模式识别方法研究影响转炉炼钢脱磷的因素

利用模式识别方法中的偏最小二乘法对转炉炼钢的磷分配比及主要影响因素进行了分析 ,用二维分类图给出了优化趋势 ,结果符合一般脱磷理论和实际 ,可以作为冶炼的参考。     

模具生产联合体加工作业统一调度问题的研究

模具生产联合体是由小规模企业组成的模具设计、制造联盟，由于设备、工装和人员分属于不同的加盟企业，其作业排序过程非常复杂。为此提出一种复合式模具生产联合体的生产排序方法：依据基本优先规则首先完成单一工序作业，然后对多工序作业用改进遗传算法进行工艺优化，求出最优解和次优解，再使用评价函数法选择最佳作业路线。该方法在生产试验中取得了良好的成效．能较好满足模具用户和加盟企业两方面的需要。     

Dual–primal proximal point algorithms for extended convex programming

This paper presents a class of dual–primal proximal point algorithms (PPAs) for extended convex programming with linear constraints. By choosing appropriate proximal regularization matrices, the application of the general PPA to the equivalent variational inequality of the extended convex programming with linear constraints can result in easy proximal subproblems. In theory, the sequence generated by the general PPA may fail to converge since the proximal regularization matrix is asymmetric sometimes. So we construct descent directions derived from the solution obtained by the general PPA. Different step lengths and descent directions are chosen with the negligible additional computational load. The global convergence of the new algorithms is proved easily based on the fact that the sequences generated are Fejér monotone. Furthermore, we provide a simple proof for the O(1/t) convergence rate of these algorithms.     

一种相控阵天线安装精度检测与校准

文中论述了一种相控阵雷达天线安装后的精度检测方法。按照雷达天线安装后的几何形态,采用光学测量仪器进行相关的数据采集,建立检测的数学模型,利用线性回归法以及最小二乘法进行数据拟合,计算出安装后雷达天线底面与水平面的最大夹角和天线边缘与正北方向的夹角,并进行了试验误差评估和分析,依据检测数据对雷达天线的水平和方位角度进行校...     

A novel artificial bee colony algorithm with Powell's method

Artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To address this concerning issue, we first propose a modified search equation which is applied to generate a candidate solution in the onlookers phase to improve the search ability of ABC. Further, we use the Powell's method as a local search tool to enhance the exploitation of the algorithm. The new algorithm is tested on 22 unconstrained benchmark functions and 13 constrained benchmark functions, and are compared with some other ABCs and several state-of-the-art algorithms. The comparisons show that the proposed algorithm offers the highest solution quality, fastest global convergence, and strongest robustness among all the contenders on almost all test functions.     

PSO和K均值混合分类算法在远程教学系统中的应用

现行的多数网络教学系统在学生按需学习和＂因材施教＂上存在局限性,本文用PSO和K均值的混合分类算法对传统的网络教学系统进行改进,根据获取的用户基本信息和兴趣特征进行聚类,充分体现＂以学习者为中心＂个性化教学模式。实验结果表明,该算法具有较好的全局收敛性,寻优能力明显提升。     

自适应均衡器的FPGA实现

在无线通信系统中,由于多径效应的干扰导致信号在传输过程中不可避免地产生码间干扰,因此必须在接收端增加均衡器,以消除码间干扰,提高传输质量。该自适应均衡器设计以FPGA为设计平台,使用自上而下的模块化的设计方法,利用StratixⅡ系列EP1C20F324C6芯片,采用横向滤波器结构,设计并行结构的8阶复数滤波器。最后在QuartusⅡ中进行仿真与综合,结果显示I、Q两路误差信号趋于零,从而实现自适应均衡,降低误码率。     

Web proxy cache replacement scheme based on back-propagation neural network

Web proxy caches are used to reduce the strain of contemporary web traffic on web servers and network bandwidth providers. In this research, a novel approach to web proxy cache replacement which utilizes neural networks for replacement decisions is developed and analyzed. Neural networks are trained to classify cacheable objects from real world data sets using information known to be important in web proxy caching, such as frequency and recency. Correct classification ratios between 0.85 and 0.88 are obtained both for data used for training and data not used for training. Our approach is compared with Least Recently Used (LRU), Least Frequently Used (LFU) and the optimal case which always rates an object with the number of future requests. Performance is evaluated in simulation for various neural network structures and cache conditions. The final neural networks achieve hit rates that are 86.60% of the optimal in the worst case and 100% of the optimal in the best case. Byte-hit rates are 93.36% of the optimal in the worst case and 99.92% of the optimal in the best case. We examine the input-to-output mappings of individual neural networks and analyze the resulting caching strategy with respect to specific cache conditions.