• Title/Summary/Keyword: Control decision

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Decision of Optimum Cycle of Traffic Junction Vehicle Signal Control using Fuzzy Identification Algorithm (퍼지 동정 알고리즘을 이용한 교차로 교통 신호등 제어의 최적 주기 결정)

  • 진현수;김재필;김종원;홍완혜;김성환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.6
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    • pp.100-108
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    • 1993
  • In this paper, noticing the point of human's ability which appropriately cope with vague conditions, we design fuzzy traffic signal light controller similar to human's distinction ability and decide the optimum cycle most suited to any traffic junction using fuzzy identification algorithm. In this study, for the control output decision process we design fuzzy controller better than electronic vehicle actuated controller in performance. We propose the cycle decision method which is not limited by the variance of traffic junction vehicle number through overcoming the limit of Webster's method which is adopted by the fixed cycle controller. Simulated experimental results show that fuzzy controller and fuzzy identification algorithm are better than the existing electronic vehicle actuated controller and fixed cycle controller in delay time per vehicle.

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A Fuzzy Model for Assessing IT Governance Complexity (IT 거버넌스 복잡성 평가를 위한 퍼지 모델)

  • Lee, Sang-Hyun;Lee, Sang-Joon;Moon, Kyung-Il;Cho, Sung-Eui
    • Journal of Digital Convergence
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    • v.7 no.4
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    • pp.169-180
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    • 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.

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Auto-switching Equalization Algorithm for 8-VSB HDTV Receiver (8-VSB HDTV 수신기용 자동 변환 채널등화 알고리즘)

  • Park, Kyung-Do;Hwang, Yu-Mor
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.624-626
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    • 1998
  • Adaptive channel equalization accomplished without resorting to a training sequence is known as blind equalization. In this paper, we present a auto-switching blind, equalization for 8-VSB HDTV receiver. The scheme operate in two mode : blind equalization mode and decision-directed equalization mode. This proposed scheme changes from the blind equalization mode at high error levels to the decision-directed equalization mode at lower error levels smoothly and automatically. Manual switch from the blind equalization mode to the decision-directed mode is not necessary.

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Control Packet Transmission Decision Method for Wearable Sensor Systems (웨어러블 센서 시스템에서의 제어 패킷 전송 결정 기법)

  • Yu, Daeun;Kim, Namgi
    • Journal of Internet Computing and Services
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    • v.16 no.5
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    • pp.11-17
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    • 2015
  • In the general transmission power control model that is used for wearable sensor systems, if RSSI value gets out of the Target RSSI Margin, then the sink node finds new transmission power by using TPC(Transmission Power Control) Algorithm. At this time, the sink node sends the control packet to the sensor node for delivering the newly calculated transmission power. However, when the wireless network channel condition is poor, even it is consuming a lot of control packets, the sink node could not find an appropriate transmission power so it only waste of energy. Therefore, we proposed a new control packet transmission decision method that the sink node changes the transmission power when the wireless network channel condition is stabilized. It makes waste of energy decline. In this paper, we apply control packet transmission decision method to Binary TPC algorithms and analyze the results to evaluate the proposed method. We propose three methods that judge the state of wireless network channel. We experiment that methods and analysis the results.

Identification of Subgroups with Poor Glycemic Control among Patients with Type 2 Diabetes Mellitus: Based on the Korean National Health and Nutrition Examination Survey from KNHANES VII (2016 to 2018) (제 2형 성인 당뇨병 유병자의 혈당조절 취약군 예측: 제7기(2016-2018년도) 국민건강영양조사 자료 활용)

  • Kim, Hee Sun;Jeong, Seok Hee
    • Journal of Korean Biological Nursing Science
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    • v.23 no.1
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    • pp.31-42
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    • 2021
  • Purpose: This study was performed to assess the level of blood glucose and to identify poor glycemic control groups among patients with type 2 diabetes mellitus (DM). Methods: Data of 1,022 Korean type 2 DM patients aged 30-64 years were extracted from the Korea National Health and Nutrition Examination Survey VII. Complex samples analysis and a decision-tree analysis were performed using the SPSS WIN 26.0 program. Results: The mean level of hemoglobin A1c (HbA1c) was 7.22±0.25%, and 69.0% of the participants showed abnormal glycemic control (HbA1c≥6.5%). The characteristics of participants associated with poor glycemic control groups were presented with six different pathways by the decision-tree analysis. Poor glycemic control groups were classified according to the patients' characteristics such as period after DM diagnosis, awareness of DM, sleep duration, gender, alcohol drinking, occupation, income status, low density lipoprotein-cholesterol, abdominal obesity, and number of walking days per week. Period of DM diagnosis with a cut-off point of 6 years was the most significant predictor of the poor glycemic control group. Conclusion: The findings showed the predictable characteristics of the poor glycemic control groups, and they can be used to screen the poor glycemic control groups among adults with type 2 DM.

