• East Asian Journal of Business Economics (EAJBE)
• /
• v.3 no.3
• /
• pp.14-26
• /
• 2015

A wind speed forecast is a crucial and sophisticated task in a wind farm for planning turbines and corresponds to an estimate of the expected production of one or more wind turbines in the near future. By production is often meant available power for wind farm considered (with units KW or MW depending on both the wind speed and direction. Such forecasts can also be expressed in terms of energy, by integrating power production over each time interval. In this study, we technically focused on mathematical modeling of wind speed and direction forecast based on locally data set gathered from Aghdasiyeh station in Tehran. The methodology is set on using most common techniques derived from literature review. Hence we applied the most sophisticated forecasting methods to embed seasonality, trend, and irregular pattern for wind speed as an angular variables. Through this research, we carried out the most common techniques such as the Box and Jenkins family, VARMA, the component method, the Weibull function and the Fourier series. Finally, the best fit for each forecasting method validated statistically based on white noise properties and the final comparisons using residual standard errors and mean absolute deviation from real data.

• Journal of applied mathematics & informatics
• /
• v.41 no.5
• /
• pp.1129-1143
• /
• 2023

Social media platforms have become an integral part of our daily lives, and they generate vast amounts of data that can be analyzed for various purposes. However, the quality of the data obtained from social media is often questionable due to factors such as noise, bias, and incompleteness. Enhancing data quality is crucial to ensure the reliability and validity of the results obtained from such data. This paper proposes an enhanced decision-making framework based on Business Decision Management Systems (BDMS) that addresses these challenges by incorporating a data quality enhancement component. The framework includes a backtracking method to improve plan failures and risk-taking abilities and a steep optimized strategy to enhance training plan and resource management, all of which contribute to improving the quality of the data. We examine the efficacy of the proposed framework through research data, which provides evidence of its ability to increase the level of effectiveness and performance by enhancing data quality. Additionally, we demonstrate the reliability of the proposed framework through simulation analysis, which includes true positive analysis, performance analysis, error analysis, and accuracy analysis. This research contributes to the field of business intelligence by providing a framework that addresses critical data quality challenges faced by organizations in decision-making environments.

• The Journal of Society for e-Business Studies
• /
• v.20 no.4
• /
• pp.41-59
• /
• 2015

Information systems has been developed and used in various business area, therefore there are abundance of history data (log data) stored, and subsequently, it is required to analyze those log data. Previous studies have been focusing on the discovering of relationship between events and no identification of anomaly instances. Previously, anomaly instances are treated as noise and simply ignored. However, this kind of anomaly instances can occur repeatedly. Hence, a new methodology to detect the anomaly instances is needed. In this paper, we propose a methodology of LAPID (Local Anomaly Process Instance Detection) for discriminating an anomalous process instance from the log data. We specified a distance metric from the activity relation matrix of each instance, and use it to detect API (Anomaly Process Instance). For verifying the suggested methodology, we discovered characteristics of exceptional situations from log data. To demonstrate our proposed methodology, we performed our experiment on real data from a domestic port terminal.

• International Area Studies Review
• /
• v.12 no.3
• /
• pp.195-216
• /
• 2008

It is generally accepted that the momentum strategies are effective in the short-term, and the contrarian strategies are profitable in the long run in major stock markets in the world. In Korean market, however, the contrarian is considered effective investment strategy both in the short- and long-term. We investigate whether this is true after 1999, and try to find out the reasons for this phenomena. We found that the contrarian strategies are still effective. Foreign investors showed consistent investment behavior both in Korean and abroad: they followed momentum in the short-tem, and contrarian in the longer-term. The individual investors, who are thought to be noise trader, showed different behavior. They followed contrarian strategies both in the short-and long-term. The reason that the contrarian is observed in Korean market regardless of the investment horizon is thought to be the irrtional behavior of individual investors.

• Informatization Policy
• /
• v.29 no.4
• /
• pp.43-66
• /
• 2022

With the development of artificial intelligence technology, competition for artificial intelligence technology patents around the world is intensifying. During the period 2000 ~ 2021, artificial intelligence technology patent applications at the US Patent and Trademark Office have been steadily increasing, and the growth rate has been steeper since the 2010s. As a result of analyzing Korea's artificial intelligence technology competitiveness through patent indices, it is evaluated that patent activity, impact, and marketability are superior in areas such as auditory intelligence and visual intelligence. However, compared to other countries, overall Korea's artificial intelligence technology patents are good in terms of activity and marketability, but somewhat inferior in technological impact. While noise canceling and voice recognition have recently decreased as topics for artificial intelligence, growth is expected in areas such as model learning optimization, smart sensors, and autonomous driving. In the case of Korea, efforts are required as there is a slight lack of patent applications in areas such as fraud detection/security and medical vision learning.

