具有Markov参数随机时滞微分方程的吸引性

应用半鞅收敛定理和■to公式对具有Markov参数随机时滞微分方程的吸引性进行了讨论,给出了吸引子存在的条件.最后,通过了一个例子对得到的结果进行了说明.     

一类时滞不确定系统的自适应鲁棒镇定

讨论了一类具有不匹配扰动的时滞不确定系统的鲁棒镇定问题.在扰动有界但上界值未知的情形下,给出了获得自适应鲁棒控制器使系统鲁棒稳定的充分条件.通过估计不确定性的上界,基于估计值设计了控制器,保证了闭环系统一致有界意义下的鲁棒稳定性.     

东北三种典型针叶树种可燃物烘干参数的确定及影响因素分析

本文拟通过室内控制试验确定对于不同样品采取什么样的烘干温度及时间,才能保证又快又好的完成样品的室内烘干处理。本文通过具体实验得出东北三种典型针叶树种(红松、樟子松、落叶松)在不同的湿度条件(100%、80%、60%、40%、20%)、时滞条件(1、10、100时滞)以及不同部位(树皮、树叶、地被物)在105℃下的烘干时间。使用正交实验法研究可知,红松所需要的烘干时间明显高于其他两种植物,排序为:红松>樟子松>落叶松,就时滞条件而言,烘干时间排序为100时滞>10时滞>1时滞,就植物部位而言,需要的烘干时间为:树皮>地被物>树叶。正交实验的结果可知,红松在100时滞条件下的树皮部分所需要的烘干时间最长,影响因素的大小依次为:时滞条件>植物部位>植物品种。     

可变时滞非自治Logistic方程的全局吸引性

主要研究一类可变时滞非自治Logistic方程的全局吸引性,通过分别研究非振动解和振动解的性质并使用一定的分析技巧结合不等式的方法,得到了方程的正平衡态为全局吸子的新的充分条件,这些条件便于验证．所得到的结果推广并改进了相关文献中的一些结果,也完善并补充了非自治变时滞Logistic方程的全局吸引性问题的研究工作．     

BP人工神经网络对酸奶货架期的预测

针对传统力学模型的局限性,构建了BP人工神经网络模型对酸奶货架期进行预测。该模型全面考虑了理化指标、微生物指标、感官指标等消费者关注度高的指标,模拟非稳定性冷链条件,对酸奶的货架期进行预测。结果表明:BP神经网络模型与传统动力学模型相比,能更加准确地预测在冷链短暂中断的温度波动条件下的货架期。     

基于人工神经网络的森林资源预测研究

应用人工神经网络方法分别建立土地资源预测、森林蓄积量预测、各龄组蓄积量预测三层前馈反向传播神经网络模型对森林资源进行预测模拟.预测结果表明在小样本条件下,森林资源预测神经网络模型预测精度较高,开辟了森林资源预测新途径.     

生物柴油催化剂固定化酶的性能评价及其动力学分析

通过正交试验优化了生物柴油催化剂固定化酶活力测定的最佳条件,比较了固定化酶与游离酶的性能,并对固定化酶催化反应的动力学进行了初步分析.结果表明：测定固定化酶活力的最佳条件为反应时间20min,温度43℃,固定化酶用量40mg;与游离酶比较,固定化酶最适反应温度提高,贮藏稳定性和操作稳定性都有大幅度提升;动力学分析结果表明,固定化酶催化反应的速率在动力学上是可以控制的.     

基于RBF神经网络方法的铀尾矿坝稳定性分析

为研究分析我国某铀尾矿坝的稳定性,以影响尾矿坝稳定性的14个指标为参数,运用MATLAB实现RBF神经网络的方法,采用实际数据对网络进行训练,结果得出了该铀尾矿坝的稳定性参数为3,属于一般安全铀尾矿坝,这对研究尾矿坝稳定性提供了重要的参考作用。     

钢琴用云杉木材吸湿性及尺寸稳定性研究

主要针对钢琴用云杉木材进行了吸湿性及尺寸稳定性研究,通过高温热处理及二次干燥两种工艺分别对木材进行了处理,试验结果表明:两种工艺处理方法可以有效降低木材的吸湿性,提高木材的尺寸稳定性,同时,在温度140℃、时间8 h的条件下进行的高温热处理,云杉木材吸湿性最低、尺寸稳定性最好.     

