可动凝胶深部调驱候选井筛选方法研究

根据可动凝胶深部调驱机理,结合注水井和对应油井的静、动态特征,筛选出了用于确定最佳调驱井的指标体系,并采用变权的模糊综合评判方法进行多因素定量评价。结果表明,用渗透率非均质性、吸水剖面非均质性、吸水强度、井口压降曲线、含水-采出程度对应关系、油水井连通程度、油层未动用程度及沉积相特征等指标来筛选调驱注入井可提高选井的可靠性,保证可动凝胶深部调驱的效果。     

基于FAHP的制导雷达技术性能评估方法研究

针对复杂使用条件下制导雷达系统综合技术性能的模糊性和不确定性,运用模糊层次分析法对制导雷达系统的技术性能进行了综合评估,解决了一般层次分析法标度复杂、判断矩阵一致性不易实现的问题,建立了多级评估体系模型,给出了确立各指标权重的方法.最后通过实例分析,证明了该方法的有效性和准确性.     

马尔柯夫链预测法在证券指数预测中的应用

介绍马尔柯夫链预测法的模糊模型，该模型以集合的模糊划分为依据摒弃了清晰划分的不足．从而保证预测结果的精确性。将该模型应用在证券指数的预测上，取得了绝对误差、相对误差较小的结果。     

自适应比例因子模糊控制器在异步电动机调速系统中的应用

为了降低转子电阻变化对异步电动机矢量控制系统性能的影响，本文把自适应比例因子模糊控制器应用到了矢量控制系统中。介绍了自适应比例因子模糊控制方法的綦本原理，给出了使用自适应比例因子模糊控制器的异步电动机矢量控制系统的结构框图，对主模糊控制器和辅助模糊控制器进行了设计。仿真实验结果表明，采用这种控制方法的调速系统不仅具有优良的动态性能，而且对转子电阻变化具有很强的鲁棒性。     

Fixed point theorems on fuzzy normed linear spaces

In this paper, definitions of strongly fuzzy convergent sequence, l-fuzzy weakly convergent sequence and l-fuzzy weakly compact set are given in a fuzzy normed linear space. The concepts of fuzzy normal structure, fuzzy non-expansive mapping, uniformly convex fuzzy normed linear space are introduced and fixed point theorems for fuzzy non-expansive mappings are proved.     

Genetically optimized fuzzy polynomial neural networks with fuzzy set-based polynomial neurons

In this paper, we propose and investigate a new category of neurofuzzy networks—fuzzy polynomial neural networks (FPNN) endowed with fuzzy set-based polynomial neurons (FSPNs) We develop a comprehensive design methodology involving mechanisms of genetic optimization, and genetic algorithms (GAs) in particular. The conventional FPNNs developed so far are based on the mechanisms of self-organization, fuzzy neurocomputing, and evolutionary optimization. The design of the network exploits the FSPNs as well as the extended group method of data handling (GMDH). Let us stress that in the previous development strategies some essential parameters of the networks (such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of the specific subset of input variables) being available within the network are provided by the designer in advance and kept fixed throughout the overall development process. This restriction may hamper a possibility of developing an optimal architecture of the model. The design proposed in this study addresses this issue. The augmented and genetically developed FPNN (gFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNNs. The GA-based design procedure being applied at each layer of the FPNN leads to the selection of the most suitable nodes (or FSPNs) available within the FPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gFPNN is quantified through experimentation in which we use a number of modeling benchmarks—synthetic and experimental data being commonly used in fuzzy or neurofuzzy modeling. The obtained results demonstrate the superiority of the proposed networks over the models existing in the references.     

虚拟环境下自主水下航行器的避障研究

为了在虚拟环境下模拟自主水下航行器的水平面避障过程，基于软件平台MultiGen Creator和Vega，在HP工作站上开发了自主水下航行器避障视景仿真系统。提出了一种前视声纳的仿真方法，利用Vega提供的碰撞矢量函数和自定义的Volume碰撞方式，模拟前视声纳的功能，并根据声纳所测得的障碍物相对于自主水下航行器的位置关系设计一个模糊推理系统来求解其避障角度，实现了虚拟环境下自主水下航行器的水平面避障。仿真结果表明，该视景仿真能够使仿真系统更加逼真和接近于实际情况，并且满足系统仿真的实时性要求。     

On a responsive replenishment system: a fuzzy logic approach

In today's competitive business environment, it is important that customers are able to obtain their preferred items in the shops they visit, particularly for convenience store chains such as 7–Eleven where popular items are expected to be readily available on the shelves of the stores for buyers. To minimize the cost of running such store chains, it is essential that stocks be kept to a minimum and at the same time large varieties of popular items are available for customers. In this respect, the replenishment system needs to be able to cope with the taxing demands of minimal inventory but at the same time keeping large varieties of needed items. This paper proposes a replenishment system which is able to respond to the fluctuating demands of customers and provide a timely supply of needed items in a cost–effective way. The proposed system embraces the principle of fuzzy logic which is able to deal with uncertainties by virtue of its fuzzy rules reasoning mechanism, thereby leveraging the responsiveness of the entire replenishment system for the chain stores. To validate the feasibility of the approach, a case study has been conducted in an emulated environment with promising results.     

基于模糊控制的气体流量控制系统

应用热式质量流量计直接测量气体质量流量。高性能AT89S51单片机作为控制器核心，并对控制量采用模糊控制算法。介绍了气体流量控制系统设计方法，给出了硬件原理图和软件主程序流程图。     

基于遗传算法的模糊关系方程求解

针对模糊关系方程的求解问题,即模糊综合评判逆问题,提出了一种基于遗传算法的求解方法.算法能有效地找出模糊关系方程的全局近似最优解,并且与模糊关系合成算子的具体形式无关,有良好的鲁棒性和自适应能力.仿真结果表明,此方法是一种有效、实用的模糊关系方程求解方法.