• 한국해양공학회지
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• 제37권5호
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• pp.198-204
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• 2023

In response to the complexity and time demands of conventional methods for estimating the hydrodynamic coefficients, this study aims to revolutionize ship maneuvering analysis by utilizing automatic identification system (AIS) data and the Support Vector Regression (SVR) algorithm. The AIS data were collected and processed to remove outliers and impute missing values. The rate of turn (ROT), speed over ground (SOG), course over ground (COG) and heading (HDG) in AIS data were used to calculate the rudder angle and ship velocity components, which were then used as training data for a regression model. The accuracy and efficiency of the algorithm were validated by comparing SVR-based estimated hydrodynamic coefficients and the original hydrodynamic coefficients of the Mariner class vessel. The validated SVR algorithm was then applied to estimate the hydrodynamic coefficients for real ships using AIS data. The turning circle test wassimulated from calculated hydrodynamic coefficients and compared with the AIS data. The research results demonstrate the effectiveness of the SVR model in accurately estimating the hydrodynamic coefficients from the AIS data. In conclusion, this study proposes the viability of employing SVR model and AIS data for accurately estimating the hydrodynamic coefficients. It offers a practical approach to ship maneuvering prediction and control in the maritime industry.

• Journal of Positioning, Navigation, and Timing
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• 제12권3호
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• pp.257-269
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• 2023

This paper presents a method for detecting faults in data obtained from the Automatic Identification System (AIS) of surface vessels. The data include latitude, longitude, Speed Over Ground (SOG), and Course Over Ground (COG). We derive two methods that utilize two models: a constant state model and a derivative augmented model. The constant state model incorporates noise variables to account for state changes, while the derivative augmented model employs explicit variables such as first or second derivatives, to model dynamic changes in state. Generally, the derivative augmented model detects faults more promptly than the constant state model, although it is vulnerable to potentially overlooking faults. The effectiveness of this method is validated using AIS data collected at a harbor. The results demonstrate that the proposed approach can automatically detect faults in AIS data, thus offering partial assistance for enhancing navigation safety.

• Asia pacific journal of information systems
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• 제3권2호
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• pp.93-116
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• 1993

This study surveys 212 accounting information systems (AIS) of 85 manufacturing firms by using the research model based on the management process of AIS to figure out the current status and problems of the computing environment and AIS of Korean firms. The analysis of the current status leads to the suggestions to promote the utilization and efficiency of AIS. The level of experiences and education of information system (IS) personnel turns out to be still low. More education is needed to upgrade the IS personnel. AIS users lack in the computer knowledge. The users need more computer education. The analysis on the computerization and information characteristics of the AIS subsystems shows that the computerization is well established in the financial accounting area. On the other hand, the computerization for managerial accounting areas is in its early stage. The managerial accounting systems need be developed to support the managerial decision making effectively. The majority of firms develop the AIS by their own IS teams. When firms use the consulting services in developing AIS, they prefer accounting firms. The majority of firms fail to evaluate the AIS because the evaluation tools are not available. Most firms do not perform the auditing for AIS. It is needed to develop the tool and techniques for evalauation and auditing AIS.

• Asian Journal of Business Environment
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• 제12권3호
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• pp.1-12
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• 2022

Purpose: This study aims to investigate whether AIS data can be used as a supporting indicator or as an initial signal to describe Indonesia's export-import conditions in real-time. Research design, data, and methodology: This study performs several stages of data selection to obtain indicators from AIS that truly reflect export-import activities in Indonesia. Also, investigate the potential of AIS indicators in producing forecasts of the value and volume of Indonesian export-import using conventional statistical methods and machine learning techniques. Results: The six preprocessing stages defined in this study filtered AIS data from 661.8 million messages to 73.5 million messages. Seven predictors were formed from the selected AIS data. The AIS indicator can be used to provide an initial signal about Indonesia's import-export activities. Each export or import activity has its own predictor. Conventional statistical methods and machine learning techniques have the same ability both in forecasting Indonesia's exports and imports. Conclusions: Big data AIS can be used as a supporting indicator as a signal of the condition of export-import values in Indonesia. The right method of building indicators can make the data valuable for the performance of the forecasting model.

• 한국컴퓨터정보학회논문지
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• 제29권3호
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• pp.1-10
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• 2024

해상 운송의 대부분을 차지하고 있는 선박의 경로를 예측하는 연구는 해상의 위험을 사전에 탐지하여 사고를 예방할 수 있다. 도로와 달리 해상에는 신호체계가 따로 존재하지 않고, 교통 관리가 어렵기에 해상 안정성을 위해 선박 경로 예측은 필수적이다. 그러나 선박의 경로 데이터셋의 시간 간격은 통신 장애로 인해 불규칙하다. 본 연구는 이 문제를 해결하기 위해 선박 경로 예측에 적합한 보간법을 사용하여 데이터의 시간 간격을 조정하는 방법을 제시한다. 또한, 선박의 경로를 예측하기 위한 선박 경로 예측 딥러닝 모델을 개발하였다. 본 연구의 모델은 선박의 실시간 경로 정보를 담고 있는 AIS 데이터를 통해 선박의 이동패턴을 파악하여 이후에 위치할 선박의 GPS 좌표를 예측하는 LSTM 모델이다. 본 논문은 선형 보간법을 사용한 데이터 전처리 방법과 선박 경로 예측에 적합한 딥러닝 모델을 제시하고, 실험을 통해 MSE 0.0131, Accuracy 0.9467로 본 논문에서 제시하는 방법의 예측 성능이 우수함을 나타낸다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2014년도 추계학술대회
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• pp.114-116
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• 2014

