• Membrane and Water Treatment
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• v.14 no.2
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• pp.65-76
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• 2023

Given the limited water resources and the presence of multiple decision makers with different and usually conflicting objectives in the exploitation of water resources systems, especially dam's reservoirs; therefore, the decision to determine the optimal allocation of reservoir water among decision-makers and stakeholders is a difficult task. In this study, by combining a fuzzy VIKOR technique or fuzzy multi-criteria decision making (FMCDM) and the Young's bilateral bargaining model, a new method was developed to determine the optimal quantitative and qualitative water allocation of dam's reservoir water with the aim of increasing the utility of decision makers and stakeholders and reducing the conflicts among them. In this study, by identifying the stakeholders involved in the exploitation of the dam reservoir and determining their utility, the optimal points on trade-off curve with quantitative and qualitative objectives presented by Mojarabi et al. (2019) were ranked based on the quantitative and qualitative criteria, and economic, social and environmental factors using the fuzzy VIKOR technique. In the proposed method, the weights of the criteria were determined by each decision maker using the entropy method. The results of a fuzzy decision-making method demonstrated that the Young's bilateral bargaining model was developed to determine the point agreed between the decisions makers on the trade-off curve. In the proposed method, (a) the opinions of decision makers and stakeholders were considered according to different criteria in the exploitation of the dam reservoir, (b) because the decision makers considered the different factors in addition to quantitative and qualitative criteria, they were willing to participate in bargaining and reconsider their ideals, (c) due to the use of a fuzzy-logic based decision-making approach and considering different criteria, the utility of all decision makers was close to each other and the scope of bargaining became smaller, leading to an increase in the possibility of reaching an agreement in a shorter time period using game theory and (d) all qualitative judgments without considering explicitness of the decision makers were applied to the model using the fuzzy logic. The results of using the proposed method for the optimal exploitation of Iran's 15-Khordad dam reservoir over a 30-year period (1968-1997) showed the possibility of the agreement on the water allocation of the monthly total dissolved solids (TDS)=1,490 mg/L considering the different factors based on the opinions of decision makers and reducing conflicts among them.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.121-129
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• 2007

Recently a multi-attribute structure analysis method is one of the evident areas of important points in the decision support system analysis. This research developed an internet/intranet-based solution builder for a three-step decision support system using fuzzy-AHP in the view of 1) brainstorming far the idea generation, 2) fuzzy-AHP (fuzzy analytic hierarchy process) as a multi-attribute structured analysis method and 3) aggregation logic model to integrate the results of individual analysis. We applied this decision support system to the make-or-buy decision problem for school foodservice system considering the multi-attributes in the decision making. A computer program is developed and demonstrated it internet/intranet-based decision problem. It was known that this solution builder provides decision makers a good tool for mate-of-buy group decision making.

• ETRI Journal
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• v.29 no.4
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• pp.527-529
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• 2007

In this paper, a decision-tree-based Markov model for phrase break prediction is proposed. The model takes advantage of the non-homogeneous-features-based classification ability of decision tree and temporal break sequence modeling based on the Markov process. For this experiment, a text corpus tagged with parts-of-speech and three break strength levels is prepared and evaluated. The complex feature set, textual conditions, and prior knowledge are utilized; and chunking rules are applied to the search results. The proposed model shows an error reduction rate of about 11.6% compared to the conventional classification model.

• Journal of Korea Technology Innovation Society
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• v.6 no.2
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• pp.159-174
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• 2003

This study reviews the emerging new model of science and technology decision making process. It examines the open source software development model and community-based innovation model in technological innovation and the active participation model of Consensus Conference and Citizen's Jury in science and technology policy decision making. It argues that the role and influence of users in innovation and policy making is becoming important in these emerging models and the existing supplier-led, bureaucratic model of science and technology decision making model is changing.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.215-223
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• 2016

Design of personnel teams has been studied from diverse perspectives; the most common are the people and systems requirements perspectives. All these point of view are linked, which is the reason why it is necessary to study them simultaneously. Considering this gap, a decision making model is developed based on factors, models, and requirements mentioned in the literature. The model is applied to a real case. The findings indicate that the Personnel Behavior Based Lean model (PBBL) can be converted into a decision making model for the selection of team members. The study is focused not only on the individual candidates' knowledge, skills, and aptitudes, but also on how the model considers the company requirements, conflicts, and the importance of each person to the project.

