基于DEA和灰色关联度的区域科技生态化创新绩效研究

构建了区域科技生态化创新绩效的评价指标体系,并采用DEA和灰色关联度对江苏省13个城市进行了实证研究.结果表明,江苏省13个城市科技生态化创新大都处于良好的发展态势,其中,科技活动人员占从业人员比重对创新绩效影响最大,其次是RD活动人员占科技活动人员比重,影响最小的因素是企业RD经费占销售收入的比例.     

基于模糊数学的城市桥梁技术状况评价

准确的评价城市桥梁的技术状况是保证其运营安全与养护决策的前提.由于影响城市桥梁技术状况的因素复杂多样,综合考虑桥面系、上部结构、下部结构指标构建了城市桥梁技术状况综合评价体系.以保定城市桥梁的检测项目为依托,基于上述三个指标,提出了基于模糊数学的大陆性季风气候区城市桥梁技术状况评价方法.结果表明:(1)随着时间的推移,城市桥梁桥面系质量状况与上部、下部结构状况相比,衰退趋势明显,主要与影响其性能的气候及交通状况有关;(2)研究使用因子域、注释级别域、模糊关系矩阵、评价因子全矢量和模糊综合评价结果向量五步法,该方法可以有效的与规范中使用的评分指标相结合;(3)在规范中采用的多指标综合评估的基础上,通过模糊数学的迭代运算,突破了传统评估方法的主观随意性,改进了评判分析的不确定性,对城市桥梁技术状况进行了定量评估;(4)研究结果为城市桥梁技术状况的准确评价和分析提供了理论方法,也为城市桥梁养护及决策提供了技术支撑.     

城镇生态系统的因子分析

本文从自然、经济、社会和环境四方面构建了城镇生态系统的指标体系 ,提出了评价生态化程度的因子分析方法 ,并对张家港市城镇生态化程度进行了分析     

国内主要城市空气质量统计分析

我国目前评价城市空气质量所用的空气污染指数法中仅以首要污染指数来反映空气质量状况,而忽视了次要污染物对空气质量的影响,这将会使评价结果的准确性产生偏差.本文在空气污染指数模型的基础上引入次要污染物,建立了新的空气质量评价模型,再利用该模型对我国近三年主要城市空气质量状况进行了评价及分析.     

基于改进TOPSIS方法的珠三角城市民生状况评价

从系统论角度出发,构建了民生改善循环系统模型,提出了涵盖社会发展、经济发展、生态环境、民生改善的民生状况评价指标体系,并采用改进TOPSIS方法对珠三角地区九个城市的民生状况进行评价,根据评价结果将九个城市民生建设分为突出发展型、(相对)均衡发展型、非均衡发展型和边缘发展型.     

基于灰区间数决策的城市土地集约利用评价

城市土地集约利用评判是典型的区间数多属性决策问题,将基于灰色系统理论的多指标灰区间数关联决策模型应用于城市土地利用状况评价领域,通过引入灰区间数序列的范数完成多指标区间数决策矩阵的规范化处理,建立了多指标区间数整体逼近决策方法,使城市土地集约利用评判方法更加客观.最后通过扬州市城市土地利用状况为实例验证模型的有效性和实用性,为城市土地集约利用评价提供了一种新方法.     

城市可持续发展综合评价方法及应用

建立了基于层次分析法的城市可持续发展综合评价方法 ,以城市可持续发展理想状态的各项指标值为参照 ,可对任一城市的可持续发展水平进行相对评估 .最后 ,以国外先进国家的平均发展水平为参照 ,对深圳市近年来可持续发展状况进行了综合评价与分析 .     

基于灰色关联分析的河南各市可持续发展状况综合评价

构建合适的可持续发展综合指标体系,并获取河南17个城市2003年到2013年10年内的指标数据,运用灰色系统理论中的灰色关联分析对六个城市的可持续发展状况排序,然后以灰色系统为核心研究工具,运用灰色综合评价法对评价数据进行分析得出最佳的城市可持续发展指标体系的指标数据.最后提出了优化城市发展的若干建议.     

灰色聚类法在三峡库区城市江段水质综合评价中的应用

应用灰色聚类法对三峡库区城市江段13个监测断面水质质量进行综合评价,获得较好的结果,能客观反映三峡库区城市江段质的类别及水体实际污染的状况.通过与模糊综合评价方法进行比较,灰色聚类法具有计算简便的优点,是一种较好的评价方法.     

基于DPSIR模型的城市大气环境发展指数研究

随着我国工业化和城市化进程的不断加快,城市大气环境发展状况越来越受到学术界的关注。针对城市化进程等因素给城市大气环境带来的挑战和威胁, 文章将指数的概念引入到城市大气环境评价领域,根据城市化等因素与城市大气环境发展变化之间的响应机理,基于DPSIR模型建立了一套城市大气环境发展指数测度指标体系与方法,并以杭州市为例,对该市2005~2014年的大气环境发展指数进行了测度和分析。文章为城市大气环境发展状况进行测度和对比分析提供了一套方法体系,使城市大气环境发展指数服务于政府管理者、城市居民等利益相关者,为城市大气环境发展管理带来新变革。     

