特征编码在摩托车盘类零件CAD中的应用

采用特征编码技术对摩托车盘类零件进行特征编码，根据码位对应的形状特征进行特征造型并定制成参数化图元，煞后以零件主特征的关键尺寸为驱动参数对构成零件形状特征的图元进行拼接，实现摩托车盘类零件的参数化设计。     

城市环保战略目标定量考核指标体系研究

本文在深入研究6个城市的定量考核指标体系的基础上,提出了城市环保战略目标定量考核指标体系建立的依据和原则,探讨了指标体系的结构与指标选取问题.本文认为,城市环保战略目标定量考垓指标体系应由目标层、准则层和指标层三个层次构成,整个结构是自上而下分解,自下而上递进.     

完全均匀混合质量平衡水质模型在滇池中的应用

介绍了完全均匀混合假设下以质量平衡为基础的湖泊水质模型,运用滇池的实测数据对模型进行了参数率定、验证,给出了模型在滇池水质预测中的应用实测,最后讨论了模型的几个假设条件对滇池的适应性。实例研究表明,该模型可适用于滇池水质有机污染长期浓度预测。      

Bayesian analysis under ordered functions of parameters

Ordered parameter problems arise in a wide variety of real world situations and are dealt with extensively in the literature. Traditional frequentist methods for dealing with these problems are rather complicated theoretically, especially when sample sizes are small. Bayesian methods are not widely used because high dimensional numerical integration is often required. However, Markov chain Monte Carlo methods provide alternatives to such numerical integration and also deal with ordered parameter problems in a straightforward manner. Little is known about the situation where functions of parameters are ordered. Such problems may seem to be of little practical concern initially, but one can readily see their importance in situations where ordering is placed on the means and variances of several normal or Gamma populations. For the Gamma distribution we will present real examples where we will analyze monthly precipitation data from San Francisco, California and Oakland Mills, Iowa. For the San Francisco data we will simultaneously order both monthly precipitation means and variances. For the Iowa data we will place ordering on seasonal average while still estimating monthly means. Our results show that we would obtain sharper, more accurate inference when order restrictions are employed.     

斜坡稳定性的二级模糊推断

根据对斜坡稳定性影响的大小,选取了七个主要因于,引用了山西明水河流域几个斜坡样点实测数据．应用模糊近似推论方法及信息分配原理,对斜坡稳定性进行了单因子灰色隶属度分析及综合二级模糊近似推论,该方法克服了传统单因子评价的弊端,能比较真实地反映实际,为布设护坡工程提供了理论依据。     

Approaches and terminology for causal analysis in land systems science

Research into land and social-ecological systems science could benefit from improved clarity in the terminology used for causal analysis and a structured way to make causal inferences. Here I identify two aspects of causality, i.e. causal effects and causal mechanisms, and discuss explanation in historical sciences. I then propose definitions for the major terms used for causal relations, including driver, (spatial) determinant, location and contextual factor, proximate and underlying factors. Finally, I discuss the contribution of various operational approaches, including time series and counterfactual approaches for assessing causal effects and process-tracing approaches for establishing causal mechanisms. Having a coherent concept of causality, agreeing on a precise vocabulary and harnessing our tools with the clear purpose of establishing both causal effects and causal mechanisms should strengthen causal explanations for single cases, for drawing policy-relevant lessons and for theoretical development in relation to land and, more broadly, social-ecological systems processes.     

GA优化的湖泊富营养化评价的普适公式探讨

在适当设定富营养化指标的“本底值”情况下,当指标值用于对应“本底值”的相对值表示时,可采用S型曲线描述湖泊富营养化的发展程度,公式中的参数可视为与指标特性无关,采用遗传算法对公式参数优化,得到对多项指标均适用的富营养化程度的指数公式,并提出用广义模糊对比因子赋权新方法计算富营养化综合指数。该评价方法物理意义明确,计算简单,使用方便,具有普适性、可比性和实用性。     

Spatio-temporal dissolved oxygen dynamics in the Orbetello lagoon by fuzzy pattern recognition

This paper models the dissolved oxygen (DO) dynamics in the Orbetello lagoon as a function of the physico-chemical and ecological system variables, including the submerged vegetation, nutrients, and hydrodynamics. It should be viewed as the concluding sequel to a previous paper describing the dynamics of the lagoon ecosystem [Giusti, E., Marsili-Libelli, S., 2006. An integrated model for the Orbetello lagoon ecosystem, Ecol. Model. 196, 379–394] by introducing the missing DO dynamics. The model considers the oxygen demand originating from the decay of carbonaceous and nitrogenous compounds, as well as photosynthesis and natural reaeration by winds and currents as the oxygen producing processes. With a fixed-parameter set the model could accurately reproduce each single circadian DO cycle, but in the long run it failed to extend this fit and could not accommodate the large DO fluctuations induced by the seasonal variability. In order to enhance the model flexibility, a fuzzy pattern recognition algorithm was designed to classify the circadian DO patterns into four typical behaviours, related to the season, and estimate the corresponding parameters, with the overall model output being a fuzzy combination of these sets. The paper discusses several methods to patch the parameter sets and compares their performance in tracking long-term DO variations. A final assessment of the model validity is obtained by incorporating the whole DO dynamics (model, fuzzy pattern recognition and parameter combination) into the general lagoon model and producing a consistently correct series of DO daily distributions over a yearly cycle. Thus the paper contains both a practical and a methodological aspect. The practical one is the linking of all the lagoon dynamics to the dissolved oxygen kinetics in order to clarify to what extent macroalgae and macrophytes influence the oxygen balance. The methodological aspect consists of extending the validity of short-term models to long time-horizons through a patching technique supported by fuzzy pattern recognition.     

Impact of bias in predicted height on tree volume estimation: A case-study of intrinsic nonlinearity

Bias originating from intrinsic nonlinearity in nonlinear models is caused by excess curvature in the solution locus of parameter estimates derived from least squares procedures. Bias due to intrinsic nonlinearity varies according to sample size as well as model specification. This paper analyses consequences of fractionising data into smaller sub-samples. Based on measurements of stem diameter and total tree height from the first Danish national forest inventory, it is demonstrated how data splitting at random may cause the intrinsic nonlinear curvature to exceed the critical F-value. Application of a Taylor-series expansion shows that, for all practical purposes, the bias in predictions of individual tree volume (based on stem diameter and tree height) is negligible. To minimize residual variance, intrinsic curvature and, in turn, prediction bias, it is recommended that data be stratified according to site conditions, stand characteristics or other relevant criteria. Finally, the preferred model should exhibit close-to-linear behaviour.     

基于PSO-SVM算法的环境监测数据异常检测和缺失补全

针对环境监测数据异常和数据缺失问题,提出了基于支持向量机的粒子群优化数据异常检测和缺失补全算法。利用粒子群优化算法选取较优的支持向量机训练参数组合,以此建立非线性的支持向量机模型,并利用结果模型对测得的真实数据拟合预测。以宁夏回族自治区某污水处理厂的污染物测量数据作为实验数据,结果表明,利用该算法预测数据的准确率可达97.977%,检测异常数据准确度高,缺失数据补全正确。