• Title/Summary/Keyword: Practical inference

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Web Enabled Expert Systems using Hyperlink-based Inference

  • Yong U. Song;Kim, Wooju;June S. Hong
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2003.05a
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    • pp.319-328
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    • 2003
  • With the proliferation of WWW, providing more intelligence to Web sites has become a major concern in e-business industry. In recent days, this trend is more accelerated by prosperity of CRM (Customer Relationship Management) in terms of various aspects such as product recommendation, self after service, etc. To accomplish this goal, many e-companies are eager to embed web enabled rule-based system, that is, expert systems into their Web sites and several well-known commercial tools are already available in the market. Most of those tools are developed based on CGI so far but CGI based systems inherently suffer over-burden problem when there are too many service demands at the same time due to the nature of CGI. To overcome this limitation of the existing CGI based expert systems, we propose a new form of Web-enabled expert system using hyperlink-based inference mechanism. In terms of burden to Web server, our approach is proven to outperform CGI based approach theoretically and also empirically. For practical purpose, our this approach is implemented in a software system, WeBIS and a graphic rule editing methodology, Expert Diagram is incorporated into the system to facilitates rule generation and maintenance. WeBIS is now successfully operated for financial consulting in the web site of a leading financial consulting company in Korea.

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A BAYESIAN ANALYSIS FOR PRODUCT OF POWERS OF POISSON RATES

  • KIM HEA-JUNG
    • Journal of the Korean Statistical Society
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    • v.34 no.2
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    • pp.85-98
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    • 2005
  • A Bayesian analysis for the product of different powers of k independent Poisson rates, written ${\theta}$, is developed. This is done by considering a prior for ${\theta}$ that satisfies the differential equation due to Tibshirani and induces a proper posterior distribution. The Gibbs sampling procedure utilizing the rejection method is suggested for the posterior inference of ${\theta}$. The procedure is straightforward to specify distributionally and to implement computationally, with output readily adapted for required inference summaries. A salient feature of the procedure is that it provides a unified method for inferencing ${\theta}$ with any type of powers, and hence it solves all the existing problems (in inferencing ${\theta}$) simultaneously in a completely satisfactory way, at least within the Bayesian framework. In two examples, practical applications of the procedure is described.

An Integrated Sequential Inference Approach for the Normal Mean

  • Almahmeed, M.A.;Hamdy, H.I.;Alzalzalah, Y.H.;Son, M.S.
    • Journal of the Korean Statistical Society
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    • v.31 no.4
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    • pp.415-431
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    • 2002
  • A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.

Intelligent Support System for Ship Steering Control System Based on Network

  • Seo, Ki-Yeol;Suh, Sang-Hyun;Park, Gyei-Kark
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.301-306
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    • 2006
  • The important field of research on ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships and the safety of navigation. As a way of practical application for a smart ship based on network system, this paper proposes the intelligent support system for ship steering control system based on TCP/IP and desires to testify the validity of the proposal by applying the fuzzy control model to the steering control system. As the specific study methods, the fuzzy inference was adopted to build the maneuvering models of steersman, and then the network system was implemented using the TCP/IP socket-based programming. Lastly, the miniature model steering control system combined with LIBL (Linguistic Instruction-based Learning) was designed to testify for its effectiveness.

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System Modelling with Fuzzy Inference and Its Implementation to Auto-Tuning (퍼지추론을 이용한 시스템 모델링 및 오토-튜닝의 구현)

  • Lee, Dong-Jin;Lee, Un-Cheol;Byun, Hwang-Woo;Nam, Moon-Hyun
    • Proceedings of the KIEE Conference
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    • 1993.07a
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    • pp.214-217
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    • 1993
  • This paper presents a new identification method which utilizes fuzzy inference in parameter identification. The proposed system has an additional control loop where a real plant is replaced by a plant model. The control system to be designed is to satisfy the following specifications: 1) It has zero steady-state error. 2) It has adequate damping characteristics. 3) 1),2) satisfied, it has a shortest rise-time. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. This method is effective in auto-tuning because the response of the closed loop is verified. The proposed method is tested in simulation for several plants with first- order lags and dead-times. The results show that the proposed method is effective in practical use.