• Journal of Intelligence and Information Systems
• /
• v.28 no.4
• /
• pp.329-346
• /
• 2022

Recently, as the market for short form videos (Instagram, TikTok, YouTube) on social media has gradually increased, research using them is actively being conducted in the artificial intelligence field. A representative research field is Video to Shop, which detects fashion products in videos and searches for product images. In such a video-based artificial intelligence model, product features are extracted using convolution operations. However, due to the limitation of computational resources, extracting features using all the frames in the video is practically impossible. For this reason, existing studies have improved the model's performance by sampling only a part of the entire frame or developing a sampling method using the subject's characteristics. In the existing Video to Shop study, when sampling frames, some frames are randomly sampled or sampled at even intervals. However, this sampling method degrades the performance of the fashion product search model while sampling noise frames where the product does not exist. Therefore, this paper proposes a sampling method MF (Missing Fashion items on frame) sampler that removes noise frames and improves the performance of the search model. MF sampler has improved the problem of resource limitations by developing a keyframe mechanism. In addition, the performance of the search model is improved through noise frame removal using the noise detection model. As a result of the experiment, it was confirmed that the proposed method improves the model's performance and helps the model training to be effective.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.2775-2781
• /
• 2011

Urban Transit Train Radio is Radio Communication system that is used official business as leading motive for train safety running among the train crew and the central control center and drive-caring-chamber on main line and branch line. This system is operated that organizes talking path on handset of terminal after the train crew receives audio and understands call voice on speaker of terminal at calling the train of the central control center. When the central control center calls the specific train uses all call radio form, the train crew doesn't recognize the call cause the train situation, noise and action as train control. So there is a delay response cause reset call at the central control center. This research discusses the management of subway radio system and describes the call the train system that recognize train call number of all-call used between the central control center and the train crew.

• ETRI Journal
• /
• v.34 no.6
• /
• pp.879-884
• /
• 2012

When the number of users is finite, the performance improvement of the orthogonal random beamforming (ORBF) scheme is limited in high signal-to-noise ratio regions. In this paper, to improve the performance of the ORBF scheme, the user set and transmit power allocation are jointly determined to maximize sum rate under the total transmit power constraint. First, the transmit power allocation problem is expressed as a function of a given user set. Based on this expression, the optimal user set with the maximum sum rate is determined. The suboptimal procedure is also presented to reduce the computational complexity, which separates the user set selection procedure and transmit power allocation procedure.

• International Journal of Fluid Machinery and Systems
• /
• v.2 no.1
• /
• pp.92-101
• /
• 2009

The purpose of this paper is to gain a greater understanding of the performance of practical wind turbine generating systems with differing output power controllers and controlling means for wind turbine speed. Subjected wind turbines, both equipped with an asynchronous power generator, are located at two sites and are defined as wind turbine A and wind turbine B in this study, respectively. Their performance differences are examined by measuring wind speed and electric parameters. The study suggests that both wind turbines have a clear linkage between current and output power fluctuations. Comparison of the fluctuations to wind speed fluctuation, although they are triggered primarily by wind speed fluctuation, clearly indicates the specific behaviors inherent to the respective turbine control mechanisms.

• Journal of Korea Port Economic Association
• /
• v.20 no.2
• /
• pp.101-130
• /
• 2004

Such Hinterland in New Busan-Jinhae Port are so placed as to do harm to their surrounding residential areas due to traffic, noise and dirt, etc. according to the current plan. So they are likely to fail to serve as harbors and residential districts. Because this is responsible for a conflict between harbors and urban functions, plans for the use of such areas should be well planned enough to achieve win-win results by getting rid of a conflict between the harbors and urban functions by creating manufactural and industrial complexes and green parks close to harbor logistics, by consolidating the functions of the cities through exchanges, commercial business and educational facilities and by adding comfort facilities at the hinterland of Ungdong and Myeongji.