• Title/Summary/Keyword: Intelligent Framework

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An Intelligent Decision Support System for Strategic Planning Processes

  • Kwon, Yeong Sik
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.11 no.18
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    • pp.17-26
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    • 1988
  • 본 논문은 전략적 계획과정에 대한 지능적인 의사결정 지원 시스템의 틀(framework)을 개발하는 것을 목적으로 한다. 전문가 시스템의 능력을 의사결정 지원 시스템에 통합한 지능적인 의사결정 지원 시스템은 사업가나 의사결정자가 전략계획을 효율적이고 효과적으로 분석ㆍ평가ㆍ통제할 수 있도록 한다.

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Human Hierarchical Behavior Based Mobile Agent Control in Intelligent Space with Distributed Sensors (분산형 센서로 구현된 지능화 공간을 위한 계층적 행위기반의 이동에이젼트 제어)

  • Jin Tae-Seok;Hashimoto Hideki
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.12
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    • pp.984-990
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    • 2005
  • The aim of this paper is to investigate a control framework for mobile robots, operating in shared environment with humans. The Intelligent Space (iSpace) can sense the whole space and evaluate the situations in the space by distributing sensors. The mobile agents serve the inhabitants in the space utilizes the evaluated information by iSpace. The iSpace evaluates the situations in the space and learns the walking behavior of the inhabitants. The human intelligence manifests in the space as a behavior, as a response to the situation in the space. The iSpace learns the behavior and applies to mobile agent motion planning and control. This paper introduces the application of fuzzy-neural network to describe the obstacle avoidance behavior teamed from humans. Simulation results are introduced to demonstrate the efficiency of this method.

The Hybrid Knowledge Integration Using the Fuzzy Genetic Algorithm

  • Kim, Myoung-Jong;Ingoo Han;Lee, Kun-Chang
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 1999.03a
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    • pp.145-154
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    • 1999
  • An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes th hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

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Intelligent Digital Redesign for Helicopter System (헬리콥터 시스템의 지능형 디지털 재설계)

  • Sung, Hwa-Chang;Park, Jin-Bae;Joo, Young-Hoon
    • Proceedings of the KIEE Conference
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    • 2005.07a
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    • pp.893-895
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    • 2005
  • We represent an efficient intelligent digital redesign method for a Takagi-Sugeno (T-S) fuzzy system. intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows to matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality (LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

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Intelligent Digital Redesign for Helicopter System (헬리콥터 시스템의 지능형 디지털 재설계)

  • Sung, Hwa-Chang;Park, Jin-Bae;Joo, Young-Hoon
    • Proceedings of the KIEE Conference
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    • 2005.07d
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    • pp.3105-3107
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    • 2005
  • We represent an efficient intelligent digital redesign method for a Takagi-Sugeno (T-S) fuzzy system. Intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows to matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality (LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

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An intelligent approach for managing suppliers in SCM using neural networks (SCM에서의 공급자 관리를 위한 신경망을 이용한 지능적 방법)

  • Han Hyeon Su;Lee Yeong Hae;Jo Min Gwan
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.05a
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    • pp.258-261
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    • 2003
  • The purpose of this study is designing intelligent supplier management system with selected criteria for monitoring and evaluating suppliers by the information As suppliers keep changing their performance continuously according to the environment and with the passage or time. Companies need to monitor suppliers' condition continuously and choose the suitable action. This study considers a framework or supply chain management system usuig neural networks for ongoing partnership with criteria of supplier performance. The intelligent supplier management system that this study suggests ran offer the supplier evaluation criteria for monitoring and more efficient supply chain management ran be expected for cost reduction or supply chain management with this system.

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A Development of Intelligent Context-Awareness Middleware (지능적 상황인지 미들웨어의 개발)

  • Suh, Joohee;Woo, Chong-Woo
    • Journal of Information Technology Services
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    • v.11 no.sup
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    • pp.165-176
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    • 2012
  • Context-Awareness system provides an appropriate service to user by recognizing situation from surrounding environment. There are many successful studies on this framework, but still has some limitations. In this paper, we are describing a context-awareness middleware that can enhance the limitation of the previous approaches. We first defined a new concept of context-awareness environment as a social intelligence. This concept implies that intelligent objects can make relationships, can aware of situation from surrounding environment, and can collaborate to accomplish a given task. The significance of the study is as follows. First, the system is capable of multi context-awareness since it is designed with a structure that supports multiple lines of reasoning. Second, the system is capable of context planning by adapting AI planning mechanism. Third, the system is capable of making the intelligent objects as a group for collaboration, and provides adaptive service to user. We have developed a prototype of the system and tested with a virtual scenario.

Towards a Ubiquitous Robotic Companion: Design and Implementation of Ubiquitous Robotic Service Framework

  • Ha, Young-Guk;Sohn, Joo-Chan;Cho, Young-Jo;Yoon, Hyun-Soo
    • ETRI Journal
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    • v.27 no.6
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    • pp.666-676
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    • 2005
  • In recent years, motivated by the emergence of ubiquitous computing technologies, a new class of networked robots, ubiquitous robots, has been introduced. The Ubiquitous Robotic Companion (URC) is our conceptual vision of ubiquitous service robots that provide users with the services they need, anytime and anywhere in ubiquitous computing environments. To realize the vision of URC, one of the essential requirements for robotic systems is to support ubiquity of services: that is, a robot service must be always available even though there are changes in the service environments. Specifically robotic systems need to be automatically interoperable with sensors and devices in current service environments, rather than statically preprogrammed for them. In this paper, the design and implementation of a semantic-based ubiquitous robotic space (SemanticURS) is presented. SemanticURS enables automated integration of networked robots into ubiquitous computing environments exploiting Semantic Web Services and AI-based planning technologies.

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Neural Network Compensation for Impedance Force Controlled Robot Manipulators

  • Jung, Seul
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.1
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    • pp.17-25
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    • 2014
  • This paper presents the formulation of an impedance controller for regulating the contact force with the environment. To achieve an accurate force tracking control, uncertainties in both robot dynamics and the environment require to be addressed. As part of the framework of the proposed force tracking formulation, a neural network is introduced at the desired trajectory to compensate for all uncertainties in an on-line manner. Compensation at the input trajectory leads to a remarkable structural advantage in that no modifications of the internal force controllers are required. Minimizing the objective function of the training signal for a neural network satisfies the desired force tracking performance. A neural network actually compensates for uncertainties at the input trajectory level in an on-line fashion. Simulation results confirm the position and force tracking abilities of a robot manipulator.