Fuzzy regression model of R&D project evaluation

Engineering and technology play an important role in strengthening the competitive power of a company and in surviving a severe competition in the world. About 70% of the total R&D investment in Japan comes from the private sector. It is the most important to decide which research projects have to be adopted for a future research out of proposals from divisions and sections in a company. The objective of this paper is to analyze the results of experts’ evaluation in selecting submitted proposals for R&D and to model the experts’ evaluation. This paper analyzes a research and development of a certain manufacturing company in a heavy metallurgy industry.We employed a principal component model, dual scaling, AHP and fuzzy regression analysis to analyze the results that experts evaluated proposed research projects for single or plural of fiscal years. The experts’ evaluation was pursued on the basis of (1) the objective of a research project, (2) its background, (3) its research contents, (4) the expected effect, (5) the possibility of obtaining patents, (6) project schedule, (7) developing cost, etc. The obtained model results in the same selection of projects as the experts did.     

An intelligent speech interface for personal assistants in R&D projects

Groupware and collaborative tools have been proposed to support cooperative work. However, they suffer from some rather severe limitations. Alternatively, multi-agent systems can be proposed to improve the situation. In the latter case, the user normally interacts with the system through a special agent called a personal assistant. In this paper, we describe the design of an ontology-based speech interface for personal assistants applied in the context of cooperative projects. We believe that this type of interface will improve the quality of assistance and increase collaboration between project members. We present the interface and its insertion into a multi-agent system designed for research and development projects. We describe the design of the interface, highlighting the role of ontologies for semantic interpretation. As a result of this conversational speech interface, we expect an increase in the quality of assistance and a reduction in the time needed to answer user’s requests.     

An intelligent adaptive system for the optimal variable selections of R&D and quality supply chains

The cost of research & development (R&D) and quality management are always regarded as two major parts of total cost. The variable performance of R&D and quality design is an important index that will reflect the effectiveness of the cost reduction. This research has attempted to simultaneously vary all of the variables to achieve the global optimum for the optimal variable selections of R&D and quality design. Genetic algorithm (GA) can treat all of the variables for the global search. In this study, fuzzy refinement with orthogonal arrays was effective in improving the performance of the GA, and also showed the benefits of a good chromosome structure on the behavior of GA. It is also proposed the postponement design with temporal concept, to select the effective variables for the cost reduction of R&D and quality management design. The experimental results showed that tempo-postponement design will increase the flexibility and quick response for supply chain management. Hence, this approach can act as a useful guideline for researchers working on the optimization of the key variable selections for R&D and quality model design.     

On a novel uncertain soft set model: Z-soft fuzzy rough set model and corresponding decision making methods

In this paper, a kind of novel soft set model called a Z-soft fuzzy rough set is presented by means of three uncertain models: soft sets, rough sets and fuzzy sets, which is an important generalization of Z-soft rough fuzzy sets. As a novel Z-soft fuzzy rough set, its applications in the corresponding decision making problems are established. It is noteworthy that the underlying concepts keep the features of classical Pawlak rough sets. Moreover, this novel approach will involve fewer calculations when one applies this theory to algebraic structures. In particular, an approach for the method of decision making problem with respect to Z-soft fuzzy rough sets is proposed and the validity of the decision making methods is testified by a given example. At the same time, an overview of techniques based on some types of soft set models is investigated. Finally, the numerical experimentation algorithm is developed, in which the comparisons among three types of hybrid soft set models are analyzed.     

基于犹豫模糊集的软件质量评价模型

提出一种基于犹豫模糊集的软件质量评价模型。首先,根据专家打分,将犹豫模糊集与直觉模糊集相结合,得出软件质量特性的综合犹豫模糊评价矩阵;然后,通过计算犹豫模糊广义比较表,得出软件各质量属性得分;最后根据得分情况给出软件的质量排序。该模型较好地解决了专家对软件质量指标进行评价时的犹豫性问题。具体的案例分析表明,所提出的软件质量评价模型是可行、有效的。     

基于直觉模糊粗糙集的属性约简

针对Jensen下近似定义的局限性,提出一种新的等价类形式的近似算子表示,并将其推广到直觉模糊环境.在此基础上,将相对正域、相对约简、相对核等粗糙集的知识约简概念推广到直觉模糊环境,提出一种直觉模糊信息系统的启发式属性约筒算法.实例计算表明.该方法比Jensen的属性约简方法更为合理有效.     

