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关键词： 藕渣   膳食纤维   液态发酵   人工神经网络   遗传算法  

摘要： 为实现莲藕副产物的高值化应用以及藕渣可溶性膳食纤维(soluble dietary fiber,SDF)含量的提高,该文以藕渣为原料,接种副干酪乳杆菌PC18发酵改性制备藕渣可溶性膳食纤维,通过单因素试验及Box-Behnken试验设计,探讨料液比、发酵时间、接种量对藕渣可溶性膳食纤维含量的影响,在此基础上,选用响应面(response surface methodology,RSM)和人工神经网络-遗传算法(artificial neural networks and genetic algorithms,ANN-GA)构建发酵模型,并对两者优化结果及模型参数进行比较。单因素及Box-Behnken试验结果表明,影响藕渣SDF含量主要因素主次顺序依次为发酵时间、料液比、接种量。通过验证试验及模型参数与优化结果对比分析,发现RSM与ANN-GA构建的模型整体拟合效果均较好,但ANN-GA模型预测值、试验值更高,相对误差值更低。基于ANN-GA确定最佳工艺参数为料液比1∶38(g/mL)、发酵时间48 h、接种量4.0%,经验证得到此条件下SDF含量为(5.97±0.73)%。

关键词： 无人机配送   应急物流   选址-路径优化   旅行商问题   迭代启发式算法  

摘要： 灾害情况下物资海岛配送是应急物流的一种特殊应用场景.无人机配送作为解决应急物流问题的一种新型配送方式受到广泛关注,并涌现出了一系列配送模式.通过考虑无人机成本、无人机飞行距离、无人机起降平台和地面配送成本,构建无人机直接配送、点对点双阶段配送、回路双阶段配送和双层物流配送网络4种配送模式.针对回路双阶段配送的多指标耦合特征,提出一种迭代启发式算法进行优化.围绕普陀山海岛场景,构建20~100个需求点和2~4个无人机起降平台的算例进行数值实验,分析并验证模型正确性和算法性能.实验结果表明,4种配送模式模型具有有效性;算法一般经过2~5次迭代,能够有效减少回路双阶段配送约19.08%的无人机飞行距离,减少双层物流配送网络约28.63%的地面配送距离.

关键词： 价值函数   策略函数   多层感知机MLP   站用直流电源系统   电源故障   故障预判  

摘要： 在站用直流电源系统电源故障预测过程中,主要依托于单一的价值函数实现故障预判,无法应对策略微弱变化引起的维度爆炸等问题,使得故障预判结果的G-mean值较低。因此,提出结合价值函数和策略函数的站用直流电源系统电源故障预判算法。针对电源历史运行参数进行归一化处理,经过灰色分析处理筛选出符合要求的参数,组成故障预判分析数据集。以描述数据序列方差变化为目标,构建改进价值函数。利用改进的价值函数和策略函数组成强化学习智能体,设计包含多层感知机网络的电源故障预判模型。经过数据训练调整模型处于最优状态,获取高质量的直流电源系统电源故障预判结果。实验结果表明:所提算法得出的电源故障预判结果G-mean值为0.98,保证了故障预判结果的准确性。

关键词： Radar cross section  

摘要： The sixth-generation fighter has superior stealth performance, but for the traditional kernel density estimation (KDE), precision requirements are difficult to satisfy when dealing with the fluctuation characteristics of complex radar cross section (RCS). To solve this problem, this paper studies the KDE algorithm for F/A-XX stealth fighter. By considering the accuracy lack of existing fixed bandwidth algorithms, a novel adaptive kernel density estimation (AKDE) algorithm equipped with least square cross validation and integrated squared error criterion is proposed to optimize the bandwidth. Meanwhile, an adaptive RCS density estimation can be obtained according to the optimized bandwidth. Finally, simulations verify that the estimation accuracy of the adaptive bandwidth RCS density estimation algorithm is more than 50% higher than that of the traditional algorithm. Based on the proposed algorithm (i.e., AKDE), statistical characteristics of the considered fighter are more accurately acquired, and then the significant advantages of the AKDE algorithm in solving cumulative distribution function estimation of RCS less than 1 m2 are analyzed. © Shanghai Jiao Tong University 2022.

