基于神经网络的建筑行业投标报价研究

在建筑行业的投标报价过程中，如何在众多的信息中选出对最终报价影响较大的几项因素以及如何确定这些因素与最终报价之间的关系是一个棘手的问题．论文针对这两大难题提出了基于神经网络技术的解决方法．首先根据贡献变量分析理论确定出影响报价结果的9个报价因素，从而建立起基于神经网络的报价模型，然后在所确定模型的基础上改进传统的BP算法，进一步提高网络的泛化能力．从实际应用的结果可以看出，经过变量选择后所确定的报价因素是合理的，改进学习算法后的网络的泛化能力也有了很大的提高．     

Non-Minimum Phase Nonlinear System Predictive Control Based on Local Recurrent Neural Networks

Abstract: After a recursive multi-step-ahead predictor for nonlinear systems based on local recurrent neural networks isintroduced, an intelligent PID controller is adopted to correct the errors including identified model errors and accumulatederrors produced in the recursive process. Characterized by predictive control, this method can achieve a good controlaccuracy and has good robustness. A simulation study shows that this control algorithm is very effective.     

FROM MANUFACTURING SCHEDULING TO SUPPLY CHAIN COORDINATION：THE CONTROL OF COMPLEXITY AND UNCERTAINTY

With time-based competition and rapid technology advancements, effective manufacturingscheduling and supply chain coordination are critical to quickly respond to changing marketconditions. These problems, however, are difficult in view of inherent complexity and variousuncertainties involved. Based on a series of results by the authors, decomposition and coordination byusing Lagrangian relaxation is identified in this paper as an effective way to control complexity anduncertainty.A manufacturing scheduling problem is first formulated within the job shop context withuncertain order arrivals, processing times, due dates, and part priorities as a separable optimizationproblem. A solution methodology that combines Lagrangian relaxation, stochastic dynamicprogramming, and heuristics is developed. Method improvements to effectively solve large problemsare also highlighted. To extend manufacturing scheduling within a factory to coordinate autonomicmembers across chains of suppliers, a decentralized supply chai     

Petri网络在无控制交叉口延误分析中的应用

选用比较适合描述系统组织结构和动态行为的Petri网络模型对主路优先通行的无信号交叉口运行过程建立HSPN模型．在此基础上，结合间隙接受理论，对无控制交叉口进行平均延误分析探索，为交叉口仿真控制软件的研发奠定了算法基础。     

对城市供水行业改革的思考

分析了目前各地供水行业改革中遇到的问题,提出了加强政府对供水行业的监管力度,慎重选择投资主体和特许经营者,理顺供水价格调整机制等城市供水行业改革的措施。     

Discovering Frequent Subtrees from XML Data Using Neural Networks

By rapid progress of network and storage technologies, a huge amount of electronic data such as Web pages and XML has been available on Internet. In this paper, we study a data-mining problem of discovering frequent ordered sub-trees in a large collection of XML data, where both of the patterns and the data are modeled by labeled ordered trees. We present an efficient algorithm of Ordered Subtree Miner （OSTMiner） based on two- layer neural networks with Hebb rule, that computes all ordered sub-trees appearing in a collection of XML trees with frequent above a user-specified threshold using a special structure EM-tree. In this algo- rithm, EM-tree is used as an extended merging tree to supply scheme information for efficient pruning and mining frequent sub-trees. Experiments results showed that OSTMiner has good response time and scales well.     

鸟类对接触网运行的影响及预防

鸟害是影响接触网正常运行的一种自然灾害,如何预防鸟害成为各运营单位亟待解决的问题。分析了鸟巢和隧道(或明洞)处鸟类对接触网的影响,并提出了针对性的解决方案。     

传感器网络推拉混合模式代码传输方法

代码传输是实现无线传感器网络应用重构的关键技术.首先研究传感器网络环境自适应应用重构(EAAR)模型的两种代码传输模式-拉模式和推模式,并结合两种模式的特点提出一种适用于分簇传感器网络的能量有效代码传输模式-基于簇的混合代码传输(Cluster-based Hybrid Code Transmission, CHCT).在该模式下,簇头节点采用拉方式从基站获取代码,簇内节点采用推方式进行代码传输.仿真实验验证了方法的有效性并讨论了影响CHCT性能的主要参数.     

分布控制型供应链的多层规划模型研究

研究分布控制型供应链的生产、配送与库存决策问题,通过分析成员的独立决策行为,针对供应链系统上下层之间所具有的Stackelberg博弈特征,建立多层规划模型,最后利用交互式多层模糊算法进行求解.     

需求特征对供应链中企业资源再利用的影响分析

为了了解需求因素对供应链中企业资源再利用的影响,选取工业园上下游企业的相互联系为分析背景,建立企业间的供应链模型,研究了需求不确定性σ和需求弹性k对供应链中企业资源再利用的影响.模型仿真结果表明:对存在物料供需关系的2个企业来说,随着主产品需求不确定性σ的不断增大,2个企业的总利润π呈不断下降的趋势,销售损失和库存成本增加,企业资源再利用受到阻碍;随着弹性因子k的不断增大,需求批量与供给批量差距呈现出一种先减小后增大的趋势,总利润π减小,对企业资源再利用起到了负面的影响,阻碍其发展.