• 제목/요약/키워드: Intelligence-based decision mechanism

검색결과 20건 처리시간 0.026초

An Intelligent Multi-multivariable Dynamic Matrix Control Scheme for a 160 MW Drum-type Boiler-Turbine System

  • Mazinan, A.H.
    • Journal of Electrical Engineering and Technology
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    • 제7권2호
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    • pp.240-245
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    • 2012
  • A 160 MW drum-type boiler-turbine system is developed in the present research through a multi-multivariable dynamic matrix control (DMC) scheme and a multi-multivariable model approach. A novel intelligence-based decision mechanism (IBDM) is realized to support both model approach and control scheme. In such case, the responsibility of the proposed IBDM is to identify the best multivariable model of the system and the corresponding multivariable DMC scheme to cope with the system at each instant of time in an appropriate manner.

Mediating and Moderating Mechanism in the Relationship Between Blue Ocean Leadership Style and Strategic Decision Making: A Case Study in Malaysia

  • WAN HANAFI, Wan Noordiana;DAUD, Salina
    • The Journal of Asian Finance, Economics and Business
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    • 제8권7호
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    • pp.613-623
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    • 2021
  • This study aims to identify the effect of blue ocean leadership style on strategic decision making and it also aims to examine the mediating role of organizational politic and moderating role of emotional intelligence in the Government Link Companies (GLCs) in Malaysia. In order to achieve the objective of the study, a research framework had been developed to establish a relationship among the variables of the study based on resource-based view theory. Questionnaire method was used to collect the data form middle to top level employees in GLCs. All the items in the study's variables were assessed using the 5-point Likert scale. A stratified random sampling technique was used to identify the sample for this study. Data was derived from 135 middle to top level employees, which were involved in decision making process. The data was analyzed using the SPSS and the SmartPLS 3.0 software. This supplemented the theory surrounding blue ocean leadership styles and strategic decision making. The study also identified several avenues for further research by using different research methods and examining the impact of strategic decision making in different contexts.

지능형 사이버공격 대비 상황 탄력적 / 실행 중심의 사이버 대응 메커니즘 (A situation-Flexible and Action-Oriented Cyber Response Mechanism against Intelligent Cyber Attack)

  • 김남욱;엄정호
    • 디지털산업정보학회논문지
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    • 제16권3호
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    • pp.37-47
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    • 2020
  • The In the 4th industrial revolution, cyber space will evolve into hyper-connectivity, super-convergence, and super-intelligence due to the development of advanced information and communication technologies, which will connect the nation's core infrastructure into a single network. As applying the 4th industrial revolution technology to the cyber attack technique, it is evolving in an intelligent and sophisticate method. In order to response intelligent cyber attacks, it is difficult to guarantee self-defense in cyberspace by policy-oriented, preplanned-centric and hierarchical cyber response strategies. Therefore, this research aims to propose a situation-flexible & action-oriented cyber response mechanism that can respond flexibly by selecting the most optimal smart security solution according to changes in the cyber attack steps. The proposed cyber response mechanism operates the smart security solutions according to the action-oriented detailed strategies. In addition, artificial intelligence-based decision-making systems are used to select the smart security technology with the best responsiveness.

퍼지인식도를 이용한 웹기반 조직지식획득에 관한 연구 (Web-Based Organizational Memory Acquisition by Using a Fuzzy Cognitive Map)

  • 이건창
    • 지능정보연구
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    • 제5권2호
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    • pp.79-97
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    • 1999
  • Knowledge management (KM) is emerging as a robust management mechanism with which an organization can remain highly intelligent and competitive in a turbulent market. Organization knowledge is at the heart of KM success. As a vehicle of acquiring organizational knowledge in a distributed decision-making environment, we applied a fuzzy cognitive map (FMM) technique and proved its effectiveness in a distributed knowledge management environment. Our approach was applied to the financial statement analysis problem, yielding a robust result.

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Artificial Intelligence-Based Stepwise Selection of Bearings

  • Seo, Tae-Sul;Soonhung Han
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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    • pp.219-223
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    • 2001
  • Within a mechanical system such as an automotive the number of standard machine parts is increasing, so that the parts selection becomes more important than ever before. Selection of appropriate bearings in the preliminary design phase of a machine is also important. In this paper, three decision-making approaches are compared to find out a model that is appropriate to bearing selection problem. An artificial neural network, which is trained with real design cases, is used to select a bearing mechanism at the first step. Then, the subtype of the bearing is selected by the weighting factor method. Finally, types of peripherals such as lubrication methods are determined by a rule-based expert system.

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ADD-Net: Attention Based 3D Dense Network for Action Recognition

  • Man, Qiaoyue;Cho, Young Im
    • 한국컴퓨터정보학회논문지
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    • 제24권6호
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    • pp.21-28
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    • 2019
  • Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.