基于指标均衡和权重区间数的供应链合作伙伴选择方法

本提出基于指标均衡和权重区间数的供应链合作伙伴选择方法。该方法在对指标无量纲化的基础上，考虑指标均衡使得指标间的协调和均衡程度在评价过程中得到反映，使用区间数使得模型具有较大的伸缩性和柔性，符合人们模糊认识规律，通过收集不同阶段的评价数据可以反映动态评价的特点。最后通过实例对该方法进行了详细说明。通过比较考虑均衡度与否得到的不同结果，发现当考虑均衡度时可以放大评价结果之间的差距。     

LAHS: A novel harmony search algorithm based on learning automata

This study presents a learning automata-based harmony search (LAHS) for unconstrained optimization of continuous problems. The harmony search (HS) algorithm performance strongly depends on the fine tuning of its parameters, including the harmony consideration rate (HMCR), pitch adjustment rate (PAR) and bandwidth (bw). Inspired by the spur-in-time responses in the musical improvisation process, learning capabilities are employed in the HS to select these parameters based on spontaneous reactions. An extensive numerical investigation is conducted on several well-known test functions, and the results are compared with the HS algorithm and its prominent variants, including the improved harmony search (IHS), global-best harmony search (GHS) and self-adaptive global-best harmony search (SGHS). The numerical results indicate that the LAHS is more efficient in finding optimum solutions and outperforms the existing HS algorithm variants.     

基于局部评价环境的群组评价状态测评研究

群组评价状态测评是提高群组评价方法适用性和有效性的途径之一,以评价参与者为节点,构建具有评价群体之间链接关系的群体网络结构,即评价局部环境,将评价群体网络结构信息与属性信息进行整合构造局部评价环境的群组评价状态测度,实现协商过程有效跟随,实时对评价参与者和群组评价状态进行测评。根据测评结果给出具有评价参与者核心性测度、群体协商充分性和有效性测度的建议,对评价参与者的评价行为进行引导,给出具有导向性的评价信息集结方法建议。给出示例对群组评价状态测评进行示范解释。     

Two improved harmony search algorithms for solving engineering optimization problems

This paper describes two new harmony search (HS) meta-heuristic algorithms for engineering optimization problems with continuous design variables. The key difference between these algorithms and traditional (HS) method is in the way of adjusting bandwidth (bw). bw is very important factor for the high efficiency of the harmony search algorithms and can be potentially useful in adjusting convergence rate of algorithms to optimal solution. First algorithm, proposed harmony search (PHS), introduces a new definition of bandwidth (bw). Second algorithm, improving proposed harmony search (IPHS) employs to enhance accuracy and convergence rate of PHS algorithm. In IPHS, non-uniform mutation operation is introduced which is combination of Yang bandwidth and PHS bandwidth. Various engineering optimization problems, including mathematical function minimization problems and structural engineering optimization problems, are presented to demonstrate the effectiveness and robustness of these algorithms. In all cases, the solutions obtained using IPHS are in agreement or better than those obtained from other methods.     

决策单元的变更对共协调性的影响

本文将对共协调分析的灵敏度问题进行研究,着重探讨决策单元的变更对共协调性的影响。     

Parameter adaptive harmony search algorithm for unimodal and multimodal optimization problems

This paper presents a parameter adaptive harmony search algorithm (PAHS) for solving optimization problems. The two important parameters of harmony search algorithm namely Harmony Memory Consideration Rate (HMCR) and Pitch Adjusting Rate (PAR), which were either kept constant or the PAR value was dynamically changed while still keeping HMCR fixed, as observed from literature, are both being allowed to change dynamically in this proposed PAHS. This change in the parameters has been done to get the global optimal solution. Four different cases of linear and exponential changes have been explored. The change has been allowed during the process of improvization. The proposed algorithm is evaluated on 15 standard benchmark functions of various characteristics. Its performance is investigated and compared with three existing harmony search algorithms. Experimental results reveal that proposed algorithm outperforms the existing approaches when applied to 15 benchmark functions. The effects of scalability, noise, and harmony memory size have also been investigated on four approaches of HS. The proposed algorithm is also employed for data clustering. Five real life datasets selected from UCI machine learning repository are used. The results show that, for data clustering, the proposed algorithm achieved results better than other algorithms.     

A harmony search algorithm for university course timetabling

One of the main challenges for university administration is building a timetable for course sessions. This is not just about building a timetable that works, but building one that is as good as possible. In general, course timetabling is the process of assigning given courses to given rooms and timeslots under specific constraints. Harmony search algorithm is a new metaheuristic population-based algorithm, mimicking the musical improvisation process where a group of musicians play the pitches of their musical instruments together seeking a pleasing harmony. The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. In this paper, a harmony search and a modified harmony search algorithm are applied to university course timetabling against standard benchmarks. The results show that the proposed methods are capable of providing viable solutions in comparison to previous works.     

群体决策的偏好协调性检验

对于一类群体决策问题，本文引进群体的偏好协调性指标，并且给出了偏好协调性指标的统计检验．在此基础上，还提出一个求该类群体决策问题的方法，以及讨论了群体的偏好快调性指标和群体决策结果间的关系．     

Decision-theoretic harmony: A first step

This paper presents a novel harmony generation method based on decision-theoretic planning. We are the first to model music generation using Markov decision processes (MDPs). We give a proof of concept for this approach by using MDP planning to generate four-part harmony, given the melody or soprano line. Our initial results show feasibility, and show the variance possible, depending on the choice of reward functions.