基于LS-SVM棉针织物前处理工艺指标软测量

该文针对棉针织物前处理过程工艺指标吸水性和白度难以实现在线连续检测,且与前处理过程温度、时间、液碱浓度、双氧水浓度等影响因素具有较强非线性,难以建立精确数学模型。在分析了棉针织物前处理过程质量指标相关影响因素的基础上,采用最小二乘支持向量机建立了前处理过程工艺技术指标软测量模型,并通过实验验证了软测量模型的有效性。     

基于熵权理论和渴求函数法的多响应优化设计研究

文章首先对多响应优化问题进行了回顾和分析,针对多响应优化设计中权重确定和优化模型的建立问题,探讨了熵权理论和基于过程能力指数的渴求函数法在多响应优化设计中应用的可能性,并提出了熵权理论和渴求函数法结合的多响应优化设计方法,然后通过实例对文中所提的方法进行了实证研究,最后得出结论通过将熵权理论和渴求函数结合应用于多响应优化问题中,可以达到很好的效果。     

城市河口填海特征及其生态影响的形态学研究

淤泥质河口是填海建港主要地区,体现出明显城市化形态特征,却未在城市形态学领域引发实质性研究,导致填海规划缺乏指导。本文选择20个研究对象,以适宜分辨率Goo对eEanh影像为数据源,利用形态绘制方法,依据基础形态指数稳定域,得出河口区适宜研究幅度和精度,并利用填海方式破碎度和潮间带特征指数分析河口形态与生态特征。结果显示,多数案例河口因填海使潮间带衰退严重;亚洲填海河口在以潮间带相关指数为生态评价要素的前提下,反映出较差形态稳定性和生态状况;同等填海规模下,单斑块填海比多斑块分散填海对潮间带侵占破坏更大。     

Global sliding‐mode control with generalized sliding dynamics

A global sliding‐mode control (GSMC) scheme is proposed to provide a framework for ensuring the existence of a sliding mode throughout an entire response. Based on this framework, robust eigenvalue‐assignment GSMC (REA‐GSMC) is proposed to robustly assign closed‐loop eigenvalues that must be real. The eigenvalues being all real, however, leads to sluggish responses. According to most error criteria such as IAE, ISE, and ITAE, the optimum system should have complex eigenvalues. This paper proposes a GSMC scheme with generalized sliding dynamics, referred to as Generalized GSMC, in order to release the previous constraint on the REA‐GSMC. Thus, the Generalized GSMC can be designed to achieve a system that is both robust and optimum in the sense that it minimizes certain error performance indices in spite of the presence of system uncertainties. Experiments were conducted on a two‐link direct‐drive manipulator to demonstrate the effectiveness of the proposed scheme. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

考虑单峰分布的电热综合能源系统风险调度

不确定可再生能源并入电热综合能源系统后将引发系统运行风险,而通过合理量化风险,实现风险可控性和调度经济性平衡是电热综合能源系统风险调度的关键。依据随机风电功率的单峰分布特性构建矩模糊集并以此刻画风电功率的不确定性,同时采用分布鲁棒机会约束方法来刻画系统的运行风险,进而建立了电热综合能源系统的分布鲁棒风险调度模型。在此基础上,从风险发生概率和经济成本的角度,提出了评估不确定风电功率引发运行风险的量化指标：均值风险概率和风险调度成本。最后,以改进的巴厘岛电热综合能源系统为例进行算例分析,验证了所提模型及其风险评估指标的可行性和有效性,并给出了电热综合能源系统的最优调度决策。     

On the performance of different capability indices under normal and non-normal distributions

In this article, we have examined the performance of some useful capability indices using normal and non-normal distributions. The confidence intervals are calculated and mean coverage rates are observed for different capability indices. The effects of symmetry and kurtosis of parent distributions are examined on the mean coverage rates of different capability indices. Moreover, we have investigated the robustness (of confidence interval) using the median and percentile-based indices. We have considered the well-known distributions including normal, gamma, t, Weibull, and chi-squared. For these process scenarios, we have observed that some indices resist disturbance only in symmetry of the parent distribution, some resist the disturbance in symmetry and kurtosis of the distribution, and some indices don’t resist against either type of disturbance.     

