• 해양환경안전학회지
• /
• 제25권7호
• /
• pp.851-857
• /
• 2019

본 연구는 운항선의 운항 빅데이터를 활용하여 머신러닝 기법의 선박 마력 예측에 관한 것이다. 현재 신조선에는 ISO15016법을 이용하여 외부환경 요인에 대하여 수식을 통해 저항을 예측하나 관련 계산식이 복잡하고 요구하는 입력변수들이 많아 운항하는 실선 적용에 많은 시간과 비용이 필요하다. 본 연구에서는 최근 예측, 인식 등에서 우수한 성능을 보이는 SVM(Support Vector Machine) 알고리즘을 이용하여 우수한 성능의 선박 출력 예측이 가능한 모델을 제안한다. 제안 예측 모델은 실선 운항 빅데이터만 확보된다면 ISO15016법 대비 우수한 성능의 예측이 가능한 장점이 있다. 본 연구에서는 178K 벌크캐리어의 운항 DATA를 활용하여 ISO15016 기법과 본 연구에서 제안하는 SVM 알고리즘 기반의 마력해석법을 비교하여 ISO15016의 단점인 선박 모델 데이터 준비 부분을 줄이고 부정확한 마력 예측 성능을 개선하였다.

• 수산해양기술연구
• /
• 제39권4호
• /
• pp.298-304
• /
• 2003

In this paper a free-form hull design program and performance prediction program for planing boat is introduced. This program enables the designer to do complex geometric hull shape design on a personal computer and accurately to predict power requirements for a given loading and velocity. For a free form design, Bezier curve model is adopted as a basic representation tool of curves and surfaces, and this program has versatile functions to do fairing jobs with a convenient graphical user interface. After creating a hull form the geometric data is provided in a manner compatible with a variety of analysis tools including 'Motion Analysis(by Zarnick)' for prediction of motion characteristics in regular waves, 'Running Attitude (by Savitsky)' for prediction of the running attitude and required power.

• 대한임베디드공학회논문지
• /
• 제18권2호
• /
• pp.59-65
• /
• 2023

Currently, polysomnography is essential to diagnose sleep-related breathing disorders. However, there are several disadvantages to polysomnography, such as the requirement for multiple sensors and a long reading time. In this paper, we propose a system for predicting the severity of sleep-related breathing disorders at home utilizing measurable elements in a wearable device. To predict severity, the variables were refined through a three-step variable selection process, and the refined variables were used as inputs into three machine-learning models. As a result of the study, random forest models showed excellent prediction performance throughout. The best performance of the model in terms of F1 scores for the three threshold criteria of 5, 15, and 30 classified as the AHI index was about 87.3%, 90.7%, and 90.8%, respectively, and the maximum performance of the model for the three threshold criteria classified as the RDI index was approx 79.8%, 90.2%, and 90.1%, respectively.

• Structural Engineering and Mechanics
• /
• 제82권4호
• /
• pp.445-458
• /
• 2022

Some of the control systems used in engineering structures that use sensors and decision systems have some time delay reducing efficiency of the control system or even might make it unstable. In this research, in addition to considering the effect of the time delay in vibration control process, predictive control is used to compensate the time delay. A semi-active vibration control approach with the help of magneto-rheological dampers is implemented. In addition to using fuzzy inference system to determine the appropriate control voltage for MR damper, structural behavior prediction system and specifying future responses are also used such that the time delays occurring within control process are overcome. For this purpose, determination of prediction horizon is conducted for one, five, and ten steps ahead for single degree of freedom structures with periods ranging from 0.1 to 4 seconds, subjected to twenty earthquake excitations. The amount of time delay applied to the control system is 0.1 seconds. The obtained results indicate that for 0.1 second time delay, average prediction error values compared to the case without time delay is 3.47 percent. Having 0.1 second time delay in a semi-active control system reduces its efficiency by 11.46 percent; while after providing the control system with structure behavior prediction, the difference in the results for the control system without time delay is just 1.35 percent on average; indicating a 10.11 percent performance improvement for the control system.

• 농업과학연구
• /
• 제38권4호
• /
• pp.761-767
• /
• 2011

The objective of this study was to predict total bacteria count of pork meats by using the portable electronic nose systems developed throughout two stages of the prototypes. Total bacteria counts were measured for pork meats stored at $4^{\circ}C$ for 21days and compared with the signals of the electronic nose systems. PLS(Partial least square), PCR (Principal component regression), MLR (Multiple linear regression) models were developed for the prediction of total bacteria count of pork meats. The coefficient of determination ($R_p{^2}$) and root mean square error of prediction (RMSEP) for the models were 0.789 and 0.784 log CFU/g with the 1st system for the pork loin, 0.796 and 0.597 log CFU/g with the 2nd system for the pork belly, and 0.661 and 0.576 log CFU/g with the 2nd system for the pork loin respectively. The results show that the developed electronic system has potential to predict total bacteria count of pork meats.

