建筑工业化发展的多群体演化博弈与仿真研究

新型建筑工业化具有高质量、低消耗、可循环发展等特征，其推广已上升到国家战略层面。利用演化博弈方法，建立“政府-开发商-银行” 的三方动态演化博弈模型，进行各博弈主体策略的演化稳定性分析，并针对初始状态、奖惩力度、借贷风险和开发成本等对演化结果的影响进行动态仿真。在此基础上， 考虑开发商群体的网络拓扑特征对演化真实性的影响，引入复杂网络理论， 以无标度网络为载体描述开发商个体的连接偏好和决策机制，构建政府监管下的建筑工业化扩散模型，并通过仿真深入研究相关因素对扩散深度的影响作用，最后结合仿真结果给出相应对策建议。     

Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex

This study demonstrates the application of an improved Evolutionary optimization Algorithm (EA), titled Multi-Objective Complex Evolution Global Optimization Method with Principal Component Analysis and Crowding Distance Operator (MOSPD), for the hydropower reservoir operation of the Oroville–Thermalito Complex (OTC) – a crucial head-water resource for the California State Water Project (SWP). In the OTC's water-hydropower joint management study, the nonlinearity of hydropower generation and the reservoir's water elevation–storage relationship are explicitly formulated by polynomial function in order to closely match realistic situations and reduce linearization approximation errors. Comparison among different curve-fitting methods is conducted to understand the impact of the simplification of reservoir topography. In the optimization algorithm development, techniques of crowding distance and principal component analysis are implemented to improve the diversity and convergence of the optimal solutions towards and along the Pareto optimal set in the objective space. A comparative evaluation among the new algorithm MOSPD, the original Multi-Objective Complex Evolution Global Optimization Method (MOCOM), the Multi-Objective Differential Evolution method (MODE), the Multi-Objective Genetic Algorithm (MOGA), the Multi-Objective Simulated Annealing approach (MOSA), and the Multi-Objective Particle Swarm Optimization scheme (MOPSO) is conducted using the benchmark functions. The results show that best the MOSPD algorithm demonstrated the best and most consistent performance when compared with other algorithms on the test problems. The newly developed algorithm (MOSPD) is further applied to the OTC reservoir releasing problem during the snow melting season in 1998 (wet year), 2000 (normal year) and 2001 (dry year), in which the more spreading and converged non-dominated solutions of MOSPD provide decision makers with better operational alternatives for effectively and efficiently managing the OTC reservoirs in response to the different climates, especially drought, which has become more and more severe and frequent in California.     

A semantic modeling approach for image retrieval by content

We introduce a semantic data model to capture the hierarchical, spatial, temporal, and evolutionary semantics of images in pictorial databases. This model mimics the user's conceptual view of the image content, providing the framework and guidelines for preprocessing to extract image features. Based on the model constructs, a spatial evolutionary query language (SEQL), which provides direct image object manipulation capabilities, is presented. With semantic information captured in the model, spatial evolutionary queries are answered efficiently. Using an object-oriented platform, a prototype medical-image management system was implemented at UCLA to demonstrate the feasibility of the proposed approach.     

DNA序列比对分析中的统计特征方法

提出了一种新的基于统计的序列特征定义,并以此对进化树进行构建.同时对这一方法进行了分类测试和进化树构建测试,发现所得测试结果与同样是用进化树进行构建的基于两序列比对的传统算法比较,其性能和适用性都有明显改善.     

多约束的桥梁结构拓扑优化

基于ESO (Evolutionary Structural Optimization)的拓扑优化方法,本文提出了一种适应于桥梁结构的拓扑优化方法。引进了两种性能指标公式来确定最佳拓扑设计。另外,为了更有效地尝试改进最终设计的细节,而又不进行更精细有限元网格的完整分析,这里提出了一种精细网络设计方案。再者,结合细啃技术,完成了考虑应力、位移、频率约束的斜拉桥优化设计。通过几种桥梁的设计优化,表明该方法的可应用性、简洁性和有效性。     

基于TS101型DSP链路口的多通道高精度数据采集电路设计

介绍一种基于数字信号处理器(DSP)TS101链路口的多通道高精度数据采集电路的设计方法,详细阐述利用多个ADS8361型A/D转换器进行数据采集,并经TS101链路口传输数据的FP-GA和DSP设计实现,讨论如何提高A/D转换精度的问题.     

Minimum spanning trees made easier via multi-objective optimization

Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate the Pareto front, multi-objective optimization problems are considered as more difficult than single-objective problems. One should not forget that the fitness vector with respect to more than one objective contains more information that in principle can direct the search of evolutionary algorithms. Therefore, it is possible that a single-objective problem can be solved more efficiently via a generalized multi-objective model of the problem. That this is indeed the case is proved by investigating the computation of minimum spanning trees.This work was supported by the Deutsche Forschungsgemeinschaft (DFG) as part of the Collaborative Research Center Computational Intelligence (SFB 531) and by the German-Israeli Foundation (GIF) in the project Robustness Aspects of Algorithms.     

一种新的基于极大似然估计的系统辨识方法

进化计算是一种基于自然选择和自然变异机制的并行随机优化算法。由于递推极大似然估计法难以实现性能指标函数的全局寻优，所以本文提出了将改进的进化计算用于系统参数辨识的方法。计算机仿真结果表明，该算法能够实现似然函数的全局寻优。     

添加微量铝对TS-2合成及苯酚羟基化的影响

以硅溶胶为硅源合成分子筛TS 2时 ,在溶胶制备过程中添加微量的铝 ,可以降低模板剂氢氧化四丁基铵 (TBAOH)的用量 ,当TBAOH/SiO2 降低到 0 .1以下时 ,仍然合成了性能优良的TS 2 ,而且用于苯酚过氧化氢羟基化反应过程中催化活性也大大提高。所得催化剂用XRD ,IR ,ICP进行了表征