ID 原文 译文
11594 根据诊断解的结构分析了基于第一原理诊断方法中诊断解的分布,并利用分析结果证明了新的诊断方法在效率上优于传统的诊断方法。 According to the principle of diagnosis of solution structure is analyzed based on the first diagnosis method in the diagnosis of solution of distribution, and use the analysis results show that the new diagnostic method is superior to the traditional diagnosis methods in efficiency.
11595 通过引入"时间戳"和"状态锁",使得诊断方法能够自主地处理遥测数据在不同输入方式下的诊断问题。 By introducing "timestamp" and "state of the lock", the diagnostic method can independently deal with remote sensing data under different input methods of diagnosing the problem.
11596 为避免由于网络负载抖动而造成的频繁网络选择,本文为无线异构网络提出了一种预测网络未来负载的自适应负载均衡算法。 In order to avoid because of the network load jitter caused by the frequent network selection, this paper for heterogeneous wireless network presents a prediction network load adaptive load balancing algorithm in the future.
11597 通过马尔可夫链预测负载状态空间的概率,将预测到的概率通过负载趋势函数映射为趋势值,利用趋势值进行网络选择和自适应触发门限的调整。 ‭By markov chain to predict the probability of load state space, will predict the trend of probability through the load function mapping for trend value, using the trend values for network selection and adjustment of adaptive trigger threshold.
11598 仿真结果表明,该算法能有效降低接入阻塞率及均衡切换次数。 ‭The simulation results show that the proposed algorithm can effectively reduce the access model. ‭next and balanced switching times. ‭
11599 支持向量数据描述(support vector data description,SVDD)是一种具有单类数据描述能力的数据分类算法,因具有结构风险最小化的特性而受到广泛关注。 Support vector data description (support vector data description, the SVDD) is a data classification algorithm with single class data description ability, has the character of structure risk minimization by and attracted much attention.
11600 SVDD的参数优化是影响其分类效果的关键问题。 Parameter optimization of SVDD is the key problems affecting the classification effect.
11601 本文通过引入样本点的密度信息,提出了以界外密度最小化为目标的参数优化函数,避免了漏检率的计算问题。 In this paper, by introducing the density of sample points information, is put forward to out the goal of minimizing parameter optimization function density, avoid the problem of miss rate calculation.
11602 可充分利用训练数据的分布信息,提高数据描述能力,降低错分率。 Can make full use of the distribution information of training data, improve the ability of data description, reduce the rate of wrong points.
11603 仿真实验和UCI标准数据库的对比验证表明,优化后的SVDD算法能够有效降低漏检率和错分率,提高算法性能。 Simulation results and the comparison of UCI standard database validation show that the optimized SVDD algorithm can effectively reduce miss rate and fault rate, improve the algorithm performance.