金融泡沫理论的研究

“泡沫”(bubbles)一词是近几年来我国经济界较常见的一个词语，常被用于描述经济的虚假繁荣(即泡沫经济)和价格的虚假上涨(即经济泡沫)。它被认为有害于经济而被用于解释经济由繁荣到崩溃(如东南亚和日本经济危机)的原因，或被用于反对(或警示)一国经济的非常规快速发展(如对美国“新经济”的批判)；它也被认为是经济发展的需要,因而是有益的(泡沫不断地产生和破裂促进经济繁荣和优胜劣汰的进行)。 这些关于(或涉及)泡沫的论述(或论证)，它们之间存在着对泡沫的不同理解和因此产生的许多分歧(其中有些甚至是不可调和的)。于是，在这些“一家之言”的出现的同时，形成了泡沫研究上“百家争鸣”的局面，也有了许多关...学位：经济学硕士院系专业：经济学院财政金融系_金融学(含保险学)学号：19981201

论我国金融的“共有地的悲剧”——兼论国有银行产权改革

本文首先引入公共产品理论 ,用于说明我国金融在金融安全和国有银行资产两方面存在的公共产品性并因此而产生的“共有地的悲剧”问题 ;然后 ,引入制度经济学派产权理论对公共产权的分析框架 ,提出通过界定产权化解我国金融“共有地的悲剧”的思路和相应对策

Feeding prescription design with simulated annealing algorithm

本文在饲料配方设计中首次引入新颖、高效的组合优化算法———模拟退火算法 ,并获得理想的数值结果 ,说明了在传统的饲料配方设计中高技术的应用可以获得更高的效益 .A new and efficient combinatorial optimization algorithm——stimulated annealing algorithm is introduced to the application of feeding prescription design. The result is desirable and it shows that the application of the new technology in the traditional feeding prescription design can gain higher efficiency and benefit .教育部高等学校骨干教师资助计划项目;; 厦门大学科学研究基

Feeding Prescription Design with Simulated Annealing Algorithm

高技术、高效益是市场竞争中不可缺少的法宝 ,本文在饲料配方设计中首次引入了新颖、高效的组合优化算法 -模拟退火算法 ,并获得理想的数值结果 ,说明了在传统的饲料配方设计中高技术的应用可以获得更高的效益 .A new and efficient combinatorial optimization algorithm-stimulated annealing algorithm is introduced to the application of feeding prescription design. The result shows that the application of the new technology in the traditional feeding prescription design can gain higher efficiency and benefit.教育部《高等学校骨干教师资助计划》项目;; 国家自然科学基金项目 (60 175 0 0 8);; 福建省自然科学基金资助项目 (A0 110 0 4

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies