基于BP人工神经网络的蒸气云爆炸超压预测的研究

探讨用BP神经网络预测蒸气云爆炸超压的基本原理.重点分析影响蒸气云爆炸超压的各种因素,在此基础上利用BP神经网络算法,通过对80组不同反应活性气体在不同环境条件下爆炸的实验数据进行训练建立了预测蒸气云爆炸超压的网络模型,并对另外20组实验数据进行了爆炸超压预测.预测结果与实测结果基本吻合,说明该模型能够反映蒸气云爆炸超压与其多种影响因素的映射关系,可用于蒸气云爆炸超压预测.该方法为预测蒸气云爆炸超压提供了一条新途径,具有工程实际意义.     

模拟退火优化BP神经网络在航向控制系统中的应用

目前，广泛运用于神经网络中的误差反向传播算法（BP算法）训练时间较长，且易陷入局部最优．为了克服BP算法的固有缺陷，文中提出了在BP算法中加入模拟退火算法权因子．在航向控制系统中进行了仿真，数据显示该算法比单纯BP算法更能优化控制器性能参数和全局搜索能力，收敛速度更快，精度提高比较明显。     

BP模型在预测多孔NiTi合金孔隙度和屈服强度上的应用

基于BP神经网络的原理,建立了热爆法合成多孔NiTi形状记忆合金孔隙度和压缩屈服强度的神经网络模型.该模型拟合了温度、Ti粉颗粒尺寸和生坯密度对热爆产物孔隙度和压缩屈服强度的影响.当温度、Ti粉颗粒尺寸和生坯密度发生变化时,对反应产物的性能进行了预测,其预测值和实验值非常吻合.因此该模型可用于多孔NiTi形状记忆合金的性能控制,通过对性能的合理调控,使其与所替换的生物组织更加匹配,同时提高研究效率,降低成本.     

一种基于BP神经网络的语音相空间客观干扰效果评估模型

通过建立语音信号的相空间结构,在分析不同受扰语音相空间变化的基础上,提取了两组表征语音干扰变化的特征参数,利用BP神经网络建模方法建立了一种基于输出模式的客观语音干扰效果评估模型,并录制了大量试验数据对模型进行了验证,表明该模型具有较强的可信性,该模型可以直接在通信链路终端使用,避免了输入输出模式评估方法在应用中严格同步的困难,可操作性比较强.建立了一种新的客观语音干扰效果评估模型.     

Microstructure and oxidation resistance of porous NbAl3 intermetallic prepared by thermal explosion reaction

Porous Nb–Al intermetallic was prepared by thermal explosion (TE) of combustion synthesis (CS). The temperature profile, phase composition, open porosity and oxidation resistance of Nb–Al compact were investigated. The results showed that the significant exothermic reaction occurred, which means that an obvious TE appeared during heating. The volume expansion of 190% was observed, and the prepared sample exhibited interconnected pores with an open porosity of 65.7%. The porous NbAl₃ intermetallic showed ‘pest’ oxidation in the temperature range of 500–600°C, and followed the parabolic oxidation law at 400°C. Moreover, due to the highly porous structure, this material had great potential for application to separation and heat insulation at a temperature range of room temperature to 400°C.     

Development of Al2O3/TiN Ceramic Cutting Tool Materials by Artificial Neural Networks

The artificial neural networks (ANN) which have broad application were proposed to develop multiphase ceramic cutting tool materials. Based on the back propagation algorithm of the forward multilayer perceptron, the models to predict volume content of composition in particle reinforced ceramics are established. The Al2O3/TiNl ceramic cutting tool material was developed by ANN, whose mechanical properties fully satisfy the cutting requirements.     

Evolutionary neural network modeling for software cumulative failure time prediction

An evolutionary neural network modeling approach for software cumulative failure time prediction based on multiple-delayed-input single-output architecture is proposed. Genetic algorithm is used to globally optimize the number of the delayed input neurons and the number of neurons in the hidden layer of the neural network architecture. Modification of Levenberg–Marquardt algorithm with Bayesian regularization is used to improve the ability to predict software cumulative failure time. The performance of our proposed approach has been compared using real-time control and flight dynamic application data sets. Numerical results show that both the goodness-of-fit and the next-step-predictability of our proposed approach have greater accuracy in predicting software cumulative failure time compared to existing approaches.     

基于BP神经网络的导线脱冰跳跃高度预测模型

冰区导线脱冰振动会引起绝缘间隙减小,严重时甚至导致闪络和跳闸等电气事故.首先利用数值方法模拟得到各种参数条件下导线的脱冰动力响应,获得导线的最大脱冰跳跃高度.进而基于数值模拟结果和BP神经网络构建导线脱冰跳跃高度预测模型,将线路的导线分裂数、导线型号、档距、高差等结构参数以及初始应力、覆冰厚度和脱冰率等载荷参数作为输入...     

Al含量对热爆合成Al-Ti-C组织及细化性能的影响

为改善Al-Ti-C中间合金的晶粒细化性能,采用铝液中热爆合成法制备出用于铝及铝合金晶粒细化的Al-Ti-C中间合金.通过DTA、XRD和SEM等手段分析了Al含量对热爆反应过程及合成产物组织形态的影响,并比较了Al-Ti-C中间合金对工业纯铝的细化效果.结果表明,铝液中热爆合成的Al-Ti-C中间合金由Al、Al3Ti、TiC三相组成,Al含量对反应体系的合成温度、反应速度及合成产物组织产生重要影响.调整原料Al含量可有效控制中间合金中第二相粒子组织形态,获得良好的晶粒细化性能.