환자 IQR 이상치와 상관계수 기반의 머신러닝 모델을 이용한 당뇨병 예측 메커니즘 (Diabetes prediction mechanism using machine learning model based on patient IQR outlier and correlation coefficient)

  • 정주호;이나은;김수민;서가은;오하영
    • 한국정보통신학회논문지
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    • 제25권10호
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    • pp.1296-1301
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    • 2021
  • 최근 전 세계적으로 당뇨병 유발률이 증가함에 따라 다양한 머신러닝과 딥러닝 기술을 통해 당뇨병을 예측하려고 는 연구가 이어지고 있다. 본 연구에서는 독일의 Frankfurt Hospital 데이터로 머신러닝 기법을 활용하여 당뇨병을 예측하는 모델을 제시한다. IQR(Interquartile Range) 기법을 이용한 이상치 처리와 피어슨 상관관계 분석을 적용하고 Decision Tree, Random Forest, Knn, SVM, 앙상블 기법인 XGBoost, Voting, Stacking로 모델별 당뇨병 예측 성능을 비교한다. 연구를 진행한 결과 Stacking ensemble 기법의 정확도가 98.75%로 가장 뛰어난 성능을 보였다. 따라서 해당 모델을 이용하여 현대 사회에 만연한 당뇨병을 정확히 예측하고 예방할 수 있다는 점에서 본 연구는 의의가 있다.

Intelligent Intrusion Detection and Prevention System using Smart Multi-instance Multi-label Learning Protocol for Tactical Mobile Adhoc Networks

  • Roopa, M.;Raja, S. Selvakumar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권6호
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    • pp.2895-2921
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    • 2018
  • Security has become one of the major concerns in mobile adhoc networks (MANETs). Data and voice communication amongst roaming battlefield entities (such as platoon of soldiers, inter-battlefield tanks and military aircrafts) served by MANETs throw several challenges. It requires complex securing strategy to address threats such as unauthorized network access, man in the middle attacks, denial of service etc., to provide highly reliable communication amongst the nodes. Intrusion Detection and Prevention System (IDPS) undoubtedly is a crucial ingredient to address these threats. IDPS in MANET is managed by Command Control Communication and Intelligence (C3I) system. It consists of networked computers in the tactical battle area that facilitates comprehensive situation awareness by the commanders for timely and optimum decision-making. Key issue in such IDPS mechanism is lack of Smart Learning Engine. We propose a novel behavioral based "Smart Multi-Instance Multi-Label Intrusion Detection and Prevention System (MIML-IDPS)" that follows a distributed and centralized architecture to support a Robust C3I System. This protocol is deployed in a virtually clustered non-uniform network topology with dynamic election of several virtual head nodes acting as a client Intrusion Detection agent connected to a centralized server IDPS located at Command and Control Center. Distributed virtual client nodes serve as the intelligent decision processing unit and centralized IDPS server act as a Smart MIML decision making unit. Simulation and experimental analysis shows the proposed protocol exhibits computational intelligence with counter attacks, efficient memory utilization, classification accuracy and decision convergence in securing C3I System in a Tactical Battlefield environment.

경제적부가가치 지식을 채택한 에이전트 기반의 지능형 ERP 개발 (Adopting EVA Knowledge to Agent-Based Intelligent ERP Development)

  • 권오병;정진홍
    • Asia pacific journal of information systems
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    • 제9권4호
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    • pp.41-67
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    • 1999
  • ERP is now one of the prevailing applications for integrated information systems, So far, the conventional ERPs lack how to manage knowledge of making decisions, that is one of the important goal of ERP. This gives a motivation on adding decision support capabilities to the ERPs: active advice for business analysis, evaluation and control. In this paper, we proposed an agent-based intelligent ERP that is operated on the Internet. In special, knowledge of economic value added (EVA) is explicitly acquired as a set of data, models and methodologies, A new knowledge representation format, MIF, is suggested to show the communication mechanism between agents, The agent-based knowledge processing is adopted to deliver intelligence on the Internet.

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Unethical Network Attack Detection and Prevention using Fuzzy based Decision System in Mobile Ad-hoc Networks

  • Thanuja, R.;Umamakeswari, A.
    • Journal of Electrical Engineering and Technology
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    • 제13권5호
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    • pp.2086-2098
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    • 2018
  • Security plays a vital role and is the key challenge in Mobile Ad-hoc Networks (MANET). Infrastructure-less nature of MANET makes it arduous to envisage the genre of topology. Due to its inexhaustible access, information disseminated by roaming nodes to other nodes is susceptible to many hazardous attacks. Intrusion Detection and Prevention System (IDPS) is undoubtedly a defense structure to address threats in MANET. Many IDPS methods have been developed to ascertain the exceptional behavior in these networks. Key issue in such IDPS is lack of fast self-organized learning engine that facilitates comprehensive situation awareness for optimum decision making. Proposed "Intelligent Behavioral Hybridized Intrusion Detection and Prevention System (IBH_IDPS)" is built with computational intelligence to detect complex multistage attacks making the system robust and reliable. The System comprises of an Intelligent Client Agent and a Smart Server empowered with fuzzy inference rule-based service engine to ensure confidentiality and integrity of network. Distributed Intelligent Client Agents incorporated with centralized Smart Server makes it capable of analyzing and categorizing unethical incidents appropriately through unsupervised learning mechanism. Experimental analysis proves the proposed model is highly attack resistant, reliable and secure on devices and shows promising gains with assured delivery ratio, low end-to-end delay compared to existing approach.