Managing complexity： A problem of chaos in fisheries policy

This work intends to present chaos theory （and dynamical systems such as the theories of complexity）, in terms of interpretation of ecological phenomena. The chaos theory applied in the context of ecological systems, especially in the context of fisheries has allowed the recognition of the relevance of this kind of theories to explain fishing phenomena and fisheries policies. It has permitted new advances in the study of marine systems, contributing to the preservation of fish stocks. This paper deals with the way how to manage fisheries taking chaos in account of the problem.     

Digital Signatures

Abstract

The growing use of the Internet for business makes digital signatures a crucial issue. This article discusses three methods used in digital signatures: symmetric encryption, asymmetric encryption and signature dynamics. In addition, the need for consistent laws governing digital signatures in all of the United States, and indeed in the world, is discussed.     

基于混沌理论的网络舆论事件风险评估

网络媒体具有及时性、交互性、开放性等特点,使得网络舆论的产生、形成和发展与传统媒体舆论有着许多不同的特点。对网络舆论事件的风险进行评估,进而采取有效措施对舆论事件进行正确的引导、处置和管理,是有效化解网络舆论危机的一种新方法。本文基于混沌理论角度,对网络舆论事件风险的混沌特性进行研究,并重点探讨基于混沌理论的网络舆论事件风险评估原理。     

On designing economic agents that behave like human agents

This paper explores the idea of constructing theoretical economic agents that behave like actual human agents and using them in neoclassical economic models. It does this in a repeated-choice setting by postulating artificial agents who use a learning algorithm calibrated against human learning data from psychological experiments. The resulting calibrated algorithm appears to replicate human learning behavior to a high degree and reproduces several stylized facts of learning. It can therefore be used to replace the idealized, perfectly rational agents in appropriate neoclassical models with calibrated agents that represent actual human behavior. The paper discusses the possibilities of using the algorithm to represent human learning in normal-form stage games and in more general neoclassical models in economics. It explores the likelihood of convergence to long-run optimality and to Nash behavior, and the characteristic learning time implicit in human adaptation in the economy.     

混沌的证券市场与混沌操作法

证券市场以其价格的频繁波动，吸引了大量投资者，但长期以来人们一直在有效市场等经典理论的指导下进行交易，故始终不能稳定获利。本文介绍了一种基于混沌理论的新方法－－混沌操作法，能使投资者从新的角度把握市场，从而轻松交易，稳定获利。     

投入产出优化模型的发展与创新机遇

投入产出优化模型是投入产出分析研究与应用的方向之一。常用的与投入产出模型相结合建立最优化模型的主要方法有线性规划、多目标规划、CGE模型、高速增长模型和现代控制理论等。现代科学技术的快速发展大量渗透到经济学中，灰色系统理论、复杂性科学的发展，特别是现代优化算法如遗传算法、人工神经网络、蚁群算法等的发展，为投入产出优化模型的创新提供了新的机遇。     

人力资源价值模糊计量方法研究

人力资源可作广义和狭义两种理解;人力资源价值本身可以分为内在价值、外在价值和观念价值三个层次。影响人力资源价值的非货币因素有很多,这决定了对人力资源价值的计量除了货币计量方法以外,还应有非货币计量方法。本文拟就人力资源价值非货币计量方法中的模糊计量方法进行探讨研究。     

Stochastic chaos or ARCH effects in stock series?: A comparative study

Recent empirical studies have shown that the chaotic behaviour and excess volatility of financial series are the result of interactions between heterogeneous investors. In our article, we propose verifying this hypothesis. Thus, we use the Chen et al. [Testing for non-linear structure in an artificial financial market. Working Paper, University of Bonn (2000).] model to show that the modification of the agents' homogeneity hypothesis can drive to stochastic chaotic evolution of price series. Then, through an econometric procedure, we try to identify the underlying process of the Paris Stock Exchange returns series (CAC40). To this end, we apply several different tests: (1) dealing with long-memory components derives from the fractional integration test of Geweke and Porter-Hudak (GPH) [J. Time Ser. Anal. 4 (1983) 221.] and (2) dealing with chaotic structures comes from the work on correlation dimension of Grassberger and Procaccia [Physica 9D (1983) 189.] and the Lyapunov exponents method of Gençay and Dechert [Physica D (1992) 142.]. Finally, we forecast the CAC40 returns series using the recent methods of Principal Components Regression (PCR) and Radial Basis Functions (RBF). We conclude with the implications of the presence of chaotic structures in stock markets and future research on ARCH and chaotic models' relationships.     

基于自适应遗传算法的智能组卷的研究

智能组卷是智能计算机辅助教学中一个关键的问题,针对组卷中带约束的多目标优化问题,提出了一种自适应遗传算法,并采用新的编码方式、交叉算子和变异算子,建立了数学模型。实验结果表明,该算法能有效地解决智能组卷问题,具有较好的实用效果。     

基于小生境遗传算法的人工拣货路径优化研究

以某配送中心双区型仓库的拣货作业为研究对象,首先将其人工拣货路径优化问题转化为TSP问题,以此建立拣货路径优化模型。随后采用基于适应值共享的小生境遗传算法,对拣货路径问题进行优化研究。最后采用Matlab仿真证明小生境遗传算法可以有效缩短拣货路径节约拣货时间。