我国2002年GDP能否保持高增长

本文以 1 980年至 1 999年全社会固定资产投资、社会消费品零售总额、净出口总额为输入变量 ,以GDP及商品零售价格为输出变量 ,建立宏观经济神经网络模型 ,并采用遗传算法搜索寻优 ,结合宏观经济分析 ,对 2 0 0 2年的价格水平、GDP增长率、各输入变量的增长关系进行预测 ,获得了一些有意义的结果     

松下村塾教育的历史断想

主宰松下村塾的吉田松阴,以因材适教,因人施教,尊重个性的教育活动,为日本教育界谱写了历史性的一页。他采用中国古典中的经史子集为主要教材之一,从有形的知识教育升华到无形的人生教育。他认为:在松下村塾的学习是一种人生生存。为了完善这一人生生存,必须为自己找到一个社会性的角色;必须在时空的社会舞台中找到自己,进而朔造自己,最后贡献自己.这就是松下村塾的教育。     

遗传算法在"动态路由"问题上的应用

研究遗传算法在动态路由的技术上的应用。针对一类多约束目标的优化算法中的各方面进行详细的讨论与深入分析,并给出一种基于遗传算法的动态路由策略解决方案。     

分布式水循环模型的参数优化算法比较及应用

分布式水文模型的优势在于还原水文过程的时空变异性,可以很好地模拟和反映各种水文要素和下垫面因素的时空分布不均匀性。由此也导致模型参数过多,在子流域过多的情况下,人工调节参数繁琐复杂,应用优化算法实现参数自动调节成为首选。本文选取石羊河流域九条岭站1988-2005年实测径流资料,分别应用SCE-UA算法、遗传算法(GA)和粒子群算法(PSO)对分布式水循环模型(时变增益模型)进行参数率定,对比3种算法的收敛速度、所需迭代次数和算法稳定性。结果表明:通过SCE-UA、GA和PSO的优化,模型水平衡系数都控制在0.0左右,而相关系数和效率系数分别能达到0.90和0.84以上,模拟精度较好。但粒子群算法的全局搜索能力和收敛速度优于SCE-UA和遗传算法,所需迭代次数最少,初值敏感性小,更适合时变增益模型的参数寻优,有很高的扩展性和改进潜力。     

基于遗传程序设计的机构创新设计

遗传程序设计（GP）是在遗传算法（GA）的基础上提出的,是一种借鉴生物界自然选择思想和遗传机制的全局随机搜索算法。机构创新设计的目标是产生符合设计要求的新机构,将GP应用于机构构型创新设计中,进行机构创新设计的研究,探讨机构构型设计的新理论与新方法。     

Simultaneous removal of ethyl acetate,benzene and toluene with gliding arc gas discharge

The simultaneous removal of ethyl acetate, benzene and toluene with relatively low or high initial concentration is studied using a laboratory scale gliding arc gas discharge （GA） reactor. Good decomposition efficiencies are obtained which proves that the GA is effective for the treatment of volatile organic compounds （VOCs） with either low or high concentration. A theoretical decomposition mechanism is proposed based on detection of the species in the plasma region and analysis of the decomposition by-products. This preliminary investigation reveals that the GA has potential to be applied to the treatment of exhaust air during color printing and coating works, by either direct removal or combination with activated carbon adsorption/desorption process.     

初始水权分配中的主从对策研究

通过对初始水权分配一般模式的研究,针对现有的两个水权分配机制,提出初始水权分配是一个以集中机制为主,市场机制为辅的协商过程,即一主和多从的主从对策问题。建立管理部门为主者、用户为从者且相互独立的初始水权分配模型,并应用遗传算法对该模型进行仿真计算,得出满意解。     

电机伺服系统基于遗传算法的H∞控制器优化设计

首先,介绍了永磁同步电机位置伺服系统的组成,给出了电机系统的数学模型,并采用参数辨识的方法得到了系统的传递函数。然后,针对系统中存在的不确定性,运用混合灵敏度方法进行了H∞鲁棒控制器设计。为了使系统达到给定的性能指标要求,采用遗传算法对加权函数的选择进行了优化,从而获得了性能优化的H∞控制器。最后,仿真实验验证了该方法的有效性。     

Optimum allocation of FACTS devices in Fars Regional Electric Network using genetic algorithm based goal attainment

This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission system （FACTS） devices in a power system using a multi-objective optimization function. Thyristor controlled series compensators （TCSCs） and static var compensators （SVCs） are the utilized FACTS devices. Our objectives are active power loss reduction, newly introduced FACTS devices cost reduction, voltage deviation reduction, and increase on the robustness of the security margin against voltage collapse. The operational and controlling constraints, as well as load constraints, were considered in the optimum allocation. A goal attainment method based on the genetic algorithm （GA） was used to approach the global optimum. The estimated annual load profile was utilized in a sequential quadratic programming （SQP） optimization sub-problem to the optimum siting and sizing of FACTS devices. Fars Regional Electric Network was selected as a practical system to validate the performance and effectiveness of the proposed method. The entire investment of the FACTS devices was paid offand an additional 2.4% savings was made. The cost reduction of peak point power generation implies that power plant expansion can be postponed.     

Low-cost fault tolerance in evolvable multiprocessor systems: a graceful degradation approach

The evolvable multiprocessor （EvoMP）, as a novel multiprocessor system-on-chip （MPSoC） machine with evolvable task decomposition and scheduling, claims a major feature of low-cost and efficient fault tolerance. Non-centralized control and adaptive distribution of the program among the available processors are two major capabilities of this platform, which remarkably help to achieve an efficient fault tolerance scheme. This letter presents the operational as well as architectural details of this fault tolerance scheme. In this method, when a processor becomes faulty, it will be eliminated of contribution in program execution in remaining run-time. This method also utilizes dynamic rescheduling capability of the system to achieve the maximum possible efficiency after processor reduction. The results confirm the efficiency and remarkable advantages of the proposed approach over common redundancy based techniques in similar systems.