耦合式MEMS微波功率传感器集总参数模型的优化

耦合式MEMS微波功率传感器的集总参数模型可用于分析并计算器件的微波特性,是设计传感器相关结构尺寸的重要参考依据。针对目前传感器日益复杂化的阻抗匹配结构,对现有的集总参数模型进行了优化,并进行了相关理论推导。实验结果表明,优化后的模型计算出的反射系数最大误差为6.0 dB,插入损耗最大误差为0.7 dB,模型准确度相较于优化前有了明显的提升。因此,优化的集总参数模型对耦合式MEMS微波功率传感器的设计与优化具有一定的应用价值与参考意义。     

A Sensitivity-Based Design Space Exploration Methodology for Embedded Systems

In this paper, we propose a system-level design methodology for the efficient exploration of the architectural parameters of the memory sub-systems, from the energy-delay joint perspective. The aim is to find the best configuration of the memory hierarchy without performing the exhaustive analysis of the parameters space. The target system architecture includes the processor, separated instruction and data caches, the main memory, and the system buses. To achieve a fast convergence toward the near-optimal configuration, the proposed methodology adopts an iterative local-search algorithm based on the sensitivity analysis of the cost function with respect to the tuning parameters of the memory sub-system architecture. The exploration strategy is based on the Energy-Delay Product (EDP) metric taking into consideration both performance and energy constraints. The effectiveness of the proposed methodology has been demonstrated through the design space exploration of a real-world case study: the optimization of the memory hierarchy of a MicroSPARC2-based system executing the set of Mediabench benchmarks for multimedia applications. Experimental results have shown an optimization speedup of 2 orders of magnitude with respect to the full search approach, while the near-optimal system-level configuration is characterized by a distance from the optimal full search configuration in the range of 2%.     

免疫粒子群算法及其在矿井提升机故障诊断中的应用

基于人工免疫系统的故障诊断方法是人工智能领域发展起来的一个十分活跃的分支.为了提高免疫算法在矿井提升机故障诊断系统中的执行效率,通过对诊断问题进行更精确的建模和分析,提出了将免疫模型和离散粒子群进化算法相结合的提升机系统的故障诊断方法.该方法在免疫形态空间中采用核主元形式的相似性度量,解决了传统距离判别函数法在故障诊断中存在误差较大等问题.仿真结果表明,该方法能够适应诊断过程中出现的不确定性,并实现多故障诊断.     

基于粒子群算法的3维激光雷达回波分解

为了提高3维激光雷达回波分解的精度和准确度,采用粒子群算法与最小二乘法相结合的方法,分析了激光雷达回波分解原理以及粒子群算法原理,研究了粒子群算法在激光雷达回波信号分解中的应用;进行了理论分析与实际数据验证,取得了实际激光雷达回波数据的分解结果。结果表明,采用粒子群算法与最小二乘法相结合的分解方法,激光雷达回波可以更高精度地分解为一系列单个波形的叠加,并获得了延时、强度及脉宽等参量,拟合度提高至0.989,一定程度上抑制了噪声的干扰。该算法可以有效提高激光雷达回波分解的精度。     

基于鲸鱼优化算法的贝叶斯分类器研究与应用

朴素贝叶斯分类器的条件独立性这一假设称为“朴素贝叶斯假设”,其限制了朴素贝叶斯分类的适用范围和分类准确率,为了解决问题,本文提出用改进的鲸鱼优化算法来优化朴素贝叶斯分类器,并对算法进行应用研究。改进的鲸鱼优化算法使用禁忌搜索机制来跳出算法寻优时候易陷入局部最优的误区。为了削弱朴素贝叶斯分类器独立性假设,通过改进的鲸鱼优化算法自动搜索分类器的属性全局性权值,从而提升了加权贝叶斯分类器的运算的准确率。试验证明,相比较传统的朴素贝叶斯分类算法,本文优化后的加权贝叶斯分类算法具有更精准的分类结果。最后提出将改进后的属性加权贝叶斯分类器应用到“移动云”建设的方案。     