微波辐照提取板栗壳棕色素的研究

以板栗壳为原料,在微波条件下,以乙醇溶液作溶剂直接从板栗壳中提取天然棕色素.探讨了各因素对板栗壳天然色素提取效果的影响.确定了在微波条件下从板栗壳中提取天然色素的最佳工艺条件:5 g板栗壳粉在微波辐照时间13 min、浸提温度75 ℃、乙醇溶液的体积分数40 %、料液比1:20(g:mL)的条件下得率为7.02%.通过对色素的定性实验和稳定性实验,表明该板栗壳色素属于黄酮类色素,其对光照、温度、还原剂、氧化剂、pH值有良好的稳定性.     

Gentan probability analysis with a state-dependent discrete forest growth model

The previous stochastic models applied for Gentan probability estimation utilized either a stationary or nonstationary Poisson process to describe the forest owners’ harvesting behavior by means of the counting process. A nonstationary Poisson process has the advantage over a stationary Poisson process of capturing a time-dependent change of harvesting events. However, a nonstationary Poisson process can lack one preferred characteristic of the probability theory when utilizing an average growth function with an asymptotic nature of growth. That is, the sum of the derived Gentan probabilities over time does not always become unity. In this paper, we introduce a state-dependent discrete forest growth model with an asymptotic nature of growth to overcome the problem, then propose a stochastic model applied for Gentan probability estimation. The Mitscherlich type growth function is utilized. The derived probability law to capture the harvesting behavior is shown to be the binomial probability law. The derived probabilities prove to sum up to unity over time.     

Estimating the stock recovery rate using matrix models

The stock recovery rate, that is the ratio of the exploitable wood stock at the end of a felling cycle over the exploitable wood stock at the beginning of this cycle, is a key parameter used in the management plans of the natural forests in central Africa. Estimating this rate requires a model of forest dynamics. Forest managers usually use a formula that is based on a simple model that assumes constant vital rates. A generalization of this formula is based on matrix models of population dynamics. The stock recovery rate at the end of the k th felling cycle can be simply computed using matrix models. The asymptotic stock recovery rate (that is the limit as k tends to infinity) is the asymptotic growth rate (that is the dominant eigenvalue) of a transition matrix that includes harvest. The estimate of the stock recovery rate can be completed by its confidence interval using bootstrap methods. When applied to sapelli (Entandrophragma cylindricum, Meliaceae), a major timber species in central Africa, it turns out that a few thousands observations are required to estimate the stock recovery rate with an accuracy of at least 10%. The number of observations available on an experimental site in the Central African Republic does not permit to do better than an accuracy of about 45% at level 95%. This does not permit to conclude whether the asymptotic stock recovery rate is greater or less than one. As a conclusion, in management plans in central Africa, stock recovery rates should be given together with an indication of the variability of their estimate (standard error or confidence limits).     

A model of carbon storage in forests and forest products

This paper discusses the general formulation of a model that describes carbon storage in a forest and its timber products as a function of the forest growth curve, the rotation period and the carbon retention curves for the timber products. After a number of rotations, the rotation-averaged quantity of stored carbon approaches an asymptotic value. It is shown that, when forests are managed for maximum sustained yield of biomass, the contribution to asymptotic carbon storage from timber products is about 2.5D/T* times the contribution from living trees, where D is the characteristic decay time for reconversion of timber products to carbon dioxide, and T* is the normal rotation period for maximum sustained yield. For a given value of D/T*, carbon storage can be optimized if the policy of maximizing sustained yield is relaxed. For D/T* < 1, as the rotation period is increased indefinitely, the asymptotic level of carbon storage increases monotonically toward the value of the carbon content of living trees at maturity, g(f). For D/T* > 1, there is a finite, optimal rotation period, T(o), greater than T*, for which asymptotic carbon storage is greater than g(f). As D/T* tends to large values, however, T(o) tends to T*, so that, in this limit, management for maximum sustained yield also ensures maximum carbon storage. From initial planting, the time taken to reach asymptotic carbon storage decreases as the normal rotation period, T*, decreases, but increases almost linearly with increasing decay time of timber products, D. This result qualifies the short-term value of any particular planting strategy.     