Estimating Construction Material Indices with ARIMA and Optimized NARNETs

Construction Industry operates relying on various key economic indicators. One of these indicators is material prices. On the other hand, cost is a key concern in all operations of the construction industry. In the uncertain conditions, reliable cost forecasts become an important source of information. Material cost is one of the key components of the overall cost of construction. In addition, cost overrun is a common problem in the construction industry, where nine out of ten construction projects face cost overrun. In order to carry out a successful cost management strategy and prevent cost overruns, it is very important to find reliable methods for the estimation of construction material prices. Material prices have a time dependent nature. In order to increase the foreseeability of the costs of construction materials, this study focuses on estimation of construction material indices through time series analysis. Two different types of analysis are implemented for estimation of the future values of construction material indices. The first method implemented was Autoregressive Integrated Moving Average (ARIMA), which is known to be successful in estimation of time series having a linear nature. The second method implemented was Non-Linear Autoregressive Neural Network (NARNET) which is known to be successful in modeling and estimating of series with non-linear components. The results have shown that depending on the nature of the series, both these methods can successfully and accurately estimate the future values of the indices. In addition, we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.     

Effects of woody elements on simulated canopy reflectance: Implications for forest chlorophyll content retrieval

An important bio-indicator of actual plant health status, the foliar content of chlorophyll a and b (Cab), can be estimated using imaging spectroscopy. For forest canopies, however, the relationship between the spectral response and leaf chemistry is confounded by factors such as background (e.g. understory), canopy structure, and the presence of non-photosynthetic vegetation (NPV, e.g. woody elements)—particularly the appreciable amounts of standing and fallen dead wood found in older forests. We present a sensitivity analysis for the estimation of chlorophyll content in woody coniferous canopies using radiative transfer modeling, and use the modeled top-of-canopy reflectance data to analyze the contribution of woody elements, leaf area index (LAI), and crown cover (CC) to the retrieval of foliar Cab content. The radiative transfer model used comprises two linked submodels: one at leaf level (PROSPECT) and one at canopy level (FLIGHT). This generated bidirectional reflectance data according to the band settings of the Compact High Resolution Imaging Spectrometer (CHRIS) from which chlorophyll indices were calculated. Most of the chlorophyll indices outperformed single wavelengths in predicting Cab content at canopy level, with best results obtained by the Maccioni index ([R₇₈₀ − R₇₁₀] / [R₇₈₀ − R₆₈₀]). We demonstrate the performance of this index with respect to structural information on three distinct coniferous forest types (young, early mature and old-growth stands). The modeling results suggest that the spectral variation due to variation in canopy chlorophyll content is best captured for stands with medium dense canopies. However, the strength of the up-scaled Cab signal weakens with increasing crown NPV scattering elements, especially when crown cover exceeds 30%. LAI exerts the least perturbations. We conclude that the spectral influence of woody elements is an important variable that should be considered in radiative transfer approaches when retrieving foliar pigment estimates in heterogeneous stands, particularly if the stands are partly defoliated or long-lived.     

Ecological assessment of Phragmites australis wetlands using multi-season SPOT-5 scenes

Ecologists and conservationists need accurate and replicable tools for monitoring wetland conditions in order to develop and implement adaptive management strategies efficiently. The Rhone Delta (Camargue) in southern France encloses 9200 ha of fragmented reed marshes actively managed for reed harvesting, waterfowl hunting or cattle grazing, and holding significant numbers of vulnerable European birds. We used multi-season SPOT-5 data in conjunction with ground survey to assess the predictive power of satellite imagery in modelling indicators of reed structure (height, diameter, density and cover of green/dry stems) relevant to ecosystem management and bird ecology. All indicators could be predicted accurately with a combination of bands (SWIR, NIR) and indices (SAVI, OSAVI, NDWI, DVI, DVW, MSI) issued from scenes of March, June, July, September or December and subtraction between these. All models were robust when validated with an independent set of satellite and field data. The high spatial resolution of SPOT-5 scenes (pixel of 10 × 10 m) permits the monitoring of detailed attributes characterizing the reed ecosystem across a large spatial extent, providing a scientifically-based, replicable tool for managers, stakeholders and decision-makers to follow wetland conditions in the short and long-term. Combined with models on the ecological requirements of vulnerable bird species, these tools can provide maps of potential species ranges at spatial extents that are relevant to ecosystem functioning and bird populations.