Web-based multi-attribute analysis model for engineering project evaluation

This paper is concerned with development of web-based multi-attribute evaluation model for engineering project. Major technologies used for this study are; analytic hierarchy process (AHP), multi-attribute utility with multi-echelon structure and integrating the prioritized set of evaluated results. In this study, we developed a 3-step approach, three sub-modules are: (1) web-based brainstorming module for idea and alternative generation, (2) web-based AHP and Fuzzy AHP module for evaluation of alternatives, and (3) priority integration module to aggregate the multiple rank-ordered sets based on fuzzy set priority. Finally, we have developed a systematic and practical computer program and it has been found that the proposed model is potentially efficient and useful in evaluating engineering project through examples. However, the proposed model can provide engineering decision makers to get the best alternative.     

Intuitionistic fuzzy rough set model based on conflict distance and applications

Due to the complexity and uncertainty of the objective world, as well as the limitation of human ability to understand, it is difficult for one to employ only a single type of uncertainty method to deal with the real-life problem of decision-making, especially problems involving conflicts. On the other hand, by incorporating the advantages of various theories of uncertainty, one is expected to develop a more powerful hybrid method for soft decision making and to solve such problems more effectively. In view of this, in this paper the thought and method of intuitionistic fuzzy set and rough set are used to construct a novel intuitionistic fuzzy rough set model. Corresponding to the fact that the decision-making information system of rough sets is of intuitionistic fuzzy information system, our method defines the conflict distance by using the idea of measuring intuitionistic fuzzy similarity so that it is introduced into the models of rough sets, leading to the development of our intuitionistic fuzzy rough set model. After that, we investigate the properties of the model, introduce a novel tool for conflict analysis based on our hybrid model, and employ this new tool to describe and resolve a real-life conflict problem.     

Performance of multiclass BCMP model for computer system based on fuzzy set theory

The purpose of this paper is to combine the ability of fuzzy set to represent more realistic situations with the well-established traditional queueing system model problem. We are forced to employ subjective probabilities when there is no information about a model or some parameters of a model are vague. The information and data are very fuzzy, because they are frequently very little, 'and may be sometimes obtained from experts subjectively. We apply fuzzy set theory to the closed multiclass model with the fuzzy queues. thus, we represent the characteristic and performance of the closed multiclass model based on the proposed fuzzy set theory.     

基于模糊粗糙集的TOPSIS供应商评估方法

由于供应商选择是一个多目标评价问题, 不确定的因素很多, 如果仅靠经验判断则无法避免结果的主观性, 针对这一问题采用了定性和定量相结合的方法, 利用模糊粗糙集求得指标的客观权重, 利用专家评分法来定义指标的主观权重, 再综合主客观权重, 最后将综合权重用于TOPSIS进行评估, 并用实例证明了这种方法的有效性和可行性。     

RASP—A language with operations on fuzzy set

At the Center for Multidisciplinary Studies, University of Belgrade, Yugoslavia, a high level language for easily manipulating fuzzy set operations was developed. In this paper, after a brief introduction to the theory of fuzzy sets, some features and possibilities are described from the user point of view, and an application in picture enhancement is shown. The language presented was written in BASIC, thus any microcomputer, for personal/home use, should be able to execute RASP.     

基于模糊粗糙集的因素权重分配方法

基于模糊集与粗糙集的融合,提出一种对多因素分配权重的简单方法．该方法与传统的权重分配方法有明显的区别．首先利用模糊聚类分析对数据进行聚类,并提取最佳聚类;然后应用粗糙集中属性的重要程度对各个特征因素进行客观地分配权重．实例分析验证了所提出方法的有效性．     

模糊集FScom在台风灾害等级评判中的应用

模糊集FScom在传统模糊集的基础上提出了三种否定关系：矛盾否定关系、对立否定关系以及中介否定关系,对处理模糊知识信息更具有实用性。以模糊集FScom及其[λ]-中介否定集为理论基础,给出了一种基于FScom模糊综合评判方法的灾害等级评判体系,将此体系应用到台风灾害等级评判中。     

