• Spatial Information Research
• /
• v.7 no.2
• /
• pp.191-207
• /
• 1999

Data and information necessary for solving the spatial decision making problems are imperfect or inaccurate and most are described by natural language. In order to process these arts of information by the computer, the obscure linguistic value need to be described quantitatively to let and computer understand natural language used by humans. For this , the fuzzy set theory and the fuzzy logic are used representative methodology. So this paper describes the construction of the language model by the natural language that user easily can understand and the logical concepts and construction process for building the fuzzy inference mechanism. It makes possible to solve the space related decision making problems intellectually through structuring and inference used by the computer, in case of the evaluation concern or decision making problems are described inaccurate, based on the inaccurate or indistinct data and information.

• Journal of Korean Institute of Industrial Engineers
• /
• v.23 no.1
• /
• pp.163-175
• /
• 1997

This paper presents the algorithm for finding the compensatory solution for fuzzy multiobjective nonlinear programming problem using $\gamma$-operator. The proposed algorithm can be applied to all cases with multiobjective problems since the interactive process with a decision maker is simple, various uncertainties involved on decision making are eliminated and all the objectives are well balanced. On the basis of proposed algorithm, an illustrative numerical example is presented.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.6
• /
• pp.2925-2948
• /
• 2019

In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.

• Architectural research
• /
• v.12 no.2
• /
• pp.85-92
• /
• 2010

In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

• Journal of Distribution Science
• /
• v.11 no.6
• /
• pp.21-30
• /
• 2013

Purpose - This paper examines product design management, the current design focus of which has shifted to the need to produce innovation applications that can effectively respond to the market's consumption changes in a timely manner. Research design, data, methodology - This study discusses several methodologies that are widely used in experimental processes, such as fuzzy theory, multi-criteria decision-making theory, and managing decision making. The designers will better understand their customers by applying these methodologies. This study examines how the current trend in product innovation design observes customer needs, controls innovation, and stimulates design ability. Results - This paper takes innovative telephone design as an experimental case to investigate how to create a product using market-oriented and customized management concepts and creative design abilities. Conclusions - If accompanied by an innovative product value chain, a product can further the development of enterprise management, now the main element of every developed country's social and economic development.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.1
• /
• pp.7-11
• /
• 2024

In the era of the 4th Industrial Revolution, new technologies such as artificial intelligence, big data, cloud, Internet of Things, and blockchain are being developed and applied to new industries. Blockchain has the characteristics of decentralization, security, and transparency, so it can serve as a core technology for developing new growth industries. Blockchain is provided as BaaS (Blockchain as a Service), but it is not easy for users who are introducing or building blockchain to choose BaaS. In this study, we identify evaluation factors and develop a decision-making model using fuzzy theory and AHP for BaaS selection. Eventually we aim to help companies choose the best BaaS and develop and commercialize blockchain-based services by developing a new decision-making model for BaaS selection.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.227-230
• /
• 1997

In this paper, robot navigation experiments with a new navigation algorithm are carried out in real environments. The authors already proposed a reactive navigation algorithm for mobile robots using optimal via-point selection method. At each sampling time, a number of via-point candidates is constructed with various candidates of heading angles and velocities. The robot detects surrounding obstacles, and the proposed algorithm utilizes fuzzy multi-attribute decision making in selecting the optimal via-point the robot would proceed at next step. Fuzzy decision making allows the robot to choose the most qualified via-point even when the two navigation goals-obstacle avoidance and target point reaching-conflict each other. The experimental result shows the successful navigation can be achieved with the proposed navigation algorithm for real environments.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.19 no.3
• /
• pp.53-62
• /
• 1994

Complex decision-making problems are often characterized by multicriteria phenomena and fuzziness inherent in the structure of information and therefore suitable scientific solution methods. Especially, when similar dependent criteria are introduced, the problems become more complex. This paper presents a fuzzy intersectional dependence relation model for this kind of multicriteria decision-making problems. The model we propose is based on the fuzzy relation from fuzzy systems theory. In ths case of introducing similar dependent criteria, the rank reversal by distortion of weights is hard to occur by our proposed method. A numerical example is presented to illustrate the use of the model.

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.34C no.10
• /
• pp.98-105
• /
• 1997

In this work, we proesent a bidirectional approximate reasoning method and fuzzy inference network for interval valued decision making systems. For this, we propose a new type of similarity measure between two fuzzy vectors based on the Ordered Weighted Averaging (OWA) operator. Since the proposed similarity measure has a structure to give the extreme values by choosing a suitable weighting vector of the OWA operator, it can render an interval valued similarity value. From this property, we derive a bidirectional approximate reasoning method based on the similarity measure and show its fuzzy inference network implementation for the decision making systems requiring the interval valued decisions.

• Journal of Digital Convergence
• /
• v.7 no.4
• /
• pp.169-180
• /
• 2009

IT governance implies a system in which all stakeholders with a given organization, including the board, internal customers, and related areas such as finance provide the necessary input into their decision-making process. However, the concepts of IT governance are broad and ambiguous, so IT governance is eventually needed multi-criteria decision making. This paper presents a hierarchical structure to better understand the relationship between control structure and the complexity of collective behavior with respect to IT governance and proposes a corresponding fuzzy model for analyzing IT governance complexity based on an extensive literature review. The results of this study are expected to provide a clearer understanding of how the concerns of IT governance behave and how they interact and form the collective behavior of the entire system.