富水氢氧化铝污泥冷冻时间的预测

对描述平板状和圆柱状富水氢氧化铝污泥冷冻的一维非稳态热传导数学模型进行适当的参数简化,并结合修正的Plank表达式,用数值法和半经验法对平板状和圆柱状污泥的冷冻时间进行了预测.结果表明,数值法预测的冷冻时间和温度与实验测定值吻合良好,但此法较烦琐;半经验法预测的冷冻时间比实验值稍偏小,但此法较简便.根据预测结果可以得到,在冷冻环境为-15℃时,8mm厚的平板状或6mm圆柱状污泥从30℃冷冻到-5℃所需的冷冻时间均约为40min,这为冷冻装置工业设计提供了基本依据.     

非线性时间序列的重构及预测

采用自适应前馈网络算法(AFN)进行非线性时序预测，对网络结构设计进行详细的探讨，并应用该方法对经典非线性时间序列数据进行预测，与传统预测方法(TAR)比较，结果证明此种方法具有较好的效果，网络的结构得到了简化。不仅满足了误差目标的要求，而且提高了网络的推广能力。且AFN方法可以对时间序列数据间的关系给出一种基于贡献率的解释。     

电力设备预防性维修策略的优化

提出了设备预防性维修的两阶段优化模型．阶段1确定最少的预防性维修次数．阶段2在第一阶段给出结果的基础上确定各预防性维修的最优周期．模型简化了求解复杂度，克服了长期运行期望周期模型的缺点，具有很强的可操作性，可为维修计划的制订和现场的作业调度提供决策支持．     

双向Elman神经网络在卫星电池阵功率预测中的应用研究

针对神经网络预测电池阵功率存在的模型阶数难以确定及预测精度低下的问题，提出一种基于改进的Elman神经网络的双向预测模型。该模型利用关联层动态神经元的反馈连接，将未来预测网络和过去预测网络的信息进行融合。使网络对时间序列特征信息的记忆得到加强，从而提高预测精度。用该文提出的双向预测模型对电池阵功率进行预测，输入层仅需一个节点，不需事先对模型进行定阶。仿真预测表明，预测精度比单向模型明显提高，且网络具有较好的泛化能力。     

基于支持向量机的短期GDP预测模型与应用研究

支持向量机是最近几年国际上模式识别研究的热点,具有全局最优和良好的泛化能力.本文在理论分析江门市GDP预测指标体系的前提下,研究了基于SVM的预测方法,并运用实际数据进行建模和预测,获得了比较准确的预测结果.     

基于灰色理论的煤炭需求预测模型研究

研究了GM(1，1)模型在我国煤炭需求预测中的应用，并以实际数据为基础，建立了我国煤炭需求量的数列预测模型。经检验，模型可靠，可用于对我国煤炭需求总量的预测。简要分析了根据实际变化不断改进模型的必要性。     

人工神经网络构造经济预测模型方法的探讨

探讨利用人工神经网络建立经济模型的一般原理和方法,并通过构造一个宏观经济模型的实例加以说明.与传统的回归分析方法相比,人工神经网络具有良好的适应性和分析预测能力.     

基于BP神经网络预报的动态矩阵预测控制

提出了一种基于BP神经网络预报的动态矩阵预测控制新算法 ,在该算法中 ,先用BP神经网络辨识对象模型 ,同时预测对象的未来输出 ,然后用动态矩阵控制算法进行滚动优化和反馈校正。该方法解决了非线性、时变对象难以建模及控制的问题 ,仿真结果验证了这一新型算法的可行性     

A multi-layer zone model for predicting temperature distribution in a fire room

Modelingoffireinacompartmentcanbeachievedeitherusingazonemodelingmethodoracomputationalfluiddynamics (CFD )modelingmethod .Themostcommonzonemodelisthetwo zonemodel.Themaincharacterofthismodelisthatitdividestheroom (s)intoahot ,upperlayerandacooler,lowerlayer ,andthatthephysicalpropertiesofeachlayer ,suchasitsgastemperatureandspeciesconcentrationsarealluniform .Somemodelsofthistypehavebeendeveloped[1～3] ,andacomprehensivereviewoftheexistingtwo zonefiremodelscanbefoundinreference [4 ].Thecomp…     

Approaches to prediction of impact of Qinghai-Tibet Railway construction on alpine ecosystems alongside and its recovery

With the aid of the Remote Sensing (RS) and Geographic Information System (GIS) technology, the ecosystem pattern and fragility distribution maps of the 50-km-wide zone along the Qinghai-Tibet Railway were compiled and by using the superimposition method, range, area and indexes of the impact of various engineering activities on the ecosystems alongside the railway were studied. By making reference to the ecosystem recovery process of the Qinghai-Tibet Highway, mechanisms of recovery of the alpine ecosystems alongside the Qinghai-Tibet Railway were studied and extents and rates of the recovery were predicted.The results indicate that the impact of the railway engineering on the Alpine ecosystem depends mainly on how much the original surface soil in the zone has been disturbed and how fragile of the ecosystem per se. Restoration of vegetation coverage and species abundance shows a significantly reverse relationship with disturbance of the original surface soil but an extremely positive one with the length of the restoration period and mean annual precipitation and annual mean relative humidity in the period and no obvious bearings with altitude and temperature. In sections with an annual precipitation over 200mm, as long as a certain percentage of original soil is left in situ, it takes only 30 years or so for biodiversity to get basically restored to the original level after the construction is completed but at least 45-60 years or more for vegetation coverage.