• Journal of Technology Innovation
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• v.7 no.2
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• pp.21-36
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• 1999

This paper presents a R&D investment model for Information and telecommunications (I&T) technology, which can be used by group decision makers, using multiple objective linear programming (MOLP). The MOLP model involves the simultaneous maximization of three linear objective functions associated with three criteria, which are social, technological, and economic criterion. This model is different from the traditional one which only involves the maximization of economic criterion. The presented problem in this model can be formulated as a problem of optimizing a linear function over an efficient set of MOLP. Its application to the National R&D Project in I&T Industry is also presented. In this application, the Analytic Hierarchy Process (AHP) is proposed to estimate the weights, which are used as the coefficients in each objective function of the MOLP model and in a linear decision function. By solving this problem, it yields a suitable R&D investment ratio to each technology field. It is showed that the MOLP model can be useful decision aid in formulating R&D investment plan in I&T industry which needs to be decided by group decision makers, not by an individual. It is expected that the MOLP model works as the basis for planning R&D investment strategy in I&T industry.

• Journal of the Society of Disaster Information
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• v.5 no.2
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• pp.76-85
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• 2009

SWE(Sensor Web Enablement) is the standard platform of OGC for the sensor data service. SWE is only focusing in the data transmission protocols, but supporting the semantic decision. Sensor data service is the decision service of the status whether is on normal or not. In this study, we study the semantic decision model of the sensor data. It can support the context-aware service based on the decision information.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5593-5596
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• 2014

Background: The objective of this study was to determine a diagnostic classification scheme using a decision tree based model. Materials and Methods: The study was conducted as a retrospective case-control study in Imam Khomeini hospital in Tehran during 2001 to 2009. Data, including demographic and clinical-pathological characteristics, were uniformly collected from 624 females, 312 of them were referred with positive diagnosis of breast cancer (cases) and 312 healthy women (controls). The decision tree was implemented to develop a diagnostic classification scheme using CART 6.0 Software. The AUC (area under curve), was measured as the overall performance of diagnostic classification of the decision tree. Results: Five variables as main risk factors of breast cancer and six subgroups as high risk were identified. The results indicated that increasing age, low age at menarche, single and divorced statues, irregular menarche pattern and family history of breast cancer are the important diagnostic factors in Iranian breast cancer patients. The sensitivity and specificity of the analysis were 66% and 86.9% respectively. The high AUC (0.82) also showed an excellent classification and diagnostic performance of the model. Conclusions: Decision tree based model appears to be suitable for identifying risk factors and high or low risk subgroups. It can also assists clinicians in making a decision, since it can identify underlying prognostic relationships and understanding the model is very explicit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.89-98
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• 2007

In this paper the economic value of weather forecasts is valuated for profit-oriented enterprise decision-making situations. Value is estimated in terms of monetary profits (or benefits) resulted from the forecast user's decision under the specific payoff structure, which is represented by a profit/loss ratio model combined with a decision function and a value score (VS). The forecast user determines a business-related decision based on the probabilistic forecast, the user's subjective reliability of the forecasts, and the payoff structure specific to the user's business environment. The VS curve for a meteorological forecast is specified by a function of the various profit/loss ratios, providing the scaled economic value relative to the value of a perfect forecast. The proposed valuation method based on the profit/loss ratio model and the VS is adapted for hypothetical sets of forecasts and verified for site-specific probability of precipitation forecast of 12 hour and 24 hour-lead time, which is generated from Korea meteorological administration (KMA). The application results show that forecast information with shorter lead time can provide the decision-makers with great benefits and there are ranges of profit/loss ratios in which high subjective reliability of the given forecast is preferred.

• Journal of Korean Academy of Nursing
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• v.49 no.5
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• pp.601-612
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• 2019

Purpose: The purpose of this study was to construct and test a hypothetical model of clinical decision-making ability of nurses based on the Decision Making Process model and the Cognitive Continuum theory. Methods: The data were collected from nurses working at 11 hospitals in Busan, Daejeon, and South Gyeongsang Province from June 30 to August 1, 2017. Finally, the data from 323 nurses were analyzed. Results: The goodness-of-fit of the final model was at a good level ($x^2/df=2.46$, GFI=.87, AGFI=.84, IFI=.90, CFI=.90, SRMR=.07, RMSEA=.07) and 6 out of 10 paths of the model were supported. The clinical decision-making ability was both directly and indirectly affected by task complexity and indirectly affected by experiences, autonomy, and work environment. Specifically, it was strongly directly affected by analytical competency but was insignificantly affected by intuitive competency. These variables accounted for 66.0% of clinical decision-making ability. Conclusion: The nurses' clinical decision-making ability can be improved by improving their analytical competency. Therefore, it is necessary to organize nursing work, create a supportive work environment, and develop and implement various education programs.