稀土永磁及磁记录材料的矫顽力与有效激活体积

指出了文献 [1]中的一个错误。给出了不同模型的稀土永磁材料以及磁记录材料的矫顽力 Hc和有效激活体积υ之间的正确关系 ,这样的关系被表示成一个复杂的函数关系 ,同时指出 ,对不同模型的稀土磁性材料 ,这个函数关系是不同的     

Ray-cast volume rendering accelerated by incremental trilinear interpolation and cell templates

Two related ideas for improving the speed of ray-cast volume rendering are studied in this paper. The first is an incremental algorithm for trilinear interpolation, a method commonly used in ray-cast volume rendering to calculate sample values. The incremental algorithm can expedite trilinear interpolation when many samples along a ray are located in one cell. The second is an efficient hybrid volume rendering restricted to parallel projection. In the preprocessing stage, acell template is created to store the information used by the incremental trilinear interpolation. When a cell is parallel projected, the information is retrieved from the template to compute the cell contribution. Because the algorithm with only one template may cause aliasing, an antialiasing technique exploiting multiple cell templates is proposed. With our method, ray-cast volume rendering can be accelerated considerably.     

关于集群系统中无线信道数的确定

准确估算集群系统所需无线信道数是工程设计中的一个重要的关键环节。本文从讨论系统业务、系统话务量出发,提出了一种正确使用爱尔兰—B公式(或巴姆表)确定集群系统中无线信道数的新方法。继而,较为详细地定量分析了集群方式对系统话务量的影响。最后,针对实际工程设计,推荐了一个集群系统容量计算的经验公式。     

火箭燃气射流对斜板冲击流场的数值模拟

采用高精度，高分辨率的二阶ＴＶＤ有限体积方法，对二维无粘射流冲击斜板的复杂流动场进行了数值模拟，得到了和实验规律相一致的计算结果。     

基于VTK三维地震数据体绘制系统框架

针对地震数据信息量大的特点,文中提出了一种针对三维地震数据体绘制系统的框架。解决的方法是将数据处理、用户交互、渲染绘制分离成三个模块,并且设计了层次结构来保持模块之间的独立性,便于各个模块的修改、更换和扩展,提高了可视化绘制系统快速开发的灵活性。基于三维可视化开发工具包VTK,设计并编程实现了一个地震数据体绘制系统界面。通过实验结果证明,此体绘制方案是可行的、有效的。     

主机数据流量检测的实现

分布式网络环境中主机数据流量的异常通常反映出主机是否遭受病毒、木马等恶意程序的入侵而成为网络攻击中的傀儡机,因此,对主机数据流量进行监测可以尽早发现潜在的危险。研究了基于Cisco路由器的主机数据流量检测的基本方法,并给出了具体的程序实现方法和网络硬件环境配置方法。     

改进BP网络在航材需求预测中的应用

针对航材备件需求预测问题,在对影响航材备件需求量的多个因素进行分析研究的基础上,运用改进BP神经网络算法进行预测的仿真实验。实验结果表明,改进BP神经网络能够对积累的历史数据进行充分的应用,并且有较高的预测准确性。     

基于Copula函数的洪水峰量联合设计方法研究

为明晰洪水峰量联合设计的特点,以岗南水库洪水为例,基于Gumbel Copula函数,分析了AND、OR、Kendall、生存Kendall 4种重现期的优缺点,采用极大似然法、同频率法、条件最可能组合法3种方法计算了联合设计值。结果表明: ①AND和OR重现期在危险域和安全域的识别上存在局限性;相对而言,Kendall重现期更合理,但其安全域是无界的,这与实际不符;生存Kendall重现期则界定了有界的安全域,使得重现期的概念在逻辑上更科学合理。② 3种设计值计算方法的差别不大,但从简单实用角度出发,推荐采用同频率法计算设计值。③不同重现期标准的设计值差别比较明显,基于OR重现期计算的设计值总是最大的,生存Kendall、Kendall重现期设计值次之,AND重现期设计值最小。④推荐采用生存Kendall重现期进行两变量洪水设计,因其有比较严谨的理论基础,且设计结果兼顾了安全性与经济性。⑤两变量联合设计值与单变量设计值的差异受变量间相关性的影响较大,且变量相关性越弱,差异越大。研究显示,基于生存Kendall重现期、采用同频率法计算设计值是目前较为科学合理的洪水峰量联合设计途径。     

Stock Price Forecasting: An Echo State Network Approach

Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean absolute error (MAE) was used to present the accuracy results. The MAEs of the data forecast by ESN were 0.024, 0.024, and 0.025, which were, respectively, 0.065, 0.007, and 0.009 less than those of LSTM. In terms of convergence, ESN has a reservoir state-space structure, which makes it perform faster than other models. Root-mean-square error (RMSE) was used to present the convergence time. In our experiment, the RMSEs of ESN were 0.22, 0.27, and 0.26, which were, respectively, 0.08, 0.01, and 0.12 less than those of LSTM. In terms of network structure, ESN consists only of input, reservoir, and output spaces, making it a much simpler model than the others. The proposed ESN was found to be an effective model that, compared to others, converges faster, forecasts more accurately, and builds time-series analyses more easily.