德尔菲法估计初始权数的改进

德尔菲法是估计初始权数时应用最广泛的方法,但传统德尔菲法估计权数的效率和精度都不高,因此,对传统德尔菲法提出了一些改进思想。     

An information delivery model for banking business

Banking is an enterprise consists of different levels of users with the requirement of different levels of information. We propose an information delivery model for banking business which takes information from business analysis and finds the best user for this information with respect to criteria and delivers the multi criteria reporting. There are many multi criteria decision making techniques [MCDM] available to find the best alternative in MCDM problem. We applied fuzzy MCDM technique which resolves inconsistency and uncertainty issues involved in decision making of information delivery for bank users. This model classifies most preferred user to least preferred user for the given information using fuzzy score. This information delivery model and its layers can be applied to other domains to build information delivery model.     

基于OSGI的人力资源绩效考评系统设计与实现

对于人力资源管理来说,科学、合理地评价员工的工作绩效具有非常重要的意义。分析了人力资源绩效考评系统主要功能模块和处理流程,构建了一个人力资源绩效考评模型。介绍了OSGI框架的基本原理,提出了基于OS—GI框架的绩效考评系统架构,并讨论了系统关键技术实现。     

智慧城市建设视角下资源环境承载能力提升路径研究

基于熊彼特创新理论,论证了智慧城市建设对资源环境承载能力的影响机制,利用陕西省2015—2019年的面板数据,结合结构方程模型（SEM）与模糊集定性比较分析法(fsQCA),探索智慧城市建设各维度对资源环境承载能力的影响及多维度间“联合效应”与“互动关系”。研究发现：①智慧环境、智慧人力资本和智慧经济对资源环境承载能力有显著正向效应。②智慧经济在推动资源环境承载能力可载中起到了关键作用。③存在经济拉动型、环境治理型、绿色发展型和创新驱动型等四条智慧城市建设路径可以提升资源环境承载能力,具体可归纳为产业升级推动式和环境规制拉动式。④在一定情形下智慧经济与智慧治理、智慧环境之间具有替代关系。本研究深化了现有智慧城市建设效应理论研究,并为以提升资源环境承载能力为导向的智慧城市建设提供了差异化的方案。     

基于FCM-PFS与PSO-RF的隐性知识外显案例适配研究

对隐性知识外显案例实施有效适配,于知识应用乃至创新、实现乃至增值知识资源的价值,具有重要意义。本文深入研究了隐性知识外显案例适配机理。首先,采用毕达哥拉斯模糊集对知识属性值进行处理,建立知识表达系统;接着,运用K-Means算法对FCM聚类算法进行改进,压缩匹配空间、提升案例匹配效率;而后,基于PFS相关系数求解知识供需间的视图相似度,从而获得适配案例集。在此基础上,构建随机森林适配模型,并采用粒子群算法对其优化,以确保适配效果。与传统算法的对比实验验证了本文算法的比较优势。     

运用Fuzzy公式法对大学生社会适应能力的综合评价

社会适应能力(社会健康)是整体健康的重要组成部分。运用Fuzzy(模糊)公式法，建立大学生社会适应能力综合评价模式，通过分值量化以评价其社会适应能力的高低，为学校培养高素质的人才提供依据，并为维护学生心理健康、促进能力发展、塑造良好德行、形成健全完善人格、提高社会适应能力服务。     

A novel controller design and evaluation for networked control systems with time-variant delays

A new delayed state-variable model for networked control systems is presented, upon which a linear quadratic regulator (LQR) is designed. A method of delays-estimation online is also given. A fuzzy logic with LQR controller is addressed for the difficulty on implementation of LQR in networked control systems (NCSs) with time-variant delays. Simulation results prove that the novel controller can make the system stable and robustly preserve the performance in terms of time-variant delays.     

Information security risk analysis model using fuzzy decision theory

This paper proposes a risk analysis model for information security assessment, which identifies and evaluates the sequence of events – referred to as alternatives – in a potential accident scenario following the occurrence of an initiating event corresponding to abuses of Information Technology systems. In order to perform this evaluation, this work suggests the use of Event Tree Analysis combined with fuzzy decision theory. The contributions of the present proposal are: the development of a taxonomy of events and scenarios, the ranking of alternatives based on the criticality of the risk, considering financial losses, and finally, the provision of information regarding the causes of information system attacks of highest managerial relevance for organizations. We included an illustrative example regarding a data center aiming to illustrate the applicability of the proposed model. To assess its robustness, we analyzed twelve alternatives considering two different methods of setting probabilities of the occurrence of events. Results showed that deliberate external database services attack represent the most risky alternative.     

中厚板轧机模糊PID控制系统的研究

轧机厚度控制系统是轧机最重要的部分之一。本文利用MATLAB模糊逻辑工具箱,建立了以辊缝位置为被控对象的参数自调节模糊PID厚度自动控制系统模型,对轧机自动控制系统进行模糊PID控制。仿真结果表明：模糊PID控制器控制误差小,适应范围广,可以满足生产要求。模糊PID控制技术为解决厚度自动控制提供一种有效途径,同时也为现代工业自动控制问题提供了新的解决方案。     

Performance-oriented parallel distributed compensation

The main idea of the original parallel distributed compensation (PDC) method is to partition the dynamics of a nonlinear system into a number of linear subsystems, design a number of state feedback gains for each linear subsystem, and finally generate the overall state feedback gain by fuzzy blending of such gains. A new modification to the original PDC method is proposed here, so that, besides the stability issue, the closed-loop performance of the system can be considered at the design stage. For this purpose, the state feedback gains are not considered constant through the linearized subsystems, rather, based on some prescribed performance criteria, several feedback gains are associated to every subsystem, and the final gain for every subsystem is obtained by fuzzy blending of such gains. The advantage is that, for example, a faster response can be obtained, for a given bound on the control input. Asymptotic stability of the closed loop system is also guaranteed by using the Lyapunov method. To illustrate the effectiveness of the new method, control of a flexible joint robot (FJR) is investigated and superiority of the designed controller over other existing methods is demonstrated.