对MRP模型改进的研究

通过把ＭＲＰ模型与实际的生产过程进行比较和分析,指出了传统的ＭＲＰ模型的不足之处,提出了改进的ＭＲＰ理论模型．     

稳健二进前向网络的遗传训练方法

稳健二进前向网络是对逻辑知识的隐式表示和显式表示的有机统一,是性能优良的逻辑知识库、推理机和解释器,但目前还没有一种网络训练算法能够训练出稳健二进前向网络,针对这种情况,本文首先对稳健二进前向网络的神经元辅阈值范围进行了改进和有效描述,并在此基础上提出了一种对稳健二进前向网络进行有效训练的遗传训练方法。在这种训练方法中,网络参数采用三值编码方案,并运用相应的变异机制和有效的适应度函数,经这种方法训练出的网络具有结构最优、稳健性能最强和最易实现的特点。文章最后给出了实验的结果。     

适于大斜视角星载SAR系统的改进距离┐多普勒算法

分析了当天线斜视角增大时,导致传统距离－多普勒成像算法性能下降的主要误差来源。提出了一种适合大斜视角星载ＳＡＲ系统的改进距离－多普勒算法,并给出了处理仿真点目标数据得到图像质量的比较。结果表明,在大斜视角情况下,改进算法的性能远大于传统的距离－多普勒成像算法。     

一种鲁棒的被动声目标识别方法

针对噪声环境下一些声目标识别技术性能严重下降的问题,提出了一种基于一阶补偿的径向基函数网络模型,并给出了该网络参数选择方法。实际应用表明,这种神经网络对噪声具有较强的鲁棒性,与传统的径向基函数网络相比,其识别性能等同于信噪比提高大约１０～１５ｄＢ。     

松嫩平原海伦农区种植业与草食动物兼营规模及效益分析

根据松嫩平原农区特点,运用经济分析的方法,对国家农业攻关和重大项目海伦试验基地基点村－胜利村的种植业怀草食动物兼营户的经济效益、规模进行评估分析。在目前生产力水平下,松嫩平原农区兼户的经济效益普遍高于单一种植业户,其生产规模：种植业２ｈｍ＾２－４ｈｍ＾２养牛４－６头 。     

飞行仿真系统RDFSS的实现方法

介绍了飞行指挥实时动态真实感模拟系统（ＲＤＦＳＳ）的整体结构设计思想及实现方法,研究了ＲＤＦＳＳ系统飞行器械的造型、飞行背景及目标拦截模拟方法,简要阐述了我们在研究适合于飞行模拟时所提出的一些新思想、新算法。此系统已在ＳＧＩ工作站上实现,达到了较为真实和实时的良好效果。     

Application of improved equivalent edge currents in synthetic aperture radar imaging

Target modeling and scattering function calculating are important prerequisites and groundwork for the synthetic aperture radar (SAR) imaging simulation. According to the difficult problems that normal methods cannot calculate the scattering function of electrically large object under the condition to wideband, an effective method of improved equivalent edge currents is presented and applied to SAR imaging simulation for the first time. This method improves calculating velocity and has relatively high precision. The concrete steps of applying the method are given. By way of the simulation experiment, the effectiveness of the method is verified.     

Coordinating production and recycling decisions with stochastic demand and return

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time.     

Coordinating pricing and inventory decisions in a bounded production system with uncertain yield

Most inventory researches assume that production level can fluctuate arbitrarily. However, large fluctuation of the production level in many firms may be much costly. This paper addresses the coordinating pricing and inventory control problem in a bounded production system with uncertain yield, in which the production level is constrained between a maximum and minimum level in each period and the price can be adjusted dynamically. We show that the optimal policy is the interval base-stock-list-price policy. Also, we study the impact of the production bounds and uncertainty of the yield on the production system. Numerical experiments are also performed to study the impact of parameters on the system.     

Stock loan valuation under a regime-switching model with mean-reverting and finite maturity

<正> Stock loans are business contracts between borrowers and lenders in which the borroweruses shares of stock as collateral for the loan.Since the value of the collateral is subject to wide andfrequent price swings,valuing such a transaction behaves more like an option pricing problem thana debt valuation problem.This paper will list,prove,and analyze formulas for stock loan valuationwith finite horizon under various stock models,including classical geometric Brownian motion,meanreverting,and two-state regime-switching with both mean-reverting and geometric Brownian motionstates.Numerical examples are reported to illustrate the results.