on Sorbitol Derivants Nonionic Surfactants and Glycolipid Biosurfactants  [PDF]
Dandan Song, Shengkang Liang, Qianqian Zhang, Jiangtao Wang, Limei Yan
Journal of Environmental Protection (JEP) , 2013, DOI: 10.4236/jep.2013.41B004
Abstract: Dispersants, usually blending with several surfactants and a solvent, are used to enhance oil spill dispersion as small droplets in water column. Although there is growing acceptance of dispersants as a counter measure to marine oil spills around the world, the two major issues with the dispersants are their toxicity to marine life and dispersion effectiveness (DE) for crude-oil, especially for heavy oil. To develop more efficient and less toxic dispersants, two kinds of sorbitol derivant nonionic surfactant (polysorbate 85 and sorbeth-40 tetraoleate), two kinds of glycolipid biosurfactants (rhamnolipid and sophorolipid) and less toxic solvent ethylene glycol butyl ether were chosen in this study, and two dispersant formulations were optimized by uniform design methods. Effects of dispersant-to-oil ratio, temperature, salinity and pH on the performance of the two optimized dispersants were investigated. The two dispersants had high dispersion effectiveness (DE) for heavy crude oil, while both dispersants keep high DE at the dispersant-to-oil ratio below 1:25 and the temperature above 5 ℃. In addition, the two dispersants also performed well in a wide range of salinity and pH values. Finally, toxicity tests revealed that the two dispersants showed low toxicity to two kinds of fish (Danio rerio and Microgobius gulosus).

 

Meromorphic Functions Sharing Three Values  [PDF]
Changjun Li, Limei Wang
Applied Mathematics (AM) , 2011, DOI: 10.4236/am.2011.26095
Abstract: In this paper, we prove a result on the uniqueness of meromorphic functions sharing three values counting multiplicity and improve a result obtained by Xiaomin Li and Hongxun Yi.
AtEXP2 Is Involved in Seed Germination and Abiotic Stress Response in Arabidopsis
An Yan, Minjie Wu, Limei Yan, Rui Hu, Imran Ali, Yinbo Gan
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0085208
Abstract: Expansins are cell wall proteins that promote cell wall loosening by inducing pH-dependent cell wall extension and stress relaxation. Expansins are required in a series of physiological developmental processes in higher plants such as seed germination. Here we identified an Arabidopsis expansin gene AtEXPA2 that is exclusively expressed in germinating seeds and the mutant shows delayed germination, suggesting that AtEXP2 is involved in controlling seed germination. Exogenous GA application increased the expression level of AtEXP2 during seed germination, while ABA application had no effect on AtEXP2 expression. Furthermore, the analysis of DELLA mutants show that RGL1, RGL2, RGA, GAI are all involved in repressing AtEXP2 expression, and RGL1 plays the most dominant role in controlling AtEXP2 expression. In stress response, exp2 mutant shows higher sensitivity than wild type in seed germination, while overexpression lines of AtEXP2 are less sensitive to salt stress and osmotic stress, exhibiting enhanced tolerance to stress treatment. Collectively, our results suggest that AtEXP2 is involved in the GA-mediated seed germination and confers salt stress and osmotic stress tolerance in Arabidopsis.
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