• 제목/요약/키워드: ES(Expert System)

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A Novel Unweighted Combination Method for Business Failure Prediction Using Soft Set

  • Xu, Wei;Yang, Daoli
    • Journal of Information Processing Systems
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    • v.15 no.6
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    • pp.1489-1502
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    • 2019
  • This work introduces a novel unweighted combination method (UCSS) for business failure perdition (BFP). With considering features of BFP in the age of big data, UCSS integrates the quantitative and qualitative analysis by utilizing soft set theory (SS). We adopt the conventional expert system (ES) as the basic qualitative classifier, the logistic regression model (LR) and the support vector machine (SVM) as basic quantitative classifiers. Unlike other traditional combination methods, we employ soft set theory to integrate the results of each basic classifier without weighting. In this way, UCSS inherits the advantages of ES, LR, SVM, and SS. To verify the performance of UCSS, it is applied to real datasets. We adopt ES, LR, SVM, combination models utilizing the equal weight approach (CMEW), neural network algorithm (CMNN), rough set and D-S evidence theory (CMRD), and the receiver operating characteristic curve (ROC) and SS (CFBSS) as benchmarks. The superior performance of UCSS has been verified by the empirical experiments.

Soft Set Theory Oriented Forecast Combination Method for Business Failure Prediction

  • Xu, Wei;Xiao, Zhi
    • Journal of Information Processing Systems
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    • v.12 no.1
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    • pp.109-128
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    • 2016
  • This paper presents a new combined forecasting method that is guided by the soft set theory (CFBSS) to predict business failures with different sample sizes. The proposed method combines both qualitative analysis and quantitative analysis to improve forecasting performance. We considered an expert system (ES), logistic regression (LR), and support vector machine (SVM) as forecasting components whose weights are determined by the receiver operating characteristic (ROC) curve. The proposed procedure was applied to real data sets from Chinese listed firms. For performance comparison, single ES, LR, and SVM methods, the combined forecasting method based on equal weights (CFBEWs), the combined forecasting method based on neural networks (CFBNNs), and the combined forecasting method based on rough sets and the D-S theory (CFBRSDS) were also included in the empirical experiment. CFBSS obtains the highest forecasting accuracy and the second-best forecasting stability. The empirical results demonstrate the superior forecasting performance of our method in terms of accuracy and stability.

Machine-part Group Formation Methodology for Flexible Manufacturing Systems (유연생산시스템(FMS)에서의 기계-부품그룹 형성기법)

  • Ro, In-Kyu;Kwon, Hyuck-Chun
    • Journal of Korean Institute of Industrial Engineers
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    • v.17 no.1
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    • pp.75-82
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    • 1991
  • This research is concerned with Machine-Part Group Formation(MPGF) methodology for Flexible Manufacturing Systems(FMS). The purpose of the research is to develop a new heuristic algorithm for effectively solving MPGF problem. The new algorithm is proposed and evaluated by 100 machine-part incidence matrices generated. The performance measures are (1) grouping ability of mutually exclusive block-diagonal form. (2) number of unit group and exceptional elements, and (3) grouping time. The new heuristic algorithm has the following characteristics to effectively conduct MPGF : (a) The mathematical model is presented for rapid forming the proper number of unit groups and grouping mutually exclusive block-diagonal form, (b) The simple and effective mathematical analysis method of Rank Order Clustering(ROC) algorithm is applied to minimize intra-group journeys in each group and exceptional elements in the whole group. The results are compared with those from Expert System(ES) algorithm and ROC algorithm. The results show that the new algorithm always gives the group of mutually exclusive block-diagonal form and better results(85%) than ES algorithm and ROC algorithm.

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An Application of Blackboard Architecture for the Coordination among the Security Systems (보안 모델의 연동을 위한 블랙보드구조의 적용)

  • 서희석;조대호
    • Journal of the Korea Society for Simulation
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    • v.11 no.4
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    • pp.91-105
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    • 2002
  • The attackers on Internet-connected systems we are seeing today are more serious and technically complex than those in the past. So it is beyond the scope of amy one system to deal with the intrusions. That the multiple IDSes (Intrusion Detection System) coordinate by sharing attacker's information for the effective detection of the intrusion is the effective method for improving the intrusion detection performance. The system which uses BBA (BlackBoard Architecture) for the information sharing can be easily expanded by adding new agents and increasing the number of BB (BlackBoard) levels. Moreover the subdivided levels of blackboard enhance the sensitivity of the intrusion detection. For the simulation, security models are constructed based on the DEVS (Discrete EVent system Specification) formalism. The intrusion detection agent uses the ES (Expert System). The intrusion detection system detects the intrusions using the blackboard and the firewall responses these detection information.