The interpolation of the missing AIS dynamic data can be used for predicting the lost data of the ship's state which is able to product the valuable information for analyzing and investigating the maritime accidents. The previous research proposed some interpolating methods however there exists some problem, firstly, the interpolated parameters such as COG, SOG, HDG weren't described sufficiently and accurately as in AIS message, secondly, each method is only suitable to some kinds of given AIS data, finally at heavy wind and current area, the parameters of AIS dynamic change quickly in short time, therefore, the modelling of the variation of ship's dynamic based on the physical characteristic is very difficult, in these cases the time-series and numerical method are usually better. This research proposes the other method through numerical analysis which can be suitable for many different kinds of the lost data, parameters are interpolated sufficiently, beside that this model is appropriate to all variation in short time interval. All the given AIS dynamic are regarded as the functions to time, then curves are established for fitting all data. Experiments are carried out to evaluate the performance of this approach, the interpolation results show this approach can be applied well in practice.

• Asia pacific journal of information systems
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• 제32권2호
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• pp.435-459
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• 2022

The accounting literature abounds with many studies concerning the organizational and technical aspects of the AIS to simulate progress in the business environment. However, few studies have focused on the role of individual factors in overcoming resistance to change and maximizing the value of using the system. Therefore, this study aims to shed light on user beliefs by evaluating the factors that affect the use of the AIS using a developed TAM. A total of 132 subjects participated in this study, in which the questionnaire was used as a data collection tool and AMOS was used to test the model. The results showed that subjective norm, training and experience were the most important previous factors that affect the perceptual factors represented in usefulness, ease of use and the inevitability of change, which all had an impact on the continuance intention to use the AIS among users in Algerian firms. This study shed light on the importance of assessing individual factors rather than focusing only on the ways to develop AIS or researching for new technologies and the costs of this investment because this will increase the chances of success in using the system.

• 디지털융복합연구
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• 제18권6호
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• pp.245-253
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• 2020

연구의 목적은 중소기업 회계정보시스템 수준과 환경요인을 파악해 보고 또한, 회계정보시스템 수준이 시스템 성과에 영향을 미치는지를 분석해 보고자 하였다. 연구방법은 Nolan의 성장단계모형을 이용하여 AIS 수준을 측정하였으며, 상황요인, AIS 수준 및 성과간의 영향요인 검증에서는 회귀분석모형을 이용하여 검증하였다. 연구결과를 요약하면 다음과 같다. 회계정보시스템의 수준 측정에 있어서는 4단계인 통합단계에 있는 것으로 조사되었으며, 회계정보시스템의 수준에 미치는 영향요인 분석에서는 환경의 불확실성에 절대적으로 영향을 받는 것으로 나타났다. 또한, 회계정보시스템 수준이 시스템성과에 미치는 영향분석에서는 회계정보시스템 수준이 시스템 만족도와 이용도에 부분적으로 영향을 미치는 것으로 조사되었다. 회계정보시스템의 수준을 측정해 보고 관련 환경요인과 시스템 성과에 미치는 영향관계를 검증해 보았다는데 연구의 의의가 있으며, 향후에는 상황요인 중 고려하지 못 요인들(기업문화, 경영전략, 정보기술구조 등)을 검증해 볼 필요가 있다.

• 한국음향학회지
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• 제37권3호
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• pp.129-138
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• 2018

선박 통행이 잦은 항만 및 연안 주변지역은 1 kHz 이하의 저주파 대역에서 선박소음이 수중소음에 지배적으로 영향을 미친다. 본 논문에서는 선박자동식별장치(Automatic Identification System, AIS)에서 관측된 선박의 항해정보를 이용하여 수중 선박소음을 추정하는 모델링 방안을 제시한다. 선박소음 모델링을 목적으로 AIS를 이용하여 제주 남부 해역에서 활동하는 선박들의 항행정보를 관측하였고, 모델링된 선박소음의 결과 검증을 위해 실험해역에 수중청음기를 설치하여 수중소음을 측정하였다. AIS 데이터를 이용하여 선박소음준위를 모델링하여 측정된 수중소음과 비교한 결과 시간에 따른 소음준위의 변동 특성이 유사함을 확인하였고, 오차가 발생되는 원인에 대해 토의하였다. 본 연구를 통해 AIS 데이터를 이용하여 선박소음준위를 5 dB 오차 범위에서 추정이 가능함을 확인하였다.