• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.417-423
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• 2002

In this paper, we propose intelligent steering control system that apply LIBL(Linguistic Instruction Based Learning) method to steering system of ship and take the place of process that linguistic instruction such as officer s steering instruction is achieved via ableman. We embody ableman s suitable steering manufacturing model using fuzzy inference rule by specific method of study, and apply LIBL method to present suitable meaning element and evaluation rule to steering system of ship, embody intelligent steering gear control system that respond more efficiently on officer s linguistic instruction. We presented evaluation rule to constructed steering manufacturing model based on ableman s experience, and propose rudder angle for steering system, compass bearing arrival time, meaning element of stationary state, and correct ableman manufacturing model rule using fuzzy inference. Also, we apply LIBL method to ship control simulator and confirmed the effectiveness.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.93-97
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• 2002

In this paper, we propose intelligent steering control system that apply LIBL(Linguistic Instruction Based Learning) method to steering system of ship and take the place of process that linguistic instruction such as officer's steering instruction is achieved via ableman. We embody ableman's suitable steering manufacturing model using fuzzy inference rule by specific method of study, and apply LIBL method to present suitable meaning element and evaluation rule to steering system of ship, embody intelligent steering gear control system that respond more efficiently on officer's linguistic instruction. We presented evaluation rule to constructed steering manufacturing model based on ableman's experience, and propose rudder angle for steering system, compass bearing arrival time, meaning element of stationary state, and correct ableman manufacturing model rule using fuzzy inference. Also, we apply LIBL method to ship control simulator and confirmed the effectiveness.

• Journal of Navigation and Port Research
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• v.42 no.5
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• pp.365-370
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• 2018

Currently, container transport services play a substantial role in global cargo transportation, by serving as an intermodal between exporter and importer. Container shipping has become increasingly important over the past few decades, due to obvious advantages. However, Vietnam's container market has shown severely ongoing competition among numerous domestic and foreign shipping lines, resulting in serious consequences occurring such as freight rates substantially decreasing within the last 10 years. Vietnam's sea lanes have become more defensive, to cover losses of shipping companies. Selection of criteria for competitive evaluation of container transport companies is necessary, to facilitate addressing the problems within the enterprise, especially relating to its position in the market and from here, business management can implement strategic plans and reasonable policy, to survive and grow.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.698-703
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• 1994

In the actual sound environment, the random signal often shows a complex fluctuation pattern apart from a standard Gaussian distribution. In this study, an evaluation method for the sound environmnetal system is proposed in the generalized form applicable to the actual stochastic phenomena, by introducing two type information processing methods based on the regression model of expansion series type and the Fuzzy probability. The effectiveness of the proposed method are confirmed experimentally too by applying it to the observed data in the actual noise environment.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.4
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• pp.24-30
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• 2002

In grinding operations, one of the most important problems is to increase efficiency of process. In order to achieve this purpose, it is necessary to administer the tool lift of grinding wheel and to optimize grinding conditions. Frequently dressing result in lowering the process efficiency remarkably and makes production cost high. On the other hand, grinding with a worn wheel causes the workpiece surface roughness to increase and often results in the occurrence of such troubles as chatter vibration and homing.

• Smart Structures and Systems
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• v.33 no.5
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• pp.365-374
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• 2024

This paper adopts a new approach in which nonlinear vibrations can be controlled using fuzzy controllers by optimal grey evolutionary algorithm. If the fuzzy controller cannot stabilize the systems, then the high frequency is injected into the system to assist the controller, and the system is asymptotically stabilized by adjusting the parameters. This paper uses the GM (grey model) and the neural network prediction model. The structure of the neural network is improved from a single factor, and multiple data inputs are extended to various factors and numerous data inputs. The improved model expands the applicable range of uncontrolled elements and improves the accuracy of controlled prediction, using the model that has been trained and stabilized by multiple learning. The simulation results show that the improved gray neural network model has higher prediction accuracy and reliability than the traditional GM model, improving controlled management and pre-control ability. In the combined prediction, the time series parameters and the predicted values obtained from the GM (1,1) (Grey Model of first order and one variable) are simultaneously used as the input terms of the neural network, considering the influence of the non-equal spacing of the data, which makes the results of the combined gray neural network model more rationalized. By adjusting the model structure and system parameters to simulate and analyze the controlled elements, the corresponding risk change trend graphs and prediction numerical calculation results are obtained, which also realize the effective prediction of controlled elements. According to the controlled warning principle and objective, the fuzzy evaluation method establishes the corresponding early warning response method. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2151-2158
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• 2000