基于模糊集合的完整性信任度评估模型

完整性度量是可信计算得以实现的一项重要技术。根据影响操作系统完整性的内核模块、二进制可执行文件等因素,通过定义直接信任度、间接信任度和综合信任度等计算公式构建了一个操作系统的完整性信任度评估模型,该模型利用模糊集合理论将完整性度量化为[0,1]之间的具体数值,并根据隶属函数将操作系统的信任度划分为四个信任等级。该模型改变了原有完整性度量中一致执行、不一致停止的二值状态,为远程验证者提供较为精确的操作系统完整性度量值,提高了系统的可用性。仿真实验结果表明该模型较客观地提供了操作系统的完整性信息。     

An improved fuzzy neural network based on T–S model

An improved fuzzy neural network based on Takagi–Sugeno (T–S) model is proposed in this paper. According to characteristics of samples spatial distribution the number of linguistic values of every input and the means and deviations of corresponding membership functions are determined. So the reasonable fuzzy space partition is got. Further a subtractive clustering algorithm is used to derive cluster centers from samples. With the parameters of linguistic values the cluster centers are fuzzified to get a more concise rule set with importance for every rule. Thus redundant rules in the fuzzy space are deleted. Then antecedent parts of all rules determine how a fuzzification layer and an inference layer connect. Next, weights of the defuzzification layer are initialized by a least square algorithm. After the network is built, a hybrid method combining a gradient descent algorithm and a least square algorithm is applied to tune the parameters in it. Simultaneous, an adaptive learning rate which is identified from input-state stability theory is adopted to insure stability of the network. The improved T–S fuzzy neural network (ITSFNN) has a compact structure, high training speed, good simulation precision, and generalization ability. To evaluate the performance of the ITSFNN, we experiment with two nonlinear examples. A comparative analysis reveals the proposed T–S fuzzy neural network exhibits a higher accuracy and better generalization ability than ordinary T–S fuzzy neural network. Finally, it is applied to predict markup percent of the construction bidding system and has a better prediction capability in comparison to some previous models.     

投资项目模糊多属性经济评价研究

传统项目经济评价方法在模糊信息的处理过程中,往往倾向于模糊信息清晰化、实数定量化处理,从而使信息失真甚至丢失。为此,研究将模糊数理论引入投资项目经济评价。建立反映项目经济、社会、生态综合效益的多属性经济评价指标体系,利用区间模糊数理论,将定性指标模糊化处理,将定量指标标准化处理,接着通过应用可能度分析方法,研究了基于模糊多属性决策理论的投资项目经济评价方法与步骤,并通过一个实例说明对传统经济评价方法的探索和改进。     

基于模糊理论的无线网络切换评估模型

异构无线网络环境下,智能切换关键要素是提供有保障质量和连接性的服务。针对传统基于接收信号强度的切换判决,在减少不必要切换、呼叫掉线、呼叫阻塞和切换阻碍等方面存在的缺陷,提出切换评估模型。切换判决前,在终端收集网络、用户信息;基于四种通信类型的通信需求,确定网络QoS参数权重值;使用模糊分析方法进行参数量化,将数值并行输入到模糊逻辑器,得到切换评估值,从而得到切换与否的判决。仿真结果显示提出的模型在减少不必要切换、呼叫掉线有较好的表现,能更好地保证连接性和服务质量,从而达到更高的用户满意水平。     

Investment project evaluation by a decision making methodology based on type-2 fuzzy sets

Although investment projects supported by the state are extremely important in terms of national policy the projects to be transferred from the common public funds brings with it many problems. Highly transparent and comprehensive evaluation model are required to transfer the public resources to the right investment projects. It is necessary to consider many criteria for the evaluation of an investment project. These criteria are generally subjective and extremely difficult to express in numbers. However, using the fuzzy sets provide huge facilities to decision makers in project evaluation process with linguistic variables and measurement challenges. In this study, a new evaluation model for investment projects have been proposed for development agencies operating in Turkey. To address ambiguities and relativities in real world scenarios more conveniently, type-2 fuzzy sets and crisp sets have been simultaneously used. The proposed model for the investment project evaluation problem composed of type-2 fuzzy AHP and type-2 fuzzy TOPSIS methods. The proposed fuzzy MCDM method consists of three phases: (1) identify the criteria to be used in the model, (2) type-2 fuzzy AHP computations, (3) evaluation of investment projects with type-2 fuzzy TOPSIS and determination of the final rank. To perceive proposed model better, an application with real case data have been performed in Middle Black Sea Development Agency in Turkey. As a consequence of this application, it has been observed that the proposed model have proved effective in evaluation of alternatives in multi-criteria group decision making problems in a broader perspective and flexible fashion.