马尔科夫链在电力负荷组合预测中的应用

针对单一模型都有其特定的适用范围和条件,文中提出了一种基于马尔科夫链拟合的非负时变权重组合预测算法.该算法通过马尔科夫链对筛选出模型的状态概率分布变化规律进行拟合,将一步转移概率矩阵的估计问题转化为多元约束自回归模型,然后利用一步转移概率矩阵的估计和初始状态概率分布来确定组合权重.实例表明,该方法计算量小、精确度高、具...     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

Influences of chitosan on freeze–thaw stability of Arenga pinnata starch

This study aims to investigate chitosan (CS) with five different molecular weight (Mw) on freeze–thaw stability of Arenga pinnata starch (APS) gel subjected to five freeze–thaw cycles (FTC). The syneresis of APS gels was reduced by adding CS and the APS gel with high Mw CS had lower syneresis duo to a higher water holding capacity (P < 0.05). The addition of CS significantly decreased the hardness and molecular ordered structure of APS gel. In addition, CS could improve the microstructural stability. The results suggested that CS could effectively improve the freeze–thaw stability of APS gel, and CS with higher Mw might have more practical utility to improve stability of APS gel.     

Efficient recursive least squares parameter estimation algorithm for accurate nanoCMOS variable gain amplifier performances

ABSTRACT

With the aggressive scaling of integrated circuit technology, parametric estimation is a critical task for designers who looked for solutions to the challenges of some Nanoscale CMOS parameters. This paper presented the prediction of primary parameters of CMOS transistor for 16 nm to 10 nm process nodes using both of Bisquare Weights (BW) method and a novel recursive least squares (RLS) parameter estimation algorithm. The proposed RLS algorithm consists of the minimisation of a quadratic criterion relating to the prediction error in order to attain the best estimated parameters of the developed mathematical model. The obtained results thanks to the proposed RLS algorithm were better than those reached using the BW method. Comparisons between Predictive Technology Model (PTM) data and parameters estimated with RLS algorithm were made to check the validity and the consistency of the proposed algorithm. These predicted primary parameters were helpful to estimate and to optimise the performances of the Variable Gain Amplifier (VGA) which was a basic circuit element with a key role in the design of new upcoming receivers.     

一种在矩阵空间中识别文本蕴涵的动态交互网络

针对文本蕴涵问题提出一种动态交互网络（dynamic interactive network,DIN）进行识别。不同于已有交互模型,DIN将两句词向量投射到二维矩阵空间中进行交互,然后利用输出矩阵为同时处理上下文信息和控制信息流动的GRU编码器生成动态权重。前者通过更高阶形式的信息交互挖掘深层逻辑片段,后者通过改变交互信息与上下文信息的结合模式帮助编码器有效区分两者的重要性差异。模型在SNLI测试集上获得了88.0%的识别准确度,超过已有的最佳模型,且使用的训练参数仅为它的一半。     

高温灵敏系数标定影响因素分析

高温应变计是高温结构强度测试、疲劳测试和寿命评估的主要测量传感器,其灵敏系数测试的准确性影响高温应变测试中应变修正数据的真实性。对应变计灵敏系数原理进行分析,明确灵敏系数是应变计输出与应变之间的关系,对砝码加载四点式简支梁结构和纯弯矩钢架梁结构灵敏系数测量模型进行分析,确定产生标准应变的影响因素。常温灵敏系数标定的影响因素有试验梁尺寸、试验梁轴向力,实际灵敏系数测试结果表明简支梁灵敏系数略大,分散明显较大。高温下应变计的输出与载荷应变、应变计热输出、试验梁尺寸变化、弹性模量变化和摩擦力变化有关,对热输出消除方法进行探讨,理论上明确温度下简支梁尺寸变化、弹性模量变化误差高达22%,钢架梁的刚性封闭静态力学平衡系统的温度影响误差较小。利用自研框架式高温裸栅应变计、高温陶瓷胶,进一步用简支梁、钢架梁实际测试灵敏系数随温度变化验证了理论分析的正确性。     

针对模糊效应的卫星图像质量评价模型研究*

为了实现景象匹配制导应用中对图像数据源质量的客观评价,针对卫星图像的模糊效应,研究了影响图像质量的清晰度评价指标,通过分析比较其对图像匹配过程的影响,挑选出有效指标作为评价因子;通过对大量实验数据特性的统计,结合线性回归分析,提出了基于假设检验的权值拟合算法,完成了各指标贡献率（即权值）的求解;进而建立了面向匹配制导应用的图像质量评价模型。实验表明,该模型具有良好的单调性和稳健性,在匹配制导中能对图像质量进行有效评定,对把握卫星基准图像源质量具有重要现实意义。     

基于模糊层次分析法的电力安全风险评估

分析电力安全风险的重要性,把层次分析法引入模糊环境中,提出一种利用模糊层次分析法对电力安全风险的评估方法,克服人为确定权重的随意性和主观性的缺陷。该方法应用在电力安全风险评估中是有效、可行的。     

基于风险权重的信息安全评估模型的研究

提出一种新的信息安全评估模型.该模型引入了风险权重概念,对潜在的风险因素进行分级量化,有效消除主观评价和不确定性因素对评估结果的影响.相对于已有评估模型,该模型评价指标简明清晰、评价步骤简洁规范、量化标准统一,具有良好的操作性和实用性,便于对各种信息系统进行快速评估.