This paper presents vibration control performance of a passenger vehicle installed with the mixed-mode type ER engine mounts. The performance is evaluated via hardware-in-the-loop-simulation(HILS) method. As a first step, a dynamic model of a vehicle featuring the ER engine mounts is formulated by taking into account the engine excitation forces. A new type of the fuzzy skyhook controller is then established in order to control both engine and body vibrations. This is accomplished by adopting a weighting parameter between two performance criteria which is to be determined from the fuzzy algorithm. Vertical displacement and acceleration of the engine mount obtained from the HILS method are provided in the frequency domain. In addition, vibration control performance between the conventional hydraulic engine mount and the proposed engine mount is compared in the time and frequency domains.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.163-177
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• 2024

The fingerprint image quality relies on the clearness of separated ridges by valleys and the uniformity of the separation. The condition of skin still dominate the overall quality of the fingerprint. However, the identification performance of such system is very sensitive to the quality of the captured fingerprint image. Fingerprint image quality analysis and enhancement are useful in improving the performance of fingerprint identification systems. A fuzzy technique is introduced in this paper for both fingerprint image quality analysis and enhancement. First, the quality analysis is performed by extracting four features from a fingerprint image which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the Global Contrast Factor (GCF). A fuzzy logic technique that uses Mamdani fuzzy rule model is designed. The fuzzy inference system is able to analyse and determinate the fingerprint image type (oily, dry or neutral) based on the extracted feature values and the fuzzy inference rules. The percentages of the test fuzzy inference system for each type is as follow: For dry fingerprint the percentage is 81.33, for oily the percentage is 54.75, and for neutral the percentage is 68.48. Secondly, a fuzzy morphology is applied to enhance the dry and oily fingerprint images. The fuzzy morphology method improves the quality of a fingerprint image, thus improving the performance of the fingerprint identification system significantly. All experimental work which was done for both quality analysis and image enhancement was done using the DB_ITS_2009 database which is a private database collected by the department of electrical engineering, institute of technology Sepuluh Nopember Surabaya, Indonesia. The performance evaluation was done using the Feature Similarity index (FSIM). Where the FSIM is an image quality assessment (IQA) metric, which uses computational models to measure the image quality consistently with subjective evaluations. The new proposed system outperformed the classical system by 900% for the dry fingerprint images and 14% for the oily fingerprint images.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.264-267
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• 2004

In identifying flood vulnerable areas, three methods are generally deployed: the geomorphology method which is based on topographic features; the past evidence method based on observed data of past actual floods; and, prediction of flood areas through hydrologic models. This study aims to improve the prediction model of the geomorphology method through the application of fuzzy method in GIS modeling. The generally used GIS method of superimposing thematic map layers assumes crisp boundaries of the layers, which results in either risk-averse solutions or risk-taking solutions. The introduction of fuzzy concepts to processing of evaluation criteria (DEM, slope, aspect) solves this problem. As the result of applying the fuzzy method to a test site in the west Nak-Dong river, similar flood vulnerable areas were predicted as when using the conventional Boolean criteria. The resulting map, however, showed varying degree of uncertainty of flooding in these areas. This extra information is deemed to be valuable in taking phased actions during flood response, leading to a more effective and timely decision-making.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.1
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• pp.97-104
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• 2010

At present, the biological nutrient removal (BNR) process for removal of nitrogen and phosphorus is being constructing to keep pace with the reinforced standard of effluent quality and the traditional activated sludge process of preexistence is being promoting to retrofit. At the most case of retrofitting, processes are subjected to be under consideration as alternative BNR process for retrofitting. However, process evaluation methods are restricted to compare only treatment efficiency. Therefore, when BNR process apply, process evaluation was needed various method for treatment efficiency as well as sludge production and aeration cost, and all. In this study, the evaluation method of alternative process was suggested for the case for retrofitting S wastewater treatment plant which has been operated the standard activated sludge process. Three BNR processes for evaluation of proper alternatative process were selected and evaluated with suggested method. The selected $A^2$/O, VIP and DNR processes were evaluated using the mathematical model which is time and cost effective as well as gathered objective evaluation criteria. The evaluation between 5 individual criteria was possible including sludge production and energy efficiency as well as treatment performance. The objective final decision method for selection of optimal process was established through the fuzzy inference.