• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.1-6
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• 2007

The SVDD (support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the feature space in order to distinguish a set of normal data from all other possible abnormal objects. Recently, with the objective of generalizing the SVDD which treats all training data with equal importance, the so-called D-SVDD (density-induced support vector data description) was proposed incorporating the idea that the data in a higher density region are more significant than those in a lower density region. In this paper, we consider the problem of further improving the D-SVDD toward the use of a partial reference set for testing, and propose an LMI (linear matrix inequality)-based optimization approach to solve the improved version of the D-SVDD problems. Our approach utilizes a new class of density-induced distance measures based on the RSDE (reduced set density estimator) along with the LMI-based mathematical formulation in the form of the SDP (semi-definite programming) problems, which can be efficiently solved by interior point methods. The validity of the proposed approach is illustrated via numerical experiments using real data sets.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.8-13
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• 1997

In multi-server environment there are many servers which are able to process job requests. So we bave to design a mechanism that selects appropriate servers for processing each job request while maximizing server throughput and minimizing average response time of requests. Conventional methods ac~ opt the load of each server as criteria of server selection. that is, they select a server whose load is not bigger than the others. In this work we propose an approach that uses the degree of server performance, server load and the estimated service time of requested job as guidelines of server selection. We incorporate fuzzification techniques and expert knowledge in this approach. Comparing the performances c~f our approach to that of conventional one, experiments show that the proposed approach provides better performances.

• Journal of the Korea Society of Computer and Information
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• v.14 no.6
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• pp.17-26
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• 2009

In national defense, established information systems are mainly based on simple information processing, such as mass data query. They have thus lacked intelligent ability of information and knowledge representation ability. We therefore need the research about the construction of military ontology which is the main topic for knowledge construction. Military ontology can help us develop the intelligent national defense information system which can search and manage information efficiently. In this paper, we present the six-step bottom-up approach for military ontology extraction, then we apply this approach to one of military domain, called national defense educational training, and finally implement it using $Prot\acute{e}g\acute{e}$ which is one of the most useful ontology development tool.

• Journal of Power System Engineering
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• v.12 no.6
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• pp.42-49
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• 2008

The most important job in the container terminal area is to handle the cargo effectively in the limited time. To achieve this object, many strategies have been introduced and applied to. If we consider the automated container terminal, it is necessary that the cargo handling equipments are equipped with more intelligent control systems. From the middle of the 1990's, an automated rail-mounted gantry crane(RMGC) and rubber-tired gantry crane(RTG) have been developed and widely used to handle containers in the yards. Recently, in these cranes, the many equipments like CCD cameras and sensors are mounted to cope with the automated terminal environment. In this paper, we try to support the development of more intelligent automated cranes which make the cargo handling be performed effectively in the yards. For this plant, the modelling, tracking control, anti-sway system design, skew motion suppressing and complicated motion control and suppressing problems must be considered. Especially, in this paper, the system modelling and tracking control approach are discussed. And, we design the tracking control system incorporating an observer based on the 2DOF servo system design approach to obtain the desired state informations. In the case of observer design, a weighted $H_{\infty}$ error bound approach for a state estimator is considered. Based on an algebraic Riccati equation(inequality) approach, a necessary and sufficient condition for the existence of a full-order estimator which satisfies the weighted $H_{\infty}$ error bound is introduced. Where, the condition for existence of the estimator is denoted by a Linear Matrix Inequality(LMI) which gives an optimized solution and observer gain. Based on this result, we apply it to the tracking control system design for the transfer crane.

• Journal of Internet Computing and Services
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• v.5 no.2
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• pp.97-105
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• 2004

The reason that an intelligent agent cannot understand the representation of its own perception or activity is caused by the traditional syntactic approach that translates a semantic feature into a simulated string, To implement an autonomously learning intelligent agent, Cohen introduces a experimentally semantic approach that the system learns a contentful representation of physical schema from physically interacting with environment using its own sensors and effectors. We propose that negation is a meta-level schema that enables an agent to recognize its own physical schema, To improve the planner's efficiency, Graphplan introduces the control rule that manipulates the inconsistency between planning operators, but it cannot cognitively understand negation and suffers from redundancy problem. By introducing a negative function not, IPP solves the problem, but its approach is still syntactic and is inefficient in terms of time and space. In this paper, we propose that, to represent a negative fact, a positive atom, which is called opposite concept, is a very efficient technique for implementing an cognitive agent, and demonstrate some empirical results supporting the hypothesis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2038-2057
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• 2017

Gaussian learning is a new technology in the computational intelligence area. However, this technology weakens the learning ability of a particle swarm and achieves a lack of diversity. Thus, this paper proposes a vector Gaussian learning strategy and presents an effective approach, named particle swarm optimization based on vector Gaussian learning. The experiments show that the algorithm is more close to the optimal solution and the better search efficiency after we use vector Gaussian learning strategy. The strategy adopts vector Gaussian learning to generate the Gaussian solution of a swarm's optimal location, increases the learning ability of the swarm's optimal location, and maintains the diversity of the swarm. The method divides the states into normal and premature states by analyzing the state threshold of the swarm. If the swarm is in the premature category, the algorithm adopts an inertia weight strategy that decreases linearly in addition to vector Gaussian learning; otherwise, it uses a fixed inertia weight strategy. Experiments are conducted on eight well-known benchmark functions to verify the performance of the new approach. The results demonstrate promising performance of the new method in terms of convergence velocity and precision, with an improved ability to escape from a local optimum.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.881-886
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.583-595
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• 2008

In this paper, we introduce a fuzzy nonlinear feedback approach to the control of a class of chaotic dynamical systems. The fuzzy Parallel Distributed Compensation with Reduced Rule Base approach (PDC_RRB) is proposed. The design procedure is conceptually simple and considered to a nonlinear optimal and robust control problem due to the nonlinear nature of the Takagi-Sugeno (TS) fuzzy system. Simulation results are provided to show the effictiveness of the proposed methodology.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.403-413
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• 1999

Today's businesses are experiencing intensive global competition and the most accelerating pace of change ever. Competitors have sprung up that were not even on the business's radar. This environment impacts all decisions and strategies as business try to dominate their market or their marker or their industry merely to survive. So recently most of organizations are considering on building the data warehouse system to pursuit the business intelligence. We need the proper model to guide the approach to plan building data warehouse system when we want to plan it in considering the organizational status. Therefore we suggest a model to decide the approach to build data warehouse considering the project's environmental factors. First we review Ronald S. Swift(1998)'s five environmental factors that we have to consider when planing to build data warehouse. Then we propose a model to decide DW approach by the degree of those factors to be measured. DW approaches in this model are classified in conservative approach, increasing approach, enterprise wide approach, and ideal approach.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1093-1098
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• 2003

In this paper, a practical methodology of hand-manipulator motion coordination for indoor service robot is introduced. This paper describes the procedures of opening door performed by service robot as a noticeable example of motion coordination. This paper presents well-structured framework for hand-manipulator motion coordination, which includes intelligent sensor data interpretation, object shape estimation, optimal grasping, on-line motion planning and behavior-based task execution. This proposed approach is focused on how to integrate the respective functions in harmony and enable the robot to complete its operation under the limitation of usable resources. As a practical example of implementation, the successful experimental results in opening door whose geometric parameters are unknown beforehand are provided.