• Title/Summary/Keyword: Intelligent machine

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Variable length Chromosomes in Genetic Algorithms for Modeling the Class Boundaries

  • Bandyopadhyay, Sanghamitra;Pal, Sankar K.;Murthy, C.A.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.634-639
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    • 1998
  • A methodology based on the concept of variable string length GA(VGA) is developed for determining automatically the number of hyperplanes and their appropriate arrangement for modeling the class boundaries of a given training data set in RN. The genetic operators and fitness functionare newly defined to take care of the variability in chromosome length. Experimental results on different artificial and real life data sets are provided.

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Fuzzy Subsystems of A Fuzzy Finite State Machine

  • Hwang, Seok-Yoon;Kim, Ki-Hwan
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.2
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    • pp.156-160
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    • 2001
  • In this paper we define fuzzy subsystems of a fuzzy finite state machine by using maps $S^{\alpha}$ of each state subset to its all $\alpha$-successors, which is a natural generalization of crisp submachines as fuzzy. And the corresponding concepts are also examined. also examined.

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Power System Voltage Stability Classification Using Interior Point Method Based Support Vector Machine(IPMSVM)

  • Song, Hwa-Chang;Dosano, Rodel D.;Lee, Byong-Jun
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.9 no.3
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    • pp.238-243
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    • 2009
  • This paper present same thodology for the classification of power system voltage stability, the trajectory of which to instability is monotonic, using an interior point method based support vector machine(IPMSVM). The SVM based voltage stability classifier canp rovide real-time stability identification only using the local measurement data, without the topological information conventionally used.

Man-Machine System for Controlling Triple Inverted Pendulum

  • S.Masui;T.Terano;Oh, K.shima
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1289-1292
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    • 1993
  • Though fuzzy control is very popular at present, the application field of fuzzy system will be wider if we design it as a man-machine system. We suggest, in this paper, a man-machine cooperating system which makes easy the manual control of a triple inverted pendulum by simple fuzzy controller, and verify its effectiveness by experiments.

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UV Nanoimprint Lithography using an Elementwise Patterned Stamp and Pressurized Air (Elementwise Patterned Stamp와 부가압력을 이용한 UV 나노임프린트 리소그래피)

  • Sohn H.;Jeong J.H.;Sim Y.S.;Kim K.D.;Lee E.S.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.672-675
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    • 2005
  • To imprint 70-nm wide line-patterns, we used a newly developed ultraviolet nanoimprint lithography (UV-NIL) process in which an elementwise patterned stamp (EPS), a large-area stamp, and pressurized air are used to imprint a wafer in a single step. For a single-step UV-NIL of a 4' wafer, we fabricated two identical $5'\times5'\times0.09'(W{\times}L{\times}H)$ quartz EPSs, except that one is with nanopatterns and the other without nanopatterns. Both of them consist of 16 small-area stamps, called elements, each of which is $10\;mm\;\times\;10\;mm$. UV-curable low-viscosity resin droplets were dispensed directly on each element of the EPSs. The volume and viscosity of each droplet are 3.7 nl and 7 cps. Droplets were dispensed in such a way that no air entrapment between elements and wafer occurs. When the droplets were fully pressed between ESP and wafer, some incompletely filled elements were observed because of the topology mismatch between EPS and wafer. To complete those incomplete fillings, pressurized air of 2 bar was applied to the bottom of the wafer for 2 min. Experimental results have shown that nanopatterns of the EPS were successfully transferred to the resin layer on the wafer.

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Development of Fuzzy Support Vector Machine for Pattern Classification (패턴 분류를 위한 Fuzzy Twin Support Vector machine 개발)

  • Cheon, Min-Gyu;Yun, Chang-Yong;Kim, Eun-Tae;Park, Min-Yong
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.11a
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    • pp.279-282
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    • 2007
  • Support Vector Machine(SVM)은 통계적 학습 이론에 기반을 둔 분류기이다. 또한 Twin Support Vector Machine(TWSVM)은 이진 SVM 분류기의 한 종류로써, 서로 관련된 두 개의 SVM 유형 문제를 통해 평행하지 않은 두 개의 평면을 결정하고 이 두 평면을 통해 분류기를 완성하는 방식이다. 이러한 방식은 TWSVM은 학습 시간이 SVM에 비해 훨씬 짧으며, SVM과 비교하여 떨어지지 않는 성능을 보여준다. 본 논문은 분류기 입력에 Fuzzy Memvership을 적용하는 방식의 TWSVM을 제안하고, 2차원 벡터 입력에 대한 실험을 통하여 기존에 제시 되었던 TWSVM과 비교한다.