面向B5G/6G的三三三网络体系架构和优化学习机制

面对未来B5G/6G网络是大连接复杂智能网络,极其大量的用户连接、需求连接、服务连接,加之3G、4G、5G甚至6G的综合运用,将导致网络变得极其复杂的挑战,提出了一种三三三网络体系架构,它是一个包含3类网络(核心网、接入网、终端网)、3种资源(频率带宽、功耗、时延)和3项需求(生活、工作、服务)的三维立体综合优化的体系...     

Solubility Optimization of Loxoprofen as a Nonsteroidal Anti-Inflammatory Drug: Statistical Modeling and Optimization

Industrial-based application of supercritical CO₂ (SCCO₂) has emerged as a promising technology in numerous scientific fields due to offering brilliant advantages, such as simplicity of application, eco-friendliness, and high performance. Loxoprofen sodium (chemical formula C₁₅H₁₈O₃) is known as an efficient nonsteroidal anti-inflammatory drug (NSAID), which has been long propounded as an effective alleviator for various painful disorders like musculoskeletal conditions. Although experimental research plays an important role in obtaining drug solubility in SCCO₂, the emergence of operational disadvantages such as high cost and long-time process duration has motivated the researchers to develop mathematical models based on artificial intelligence (AI) to predict this important parameter. Three distinct models have been used on the data in this work, all of which were based on decision trees: K-nearest neighbors (KNN), NU support vector machine (NU-SVR), and Gaussian process regression (GPR). The data set has two input characteristics, P (pressure) and T (temperature), and a single output, Y = solubility. After implementing and fine-tuning to the hyperparameters of these ensemble models, their performance has been evaluated using a variety of measures. The R-squared scores of all three models are greater than 0.9, however, the RMSE error rates are 1.879 × 10⁻⁴, 7.814 × 10⁻⁵, and 1.664 × 10⁻⁴ for the KNN, NU-SVR, and GPR models, respectively. MAE metrics of 1.116 × 10⁻⁴, 6.197 × 10⁻⁵, and 8.777 × 10⁻⁵errors were also discovered for the KNN, NU-SVR, and GPR models, respectively. A study was also carried out to determine the best quantity of solubility, which can be referred to as the (x₁ = 40.0, x₂ = 338.0, Y = 1.27 × 10⁻³) vector.     

基于云计算技术的光纤通信网络优化对策分析

近年来,信息科技在我国发展较快,国民对通信网络也有着越来越高的要求.为了保证生产生活等各个方面对通信的要求,我们仍需要不断创新发展通信技术,有效解决光纤通信网络优化等问题.     

光通信中高精度激光束准直系统优化设计

基于空间解析几何与矢量形式的折射定理为基础,研究了非球面、非轴对称的激光束准直光学系统,并对空间光线的传输进行了严格的理论推导,得出了光束发散角的传递矩阵递推公式,并对激光束的发散角进行了优化设计.利用激光束质量诊断仪对准直系统的发散角进行了实验测试,结果表明准直系统能达到较高的准直精度.本设计方法能广泛应用于复杂的非球面光学系统设计中.     

一种求解混合整数非线性规划问题的演化算法--搜索空间自动收缩法

提出一种求解混合整数非线性规划问题的新的演化算法 -搜索空间自动收缩法 (ACSSOS) .在这种算法中 ,演化算法既用来定位最优解区域 ,实现搜索空间自动向全局最优解收缩 ,又用来最终求得最优解 .由于在遗传算子中引用了舍入操作 ,它不仅可用来求解混合非线性整数规划问题 ,也可求解纯整型或纯实型变量非线性函数优化问题 .数值试验结果表明本文的算法在解的质量、稳定性和收敛速度等方面优于一般的演化算法 .