A hierarchical strategy for solving traveling salesman problems using elastic nets

In this article, we focus on implementing the elastic net method to solve the traveling salesman problem using a hierarchical approach. The result is a significant speed-up, which is studied both analytically and experimentally.     

四端光纤补偿网络的理论分析

强度干扰是阻碍强度调制光纤传感器发展及应用的关键问题.研究表明,光纤网络补偿方法对抑制强度干扰是一种行之有效的方法.作者经过深入的研究,提出了一种先进的四端光纤补偿网络结构.本文对四端光纤补偿网络进行了全面、系统的分析,揭示了网络的特性.这对于强度调制光纤传感器的发展及应用具有重要的意义.同时,对于强度调制光学测量系统也具有一定的意义.     

Reinforcement learning versus heuristics for order acceptance on a single resource

Order Acceptance (OA) is one of the main functions in business control. Accepting an order when capacity is available could disable the system to accept more profitable orders in the future with opportunity losses as a consequence. Uncertain information is also an important issue here. We use Markov decision models and learning methods from Artificial Intelligence to find decision policies under uncertainty. Reinforcement Learning (RL) is quite a new approach in OA. It is shown here that RL works well compared with heuristics. It is demonstrated that employing an RL trained agent is a robust, flexible approach that in addition can be used to support the detection of good heuristics.     

交联网络和浓溶液中高分子链运动的NMR研究Ⅰ.NMR质子线型分析

用质子ＮＭＲ谱对交联凝胶高分子（聚丙烯酰胺－丙烯酸）网络与线型高分子（聚苯乙烯）浓溶液体系的ＮＭＲ线型进行了比较研究。结果表明，两种体系中高分子链段运动具有不同的特征：在充分溶胀的交联凝胶高分子网络中，交联点间的链段运动比较自由，交联点的运动则比较慢，使其质子谱呈现“超洛伦兹”线型；而在线型高分子浓溶液中，缠结点间的链段与缠结点一样，运动并不自由，使谱线呈现出类似固体的宽线宽的高斯线型     

人工神经网络在配煤过程状态建模中的应用研究

本文详细介绍了人工神经网络应用于状态建模的方法．对神经网络应用中的一些难点提出了切实可行且有效的解决措施，并举例作了应用示范．同时还介绍了神经网络方法应用于优化动力配煤的情况，并就神经网络方法在优化动力配煤中的进一步应用作了展望．     

基于径向基函数神经网络的流程企业供应链预测仿真

本文在比较预测方法的基础上，采用径向基函数（RBF）神经网络技术建立流程企业供应链预测模型，进行了实例预测仿真，并将预测结果与BP网络的预测结果进行了比较。结果表明，RBF网络误差小于BP网络，其中平方根RBF网络的预测仿真误差最小，而BP网络的误差最大。     

On the existence of hyper-L triple-loop networks

Aguiló-Gost [New dense families of triple loop Networks, Discrete Math. 197/198 (1999) 15-27] has presented a new type of hyper-L tiles and used it to derive a new dense family of triple-loop networks. While Aguiló-Gost's hyper-L tile seems to be a promising tool for studying the triple-loop networks, we need to verify that the hyper-L tile producing good result is indeed the MDD of some triple-loop network. In this paper, we give necessary and sufficient conditions for the existence of Aguiló-Gost's hyper-L triple-loop networks and we correct some flaws in [F. Aguiló-Gost, New dense families of triple loop networks, Discrete Math. 197/198 (1999) 15-27].     

人工神经网络光度法用于化探样品中金的形态分析

利用人工神经网络对化探样品中金的三种存在形态（水提取态、吸附态、有机态）的含量同时进行了预测，计算结果与传统浸了方法的结果相吻合，相对误差一般小于10％，相对标准偏差在1．68％－8．94％。该法简便，快速。     

Revisiting parametric multi-terminal problems: Maximum flows, minimum cuts and cut-tree computations

Given an undirected network, the multi-terminal network flows analysis consists in determining the all pairs maximum flow values. In this paper, we consider an undirected network in which some edge capacities are allowed to vary and we analyze the impact of such variations on the all pairs maximum flow values. We first provide an efficient algorithm for the single parametric capacity case, and then propose a generalization to the case of multiple parametric capacities. Moreover, we provide a study on Gomory–Hu cut-tree relationships.     

Existence and Exponential Stability of Almost Periodic Solution for Hopfield Neural Network Equations with Almost Periodic Imput

By constructing Liapunov functions and building a new inequality, we obtain two kinds of sufficient conditions for the existence and global exponential stability of almost periodic solution for a Hopfield-type neural networks subject to almost periodic external stimuli. In this paper, we assume that the network parameters vary almost periodically with time and we incorporate variable delays in the processing part of the network architectures.