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Modern Probabilistic Machine Learning and Control Methods for Portfolio Optimization

  • Park, Jooyoung;Lim, Jungdong;Lee, Wonbu;Ji, Seunghyun;Sung, Keehoon;Park, Kyungwook
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.2
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    • pp.73-83
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    • 2014
  • Many recent theoretical developments in the field of machine learning and control have rapidly expanded its relevance to a wide variety of applications. In particular, a variety of portfolio optimization problems have recently been considered as a promising application domain for machine learning and control methods. In highly uncertain and stochastic environments, portfolio optimization can be formulated as optimal decision-making problems, and for these types of problems, approaches based on probabilistic machine learning and control methods are particularly pertinent. In this paper, we consider probabilistic machine learning and control based solutions to a couple of portfolio optimization problems. Simulation results show that these solutions work well when applied to real financial market data.

Development of Intellingent Design Support System for Machine Tools (지능형 공작기계 설계 지원 시스템 개발)

  • 차주헌;김종호;박면웅;박지형
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.1022-1027
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    • 1995
  • We present a framework of an intelligent design support system for embodiment design of machine tools which can support efficiently and systematically the machine design by utilizing design knowledge such as objects(part), know-how, public, evaluation, and procedures. The design knowledge of machining center has been accumulated through interview with design experts of machine tool companies. The processes of embodiment design of machining center are established. We also introduce a hybrid knowledge representation so that the systm can easily deal with various and complicated design knowledge. The intelligent design system is being developed on the basis of object-oriented programming, and all parts of a design object, machining center, are also classified by the object-oriented modeling. For the demonstration of effectiveness of the suggested system, a structural design system for machine tools is implemented.

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Machine Learning based Prediction of The Value of Buildings

  • Lee, Woosik;Kim, Namgi;Choi, Yoon-Ho;Kim, Yong Soo;Lee, Byoung-Dai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.8
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    • pp.3966-3991
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    • 2018
  • Due to the lack of visualization services and organic combinations between public and private buildings data, the usability of the basic map has remained low. To address this issue, this paper reports on a solution that organically combines public and private data while providing visualization services to general users. For this purpose, factors that can affect building prices first were examined in order to define the related data attributes. To extract the relevant data attributes, this paper presents a method of acquiring public information data and real estate-related information, as provided by private real estate portal sites. The paper also proposes a pretreatment process required for intelligent machine learning. This report goes on to suggest an intelligent machine learning algorithm that predicts buildings' value pricing and future value by using big data regarding buildings' spatial information, as acquired from a database containing building value attributes. The algorithm's availability was tested by establishing a prototype targeting pilot areas, including Suwon, Anyang, and Gunpo in South Korea. Finally, a prototype visualization solution was developed in order to allow general users to effectively use buildings' value ranking and value pricing, as predicted by intelligent machine learning.

Diagnosing the Cause of Operational Faults in Machine Tools with an Open Architecture CNC

  • Kim Dong Hoon;Kim Sun Ho;Song Jun-Yeob
    • Journal of Mechanical Science and Technology
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    • v.19 no.8
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    • pp.1597-1610
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    • 2005
  • The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) that is independent of a CNC vendor. The OAC and machine tools with an OAC have led to a convenient environment in which user-defined applications can be efficiently implemented within a CNC. This paper proposes a method of diagnosing the cause of operational faults. The method is based on the status of a programmable logic controller in machine tools with an OAC. An operational fault is defined as a disability that occurs during the normal operation of machine tools. Operational faults constitute more than 70 percent of all faults and are also unpredictable because most of them occur without any warning. To quickly and correctly diagnose the cause of an operational fault, two diagnostic models are proposed: the switching function and the step switching function. The cause of the fault is logically diagnosed through a fault diagnosis system using diagnostic models. A suitable interface environment between a CNC and developed application modules is constructed to implement the diagnostic functions in the CNC domain. The results of the diagnosis were displayed on a CNC monitor for machine operators and transmitted to a remote site through a Web browser. The proposed diagnostic method and its results were useful to unskilled machine operators and reduced the machine downtime.