中国的枸橼

枸橼在我国有11个类型(变种、品种或杂种),根据它们的地理分布和植物学性状,认为枸橼的原发中心在云南的西南部和西部;野生的沧源香橼是枸橼的原始类型,由其演化为小香橼、小果香橼和栽培的大香橼等;佛手是由枸橙演化而来。     

车辆半主动悬架新型控制算法的研究

车辆1/4悬架模型不能反映车辆的俯仰情况,且一般控制算法多以簧载质量加速度作为反馈,具有一定的局限性。为更好地改善悬架性能,本文建立了车辆1/2半主动悬架4自由度模型,针对悬架为一非线性、有时滞、不确定系统,提出了一种新型控制算法(在模糊控制的基础上引入PID控制),且在MATLAB中分别进行了时域和频域仿真,并就簧载质量加速度、悬架动挠度、轮胎动载荷与被动悬架、模糊控制半主动悬架进行比较。结果表明,该算法对簧载质量加速度、悬架动挠度、轮胎动载荷的改善非常有效,对车辆悬架的控制和开发具有较大的参考价值。     

Inverse Modeling to Quantify Irrigation System Characteristics and Operational Management

Remotely sensed (RS) data is a major source to obtain spatialdata required for hydrological models. The challenge for thefuture is to obtain besides the more direct observable data(landcover, leaf area index, digital elevation model andevapotranspiration), non-visible data such as soilcharacteristics, groundwater depth and irrigation practices.In this study we have explore the option of using inversemodeling to obtain these non-RS-visible data. For a commandarea in Haryana, India, we applied for the 2000–2001 rabiseason a RS-GIS-combined inverse modeling approach to derivenon-RS-visible data required in the regional application ofhydrological models. A Genetic Algorithm loaded stochasticphysically based soil-water-atmosphere-plant model (SWAP) wasdeveloped for the inverse problem and used in the study. Theresults showed good agreement with the inventoried data suchas soil hydraulic properties, sowing dates, groundwaterdepths, irrigation practices and water quality. The deriveddata could be used to predict the state of the system at anytime in the cropping season, which can be used to evaluateoperational management strategies.     

遗传算法在离心泵叶片优化设计中的应用

对遗传算法在流体机械优化设计中的应用现状作了较为全面的总结；提出了将遗传算法应用于离心泵叶片优化设计中，分析了遗传算法在离心泵优化设计中应用的可行性以及存在的问题；对离心泵优化设计的发展提出了一些新建议和尝试。     

记忆指导模拟退火算法的研究

提出了改进模拟退火算法的记忆指导模拟退火算法。该算法能够利用已知信息对搜索过程进行指导，提高算法的搜索效率，该法对回火退火算法的计算量减少５０％。     

分类规则挖掘算法综述

分类规则挖掘是数据挖掘中一个重要的研究领域.通过介绍当前数据挖掘中具有代表性的分类算法,总结了各种算法的优缺点,给出了分类算法的应用以及分类算法面临的挑战,并对分类算法的发展方向进行了展望,为使用者选择算法或研究者改进算法提供了借鉴.     

The use of compensatory and non-compensatory multi-criteria analysis for small-scale forestry

Small-scale farm forestry has the potential to offer many benefits both to landholders and the wider community. As with all changes in land-use practices, there are associated benefits and costs and these are not uniformly distributed. They have varying impacts on the different values, aspirations, goals and objectives that exist within the community. Furthermore, the community does not consider these values, aspirations, goals and objectives of equal importance. The degree of concern can vary from minor to high and overriding all other considerations. When evaluating farm forestry options it is necessary to address all of these concerns. This paper examines the combined use compensatory and non-compensatory multi-criteria analyses to evaluate forestry options, in a case study for the Darling Downs region of Queensland, Australia. These aggregation techniques are found to be highly complementary and together provide a comprehensive analysis. The compensatory technique provides a sound measure of overall performance of a forestry system, whereas the non-compensatory technique alerts decision-makers to presence of particularly poor performance with respect to individual criteria. The compensatory technique used is simple and understandable even for those with non-mathematical backgrounds. This analysis can identify and aid communication of the relative benefits and costs, and trade-offs, between economic, environmental and social considerations.     

手持GPS接收机短多径干扰抑制方法研究

分析了手持GPS接收机在实际应用中定位精度的多径干扰影响因素,提出了短多径干扰抑制算法,并将该算法用于导航接收机中,建立了实现原理框图,进而提出了短多径抑制算法的具体步骤,通过实测检测得到较高的精度.     

中央和地方政府水利投融资的演化博弈分析

在我国水利建设资金配置中,存在着中央和地方两级政府作为投资的主体,在兴建水利工程上进行着是否投资的利益博弈.基于演化博弈视角,分析了中央政府与地方政府在不同收益考量下长期博弈中形成的演化稳定策略,并揭示出由于存在“智猪博弈心态”,双方共同投资水利工程始终是不稳定策略组合,揭示了当前政府主导型的水利资金配置机制僵化现象.     

变桨距风力发电系统模糊控制

提出了一种基于灰色-ARIMA的金融时间序列智能混合预测模型。首先建立金融时间序列灰色预测模型,并采用PSO算法对灰色模型的三个参数进行优化;利用ARIMA算法对预测模型的残差进行分析,同时采用遗传算法对ARIMA的系数进行优化;最后用ARIMA的残差预测结果对灰色预测模型进行补偿。结果表明,以较好的精度拟合一段时期内MA＜107的时间序列,预测误差控制在5%以上,与单纯的灰色预测算法和神经网络算法相比,在平均绝对误差、均方根误差和趋势准确率三项评价指标上,具有明显优势。