关键词： Complex networks  

摘要： One of the most important problems in complex networks is to identify the influential vertices for understanding and controlling of information diffusion and disease spreading. Most of the current centrality algorithms focus on single feature or manually extract the attributes, which occasionally results in the failure to fully capture the vertex’s importance. A new vertex centrality approach based on symmetric nonnegative matrix factorization (SNMF), called VCSNMF, is proposed in this paper. For highlight the characteristics of a network, the adjacency matrix and the degree matrix are fused to represent original data of the network via a weighted linear combination. First, SNMF automatically extracts the latent characteristics of vertices by factorizing the established original data matrix. Then we prove that each vertex’s composite feature which is constructed with one-dimensional factor matrix can be approximated as the term of eigenvector associated with the spectral radius of the network, otherwise obtained by the factor matrix on the hyperspace. Finally, VCSNMF integrates the composite feature and the topological structure to evaluate the performance of vertices. To verify the effectiveness of the VCSNMF criterion, eight existing centrality approaches are used as comparison measures to rank influential vertices in ten real-world networks. The experimental results assert the superiority of the method. © Shanghai Jiao Tong University 2022.

关键词： FIR filters  

摘要： This paper presents a distributed arithmetic (DA) architecture that can efficiently implement finite impulse response (FIR) filters for biomedical signal processor applications. FIR filter design is more efficient when it uses a look-up table (LUT)-based technique rather than a serial one. The design’s performance and efficiency can be improved by using segmented memory banks as well as memory lookup for multiply operation. Verilog HDL is used to model the proposed design, and Synopsys Design Compiler tool is used for synthesis. The FIR filter architecture utilizing DA results in a 24.82% reduction in total power compared with the serial FIR structure. © Shanghai Jiao Tong University 2022.

关键词： Extended Kalman filters  

摘要： In the case of a medium-long baseline, for real-time kinematic (RTK) positioning, the fixed rate of integer ambiguity is low due to the distance between the base station and the observation station. Moreover, the atmospheric delay after differential processing cannot be ignored. For correcting the residual atmospheric errors, we proposed that a GPS/BDS/Galileo/GLONASS four-system fusion RTK positioning algorithm, which is based on the extended Kalman filter (EKF) algorithm. After realizing the spatio-temporal unification of multiple global navigation satellite systems (GNSSs), we introduced a parameter estimation of atmospheric errors based on the EKF model, using the least-squares integer ambiguity decorrelation adjustment (LAMBDA) to calculate the integer ambiguity. After conducting experiments for different baselines, the proposed RTK positioning algorithm can achieve centimeter-level positioning accuracy in the case of medium-long baselines. In addition, the time required to solve the fixed solution is shorter than that of the traditional RTK positioning algorithm. © Shanghai Jiao Tong University 2022.

关键词： 谱聚类   车辆路径规划   多车场车辆路径规划   启发式算法   组合优化  

摘要： 针对现有启发式算法在解决大规模多车场车辆路径规划问题时存在的初始解质量较差的缺点，提出了一种基于带约束谱聚类（CSC）的启发式车辆路径规划算法优化方法。首先，根据待配送客户点的地理位置和需求量生成配送点的地理信息特征矩阵和需求信息特征矩阵；其次，根据地理信息特征矩阵和需求信息特征矩阵生成带约束谱聚类的约束矩阵，并完成聚类操作；最后，使用谱聚类的结果生成启发式算法的初始解，选择合适的启发式算法完成车辆路径规划问题的求解。在标准数据集的21个算例上的实验中，CSC相较于SCSC(Self-Constrained-Spectral-Clustering)在聚类的两个指标标准化互信息和Fowlkes-Mallows指数上分别提升了18%和31%；在车辆路径规划任务中，使用CSC进行初始化的启发式算法在76%的算例上求得了最短路径，并且启发式算法的运行时间相较于使用SCSC缩短了13%。实验结果表明CSC能够有效提高客户点的聚类精度，进而能够有效提高车辆路径规划问题的求解速度和解的精度。