• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.516-523
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• 2000

In this paper, intelligent methods using digital protective relay in power supervisory control system is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which has various load environments and capacities in power systems. The spectrum pattern of input currents was used to monitor to state of induction motors, and by clustering the spectrum pattern of input currents, the newly occurrence of spectrums pattern caused by faults were detected. For diagnosis of the fault detected, the fuzzy fault tree was derived, and the fuzzy relation equation representing the relation between an induction motor fault and each fault type, was solved. The solution of the fuzzy relation equation shows the possibility of each fault's occurring. The results obtained are summarized as follows: 1) The test result on the basis of KEMC1120 and IEC60255, show that the operation time error of the digital motor protective relay is improved within ${\pm}5%$. 2) Using clustering algorithm by unsupervisory learning, an on-line fault detection method, not affected by the characteristics of loads and rates, was implemented, and the degree of dependency by experts during fault detection was reduced. 3) With the fuzzy fault tree, fault diagnosis process became systematic and expandable to the whole system, and the diagnosis for sub-systems can be made as an object-oriented module.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.76-82
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• 2010

In this paper, we develop Linguistic Model (LM) based on information granules as a systematic approach to generating fuzzy if-then rules from a given input-output data. The LM introduced by Pedrycz is performed by fuzzy information granulation obtained from Context-based Fuzzy Clustering(CFC). This clustering estimates clusters by preserving the homogeneity of the clustered patterns associated with the input and output data. Although the effectiveness of LM has been demonstrated in the previous works, it needs to improve in the sense of performance. Therefore, we focus on the automatic generation of linguistic contexts, addition of bias term, and the transformed form of consequent parameter to improve both approximation and generalization capability of the conventional LM. The experimental results revealed that the improved LM yielded a better performance in comparison with LM and the conventional works for automobile MPG(miles per gallon) predication and Boston housing data.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.8
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• Geomechanics and Engineering
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• v.28 no.2
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• pp.145-155
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• 2022

Safety is a most important parameters in underground railway transportation; Also stability of underground tunnel is very important in tunneling engineering. Design of a reliable support system requires an evaluation of both ground demand and support capacity. Iran's traditional railway tunnels are mainly supported with masonry structures or unsupported in high quality rock masses. A decrease in rock mass quality due to changes in groundwater regime creep and fatigue in rock and similar phenomena causes tunnel safety to decrease during time. The case study is an old tunnel in Iran, called "Keshvar"; it is more than 50 years old railway organization. In operating this Tunnel, until the several problems came up based on stability and leaking water. The goal of study is evaluation of the various reinforcement systems for supporting of the tunnel. The optimal selection of the reinforcement system is examined using TOPSIS Fuzzy method in light of the looming and available uncertainties. Several factors such as; the tunnel span, maintenance, drainage, sealing, ventilation, cost and safety were based to choose the method and system of designing. Therefore, by identifying these parameters, an optimal reinforcement system was selected and introduced. Based on optimization system for analysis, it is revealed that the systematic rock bolts and shotcrete protection had a most appropriate result for these kind of tunnel in Iran.

• The Journal of Industrial Distribution & Business
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• v.8 no.1
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• pp.33-39
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• 2017

Purpose - The main purpose of the current study is to examine the impact of accounting information quality and information asymmetry on the underinvestment phenomenon among the listed companies on the Tehran Stock Exchange (TSE). Research design, data, and methodology - The population includes 94 firms selected through systematic sampling. The data is collected from the audited financial statements of the firms provided by TSE's website from 2010 to 2015. Accounting information quality and information asymmetry is considered as independent variables, and their impact is examined on the dependent variable (underinvestment). Results - The statistical results, based on data collected from 94 listed companies on the TSE during 2010-2015, revealed positive impact of accounting information quality and positive impact of information asymmetry on underinvestment. There was a significant relationship between accrual quality (AQ) and underinvestment, and spread and underinvestment. The results also showed that information asymmetry is the main factor in the creation underinvestment. Conclusions - Findings of this article can assist accounting researchers and theoreticians in comparing Real world facts with hypotheses developed with respect to accounting information quality, information asymmetry and underinvestment. However, the results of fuzzy regression analysis indicate significant relationships between the independent variable except underinvestment.