辽东山区阔叶红松天然次生林经营与稳定性初探

通过样地调查,结合森林群落的多样性特征,采用M．Godron的稳定性测定方法,探讨了不同经营方式对辽东山区阔叶红松天然次生林生态系统稳定性的影响,研究表明：比较简单的群落,容易受到外来种的入侵,其整个群落的抗外界干扰力以及在干扰后自身的恢复能力自然要弱一些。然而,多样性最大的群落未必是稳定性最高的群落。基于该理论,认为实施动态择伐经营体系有利于该区域阔叶红松林生态系统稳定性的提高。     

甲苯二异氰酸酯交联聚乙烯醇木材粘合剂

用正交实验法,研究在水基中和催化剂-X存在下,甲苯二异氰酸酯(TDI)交联聚乙烯醇(PVA)的反应。探讨PVA、交联剂TDI和催化剂-X的加入量、交联反应的温度,以及交联反应进行的时间等因素对该粘合剂压缩剪切强度和颜色稳定性的影响。研究结果表明,本实验交联改性PVA胶水的方法,较大程度地提高粘胶的粘结性能;在实验条件范围内,粘胶的颜色稳定性只与交联反应的温度有关,而与其他实验条件无关。本研究形成一种白色的乳胶,对环境和人体健康无影响,适合于木材加工业,尤其是室内装饰用木材的粘结。本研究中试产品,经质量检验,合乎化工行业标准。     

蕉冲山滑坡特征及稳定性评价

对蕉冲山滑坡进行了分析,判定其属于蠕滑-拉裂型滑坡。详细地阐述了滑坡的基本特征,探讨了滑坡的成因机制及演化过程。在分析成因机制的基础上,采用传递系数法对该滑坡天然状态及暴雨情况下的稳定性进行了计算和评价,为滑坡治理设计提供了重要的依据。     

用红外光谱分析刨花蒸汽处理后成分的变化

用红外光谱法分析了云杉和白桦刨化蒸汽处埋后成分的变化。红外谱图不出了蒸汽处埋后刨花中的半纤维素和羟基比未处理的减少了,这是蒸汽处理改善刨花板尺寸稳定性的主要原因。红外谱图还示出了在同样的蒸汽处理条件下,白桦中半纤维素和羟基的减少程度大于云杉的减少程度,因此蒸汽处理后白桦刨花板尺寸稳定性的改善程度大于云杉刨花板的改善程度。     

重庆市开县林木种质资源现状及保护对策

开县地处三峡库区腹地,由于采伐过度,森林资源多样性遭到严重破坏,导致某些珍稀特用树种濒临绝迹。为保存珍稀濒危树种和优良造林树种种质资源,保持森林植物物种多样性和稳定性,对开县林木种质资源的现状和保护对策进行探讨。     

Comparison of image and rapid field assessments of riparian zone condition in Australian tropical savannas

Suitable methods for measuring and monitoring the condition of riparian environments are being investigated by government agencies responsible for maintaining these environments in Australia. The objective of this work was to compare two riparian condition assessment approaches, the Tropical Rapid Appraisal of Riparian Condition (TRARC) method developed for rapid on-ground assessment of the environmental condition of savanna riparian zones and an image based riparian condition monitoring scheme. Measurements derived from these two approaches were compared and correlated. The sample representativeness of the TRARC method was evaluated and the cost-effectiveness and suitability for multi-temporal analysis of the two approaches were assessed. Two high spatial resolution multi-spectral QuickBird satellite images captured in 2004 and 2005 and coincident field data covering sections of the Daly River in the Northern Territory, Australia were used in this work. Both field and image data were processed to map indicators of riparian zone condition including percentage canopy cover, organic litter on the ground, canopy continuity, tree clearing, bank stability, and flood damage. Spectral vegetation indices, image segmentation, and supervised classification were used to produce riparian health indicator maps. QuickBird image data were used to examine if the spatial distribution of TRARC transects provided a representative sample of ground based estimates of riparian health indicators. Covering approximately 3% of the study area, the sample mean of the TRARC estimates of individual indicators of riparian zone condition were in most cases within 20% of the global mean derived from the whole imaged riparian area. The cost-effectiveness of the image based approach was compared to that of the ground based TRARC method. Results showed that the TRARC method was more cost-effective at spatial scales from 1 km to 200 km of river in relatively homogeneous riparian zones along rivers with only one channel, while image based assessment becomes more feasible at regional scales (200–2000 km of river). A change detection analysis demonstrated that image data can provide detailed information on gradual change, while the TRARC method is less suited for multi-temporal analysis due to the ranked data format, which inhibits precise detection of change. However, results from both methods were considered to complement each other for single date assessment of riparian zones if used at appropriate spatial scales.