• Nuclear Engineering and Technology
• /
• 제55권7호
• /
• pp.2642-2649
• /
• 2023

A real-time unmeasured dynamic response prediction process for the nuclear power plant pressure pipeline is proposed and its performance is tested in the test-loop system (KAERI). The aim of the process is to predict unmeasurable or unreachable dynamic responses such as acceleration, velocity, and displacement by using a limited amount of directly measured physical responses. It is achieved by combining a well-constructed finite element model and robust inverse force identification algorithm. The pressure pipeline system is described by using the displacement-pressure vibro-acoustic formulation to consider fully filled liquid effect inside the pipeline structure. A robust multiphysics modal projection technique is employed for the real-time sensor synchronized prediction. The inverse force identification method is also derived and employed by using Bathe's time integration method to identify the full-field responses of the target system from the modal domain computation. To validate the performance of the proposed process, an experimental test is extensively performed on the nuclear power plant pressure pipeline test-loop under operation conditions. The results show that the proposed identification process could well estimate the unmeasured acceleration in both frequency and time domain faster than 32,768 samples per sec.

• Current Optics and Photonics
• /
• 제5권6호
• /
• pp.641-651
• /
• 2021

To handle the servo delay in a real-time adaptive optics system, a linear subspace system identification algorithm was employed to model the system, and the accuracy of the system identification was verified by numerical calculation. Experimental verification was conducted in a real test bed system. Through analysis and comparison of the experimental results, the convergence can be achieved only 200 times with prediction and 300 times without prediction. After the wavefront peak-to-valley value converges, its mean values are 0.27, 4.27, and 10.14 ㎛ when the communication distances are 1.2, 4.5, and 10.2 km, respectively. The prediction algorithm can effectively improve the convergence speed of the peak-to-valley value and improve the free-space optical communication performance.

• 한국태양에너지학회 논문집
• /
• 제37권1호
• /
• pp.25-38
• /
• 2017

Climate change and environmental pollution are becoming serious due to the use of fossil energy. For this reason, renewable energy systems are increasing, especially photovoltaic systems being more popular. The photovoltaic system has characteristics that are affected by ambient weather conditions such as insolation, outside temperature, wind speed. Particularly, it has been confirmed that the performance of the photovoltaic system decreases as the module temperature increases. In order to grasp the influence of the module temperature in advance, several researchers have proposed the prediction models on the module temperature. In this paper, we predicted the module temperature using the aforementioned prediction model on the basis of the weather conditions in Incheon, South Korea during July and August. The influence of weather conditions (i.e. insolation, outside temperature, and wind speed) on the accuracy of the prediction models was also evaluated using the standard statistical metrics such as RMSE, MAD, and MAPE. The results show that the prediction accuracy is reduced by 3.9 times and 1.9 times as the insolation and outside temperature increased respectively. On the other hand, the accuracy increased by 6.3 times as the wind speed increased.

• 한국항해항만학회지
• /
• 제30권2호
• /
• pp.125-130
• /
• 2006

Waves, which are the main source of ship motions in a seaway, considerably affect the performance of a ship. The study of waves and their impact on ship motions within harbors is an important aspect of the design and operation of harbors. The prediction of incoming groups of waves is particularly important for evaluating ship motion within a harbor. Such a prediction makes it possible to evaluate ship safety more accurately. The wave transformation model reported here is applied to actual ports based on Boussinesq wave equations both non-linear and dispersive wave processes be considered in order to capture physical effects such as wave shoaling, refractions, reflection and diffraction in variable depth environments. The prediction of incoming groups of waves is particularly important for evaluating ship motion within a harbor, Such a prediction makes it possible to evaluate ship safety more accurately and provide safe wave informations for navigation. Furthermore, a wave information support system is proposed for entering ships as one technique for improving the safety of ship operations. This system predicts the run of waves and reduces the danger by identifying the most dangerous point near the harbor entrance at the small wave groups.

• 한국정보통신학회논문지
• /
• 제1권1호
• /
• pp.77-83
• /
• 1997

본 논문에서는 현재 디지털 이동통신 시스템에서 운용되고 있는 QCELP(Qualcomm Code Excited Linear Predictor) 음성부호화 방식과 향후 IMT-2000 (International Mobile Telecommunications 2000) 등의 시스템에서 사용 예정인 CS-ACELP(Conjugate Structure Algebraic Code Excited Linear Prediction) 음성부호화 방식과의 성능을 비교한다. 특히 무선 채널을 사용하는 이동통신환경의 특징인 채널에러로 인한 음성부호화기의 성능을 비교함으로써 채널에러에 강인한 음성부호화 알고리즘 설계에 대한 고찰을 유도한다.