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Lightweight Single Image Super-Resolution by Channel Split Residual Convolution

  • Liu, Buzhong
    • Journal of Information Processing Systems
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    • v.18 no.1
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    • pp.12-25
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    • 2022
  • In recent years, deep convolutional neural networks have made significant progress in the research of single image super-resolution. However, it is difficult to be applied in practical computing terminals or embedded devices due to a large number of parameters and computational effort. To balance these problems, we propose CSRNet, a lightweight neural network based on channel split residual learning structure, to reconstruct highresolution images from low-resolution images. Lightweight refers to designing a neural network with fewer parameters and a simplified structure for lower memory consumption and faster inference speed. At the same time, it is ensured that the performance of recovering high-resolution images is not degraded. In CSRNet, we reduce the parameters and computation by channel split residual learning. Simultaneously, we propose a double-upsampling network structure to improve the performance of the lightweight super-resolution network and make it easy to train. Finally, we propose a new evaluation metric for the lightweight approaches named 100_FPS. Experiments show that our proposed CSRNet not only speeds up the inference of the neural network and reduces memory consumption, but also performs well on single image super-resolution.

Simple SPICE memristor model for neuromorphic system (뉴로모픽 시스템을 위한 간단한 SPICE 멤리스터 모델)

  • Choi, Gyumin;Park, Byeong-Jun;Rue, Gi-Hong;Hahm, Sung-Ho
    • Journal of Sensor Science and Technology
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    • v.30 no.4
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    • pp.261-266
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    • 2021
  • A simple memristor model is proposed for the neuromorphic system in the Simulation Program for Integrated Circuits Emphasis (SPICE). The memristive I-V characteristics with different voltage and frequencies were analyzed. And with the model, we configured a learning and inference system with 4 by 4 memristor array to show the practical use of the model. We examined the applicability by configuring the simplest neuromorphic circuit. The total simulation time for the proposed model was 18% lesser than that for the one-memristor model. When compared with more memristor models in a circuit, the time became even shorter.

Variable Control in Inductive Inference for Engineering Education (공학교육에서 귀납법 추론을 위한 변수 통제)

  • Hwang, Un Hak
    • Journal of Practical Engineering Education
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    • v.6 no.1
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    • pp.1-7
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    • 2014
  • The variable control in the inductive inference for the confirmation and verification when the experimental data are collected is studied by applying the principle of probability inference. The control in engineering experiments is to protect any effect by of intervening variable except primary independent variable on the dependent variable. By the special condition the possibility for developing a phenomenon will be maximized; otherwise, by the extraneous condition the possibility for developing a phenomenon will be minimized. By doing so, the control may provide insurance for the causal relationship between the certain prior event (independent variable) and the post-event (the dependent variable). Some experiments by using both elliptical trainer and tread mill under the variable control are performed in order to find the relations between the energy expenditure, the respiratory exchange ratio (RER), and the heart rate (HR) against the exercise speed.

Design and Implementation of Knowledge Base System for Fault Diagnosis (고장진단을 위한 지식기반 시스템의 설계 및 구현)

  • Jeon, Keun-Hwan;Shin, Sung-Yun;Shin, Jeong-Hun;Lee, Yang-Won;Ryu, Keun-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.38 no.6
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    • pp.57-69
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    • 2001
  • Expert system is one of AI area. It simulates the human's way of thinking to give solutions of problem in many applications. Most expert system consists of many components such as inference engine, knowledge base, and so on. Especially the performance of expert system depend on the control of efficiency of inference engine. Inference engine has to get features; first, if possible to minimize restrictions when it constructed the knowledge base. second, it has to serve various kinds of inferencing methods. In this paper we propose knowledge scheme for representing domain knowledge in ease, knowledge implementation technique for inferencing, and integrated knowledge-base engine with blackboard and inference engine. And we describe a expert system prototype that implemented in this paper using proposed methods, it perform diagnose about heavy industrial device. The fault diagnosis system prototype has been studied in this paper will be practical foundation in the research area of knowledge based system.

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Diagnosis of Deterioration Grades for Overhead Transmission Lines using Adaptive Neuro-Fuzzy Inference System (적응 뉴로퍼지 추론시스템을 이용한 가공 송전선의 열화등급 진단)

  • 김성덕;이상래
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.17 no.4
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    • pp.57-63
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    • 2003
  • Aluminum Stranded Conductors Steel Reinforced (ACSR) in overhead transmission lines have slowly degraded due to pollutants in the air for a long period of time, so in the 2000, a number of them has been exceeded over their forecasted useful life. Since most of them are faced with assessment their present conditions in regard to economical maintenance, in this paper, we have suggested a method in order to evaluate the current condition of aged conductors by using dominant parameters such as elapsed years, environment index, and conductor configuration. A diagnostic system for predicting the deterioration grades corresponding to the lifetime of aged conductors is described, which is designed as an Adaptive Neuro-fuzzy Inference System (ANFIS) based on knowledge and experiences of experts. Applying this diagnostic system to practical transmission lines in domestic, it is shown that the system can be effectively used as a guide to perform nondestructive diagnosis and economical operation for old ACSR conductors.