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Coordination among the Security Systems using the Blackboard Architecture (블랙보드구조를 활용한 보안 모델의 연동)

  • 서희석;조대호
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.4
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    • pp.310-319
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    • 2003
  • As the importance and the need for network security are increased, many organizations use the various security systems. They enable to construct the consistent integrated security environment by sharing the network vulnerable information among IDS (Intrusion Detection System), firewall and vulnerable scanner. The multiple IDSes coordinate by sharing attacker's information for the effective detection of the intrusion is the effective method for improving the intrusion detection performance. The system which uses BBA (Blackboard Architecture) for the information sharing can be easily expanded by adding new agents and increasing the number of BB (Blackboard) levels. Moreover the subdivided levels of blackboard enhance the sensitivity of the intrusion detection. For the simulation, security models are constructed based on the DEVS (Discrete Event system Specification) formalism. The intrusion detection agent uses the ES (Expert System). The intrusion detection system detects the intrusions using the blackboard and the firewall responses to these detection information.

Optimal Control of Gantry Crane Using Genetic Programming (유전프로그래밍에 의한 겐트리 크레인의 최적제어에 관한 연구)

  • 이영진;배종일;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 1998.10a
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    • pp.153-158
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    • 1998
  • In this paper, we present a design of optimal 2-DOF PID controller for control of gantry crane which has to control swing motion and trolley position. For tuning the parameter of 2-DOF PID controller, we used evolution strategy(ES). During operate the crane system in yard, the goal is transporting the load to a goal position as quick as possible without rope oscillation. The crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. However, we developed an optimal controller which has to control the crane system with disturbance.

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An Optimal Control of Container Crane Using Evolution Strategy (진화전략을 이용한 컨테이너 크레인의 최적제어에 관한 연구)

  • 이영진;이권순
    • Journal of Korean Port Research
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    • v.12 no.2
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    • pp.217-224
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    • 1998
  • During the operation of crane system in container yard, the objective is to transport the load to a goal position as quick as possible without rope oscillation. The container crane is generally operated by an expert operator, but recently an automatic control system with high speed and rapid transportation is required. Therefore, we developed an optimal controller which has to control the crane system with disturbances. In this paper, we present a design of optima 2-DOF PID controller for the control of gantry crane which has to control swing motion and trolley position. We used evolution strategy(ES) to tune the parameters of 2-DOF PID controller. It was compared with general PID controller. The computer simulations show that the proposed method has better performances than the other method.

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Heart Sound Recognition by Analysis of wavelet transform and Neural network.

  • Lee, Jung-Jun;Lee, Sang-Min;Hong, Seung-Hong
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.1045-1048
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    • 2000
  • This paper presents the application of the wavelet transform analysis and the neural network method to the phonocardiogram (PCG) signal. Heart sound is a acoustic signal generated by cardiac valves, myocardium and blood flow and is a very complex and nonstationary signal composed of many source. Heart sound can be discriminated normal heart sound and heart murmur. Murmurs have broader frequency bandwidth than the normal ones and can occur at random position of cardiac cycle. In this paper, we classified the group of heart sound as normal heart sound(NO), pre-systolic murmur(PS), early systolic murmur(ES), late systolic murmur(LS), early diastolic murmur(ED). And we used the wavelet transform to shorten artifacts and strengthen the low level signal. The ANN system was trained and tested with the back- propagation algorithm from a large data set of examples-normal and abnormal signals classified by expert. The best ANN configuration occurred with 15 hidden layer neurons. We can get the accuracy of 85.6% by using the proposed algorithm.

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Evolutionary PSR Estimator for Classification of Sonar Target (소나표적의 식별을 위한 진화적 PSR 추정기)

  • Kim, Hyun-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.08a
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    • pp.149-150
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    • 2008
  • Generally, the propeller shaft rate (PSR) estimation algorithm for the classification of the sonar target has the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family from the frequency spectrum, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

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Evolutionary PSR Estimation Algorithm for Feature Extraction of Sonar Target (소나 표적의 특징정보추출을 위한 진화적 PSR 추정 알고리즘)

  • Kim, Hyun-Sik
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.5
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    • pp.632-637
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    • 2008
  • In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.