A Study of Effective Team Decision Making Using A Distributed AI Model (분산인공지능 모델을 이용한 효과적인 팀 의사결정에 관한 연구)

  • Kang, Min-Cheol
    • Asia pacific journal of information systems
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    • v.10 no.3
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    • pp.105-120
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    • 2000
  • The objective of this paper is to show how team study can be advanced with the aid of a current computer technology, that is distributed Artificial Intelligence(DAI). Studying distributed problem solving by using groups of artificial agents, DAI can provide important ideas and techniques for the study of team behaviors like team decision making. To demonstrate the usefulness of DAI models as team research tools, a DAI model called 'Team-Soar' was built and a simulation experiment done with the model was introduced, Here, Team-Soar models a naval command and control team consisting of four members whose mission was to identify the threat level of aircraft. The simulation experiment was performed to examine the relationships of team decision scheme and member incompetence with team performance. Generally, the results of the Team-Soar simulation met expectations and confirmed previous findings in the literature. For example, the results support the existence of main and interaction effects of team decision scheme and member competence on team performance. Certain results of the Team-Soar simulation provide new insights about team decision making, which can be tested against human subjects or empirical data.

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Improved Decision Tree Algorithms by Considering Variables Interaction (교호효과를 고려한 향상된 의사결정나무 알고리듬에 관한 연구)

  • Kwon, Keunseob;Choi, Gyunghyun
    • Journal of Korean Institute of Industrial Engineers
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    • v.30 no.4
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    • pp.267-276
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    • 2004
  • Much of previous attention on researches of the decision tree focuses on the splitting criteria and optimization of tree size. Nowadays the quantity of the data increase and relation of variables becomes very complex. And hence, this comes to have plenty number of unnecessary node and leaf. Consequently the confidence of the explanation and forecasting of the decision tree falls off. In this research report, we propose some decision tree algorithms considering the interaction of predictor variables. A generic algorithm, the k-1 Algorithm, dealing with the interaction with a combination of all predictor variable is presented. And then, the extended version k-k Algorithm which considers with the interaction every k-depth with a combination of some predictor variables. Also, we present an improved algorithm by introducing control parameter to the algorithms. The algorithms are tested by real field credit card data, census data, bank data, etc.

The Impact of Croup Member Characteristics on the Use of GDSS (집단요인이 GDSS활용의 효과에 미치는 영향에 관한 연구)

  • Park, Moo-Jin
    • Journal of the Korean Operations Research and Management Science Society
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    • v.23 no.4
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    • pp.171-186
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    • 1998
  • While one main stream of research in GDSS (Group Decision Support System) is to investigate how GDSS affects decision-making performances of groups according to task types, support features, meeting facilitation modes and meeting environments. little study h3s been done about how group characteristics affect group decision processes and outcomes depending upon GDSS is provided or not. So far, most GDSS research has considered group characteristics (e.g. personality homogeneity) as given and did not include it as control variables in experiments. Therefore, the objective of this study is to investigate how members of two different groups perceive the use of GDSS in group meetings through lab experiments. The two groups are homogeneous and heterogeneous groups in terms of members' personality mix. This research found that the effect of GDSS is a function of groups' personality homogeneity in regards of the satisfaction on decision process and the communication thoroughness. The support of GDSS and the group homogeneity are proved to influence participant's perception about some dependent variables such as satisfaction on decision process.

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Development of a Nitrogen Application System for Nitrogen Deficiency in Corn

  • Noh, Hyun Kwon
    • Journal of Biosystems Engineering
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    • v.42 no.2
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    • pp.98-103
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    • 2017
  • Purpose: Precision agriculture includes determining the right amount of nitrogen for a specific location in the field. This work focused on developing and validating a model using variable rate nitrogen application based on the estimated SPAD value from the ground-based image sensor. Methods: A variable rate N application based on the decision making system was performed using a sensor-based variable rate nitrogen application system. To validate the nitrogen application decision making system based on the SPAD values, the developed N recommendation was compared with another conventional N recommendation. Results: Sensor-based variable rate nitrogen application was performed. The nitrogen deficiency level was measured using the image sensor system. Then, a variable rate application was run using the decision model and real-ti me control. Conclusions: These results would be useful for nitrogen management of corn in the field. The developed nitrogen application decision making system worked well, when considering the SPAD value estimation.

Agent-Based Decision Support System for Intelligent Machine Tools (공작기계지능화를 위한 에이전트 기반 의사결정지원시스템)

  • Lee, Seung-Woo;Song, Jun-Yeob;Lee, Hwa-Ki;Kim, Sun-Ho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.29 no.1
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    • pp.87-93
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    • 2006
  • In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.