• Title/Summary/Keyword: Data Optimization

Search Result 3,487, Processing Time 0.037 seconds

AutoML and Artificial Neural Network Modeling of Process Dynamics of LNG Regasification Using Seawater (해수 이용 LNG 재기화 공정의 딥러닝과 AutoML을 이용한 동적모델링)

  • Shin, Yongbeom;Yoo, Sangwoo;Kwak, Dongho;Lee, Nagyeong;Shin, Dongil
    • Korean Chemical Engineering Research
    • /
    • v.59 no.2
    • /
    • pp.209-218
    • /
    • 2021
  • First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

In-feed organic and inorganic manganese supplementation on broiler performance and physiological responses

  • de Carvalho, Bruno Reis;Ferreira Junior, Helvio da Cruz;Viana, Gabriel da Silva;Alves, Warley Junior;Muniz, Jorge Cunha Lima;Rostagno, Horacio Santiago;Pettigrew, James Eugene;Hannas, Melissa Izabel
    • Animal Bioscience
    • /
    • v.34 no.11
    • /
    • pp.1811-1821
    • /
    • 2021
  • Objective: A trial was conducted to investigate the effects of supplemental levels of Mn provided by organic and inorganic trace mineral supplements on growth, tissue mineralization, mineral balance, and antioxidant status of growing broiler chicks. Methods: A total of 500 male chicks (8-d-old) were used in 10-day feeding trial, with 10 treatments and 10 replicates of 5 chicks per treatment. A 2×5 factorial design was used where supplemental Mn levels (0, 25, 50, 75, and 100 mg Mn/kg diet) were provided as MnSO4·H2O or MnPro. When Mn was supplied as MnPro, supplements of zinc, copper, iron, and selenium were supplied as organic minerals, whereas in MnSO4·H2O supplemented diets, inorganic salts were used as sources of other trace minerals. Performance data were fitted to a linearbroken line regression model to estimate the optimal supplemental Mn levels. Results: Manganese supplementation improved body weight, average daily gain (ADG) and feed conversion ratio (FCR) compared with chicks fed diets not supplemented with Mn. Manganese in liver, breast muscle, and tibia were greatest at 50, 75, and 100 mg supplemental Mn/kg diet, respectively. Higher activities of glutathione peroxidase and superoxide dismutase (total-SOD) were found in both liver and breast muscle of chicks fed diets supplemented with inorganic minerals. In chicks fed MnSO4·H2O, ADG, FCR, Mn balance, and concentration in liver were optimized at 59.8, 74.3, 20.6, and 43.1 mg supplemental Mn/kg diet, respectively. In MnPro fed chicks, ADG, FCR, Mn balance, and concentration in liver and breast were optimized at 20.6, 38.0, 16.6, 33.5, and 62.3 mg supplemental Mn/kg, respectively. Conclusion: Lower levels of organic Mn were required by growing chicks for performance optimization compared to inorganic Mn. Based on the FCR, the ideal supplemental levels of organic and inorganic Mn in chick feeds were 38.0 and 74.3 mg Mn/kg diet, respectively.

Detection and Identification of Moving Objects at Busy Traffic Road based on YOLO v4 (YOLO v4 기반 혼잡도로에서의 움직이는 물체 검출 및 식별)

  • Li, Qiutan;Ding, Xilong;Wang, Xufei;Chen, Le;Son, Jinku;Song, Jeong-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.21 no.1
    • /
    • pp.141-148
    • /
    • 2021
  • In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

Introduction of Inverse Analysis Model Using Geostatistical Evolution Strategy and Estimation of Hydraulic Conductivity Distribution in Synthetic Aquifer (지구통계학적 진화전략 역산해석 기법의 소개 및 가상 대수층 수리전도도 분포 예측에의 적용)

  • Park, Eungyu
    • Economic and Environmental Geology
    • /
    • v.53 no.6
    • /
    • pp.703-713
    • /
    • 2020
  • In many geological fields, including hydrogeology, it is of great importance to determine the heterogeneity of the subsurface media. This study briefly introduces the concept and theory of the method that can estimate the hydraulic properties of the media constituting the aquifer, which was recently introduced by Park (2020). After the introduction, the method was applied to the synthetic aquifer to demonstrate the practicality, from which various implications were drawn. The introduced technique uses a global optimization technique called the covariance matrix adaptation evolution strategy (CMA-ES). Conceptually, it is a methodology to characterize the aquifer heterogeneity by assimilating the groundwater level time-series data due to the imposed hydraulic stress. As a result of applying the developed technique to estimate the hydraulic conductivity of a hypothetical aquifer, it was confirmed that a total of 40000 unknown values were estimated in an affordable computational time. In addition, the results of the estimates showed a close numerical and structural similarity to the reference hydraulic conductivity field, confirming that the quality of the estimation by the proposed method is high. In this study, the developed method was applied to a limited case, but it is expected that it can be applied to a wider variety of cases through additional development of the method. The development technique has the potential to be applied not only to the field of hydrogeology, but also to various fields of geology and geophysics. Further development of the method is currently underway.

Analysis on General High School Locations for Opening Common Curriculum Courses based on High School Credit System: Focusing on Seoul (고교학점제에 따른 일반고의 공동교육과정 과목 개설학교 입지 분석: 서울시를 중심으로)

  • Kim, Sung-Yeun
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.22 no.3
    • /
    • pp.148-159
    • /
    • 2021
  • This study focused on searching for optimal locations for general high schools by considering the minimum move distance and the maximum student capacity upon starting a common curriculum based on a high school credit system by taking Seoul as an illustration. The main results were as follows. First, the results from P-median showed that the students' average move distance was below 625m when more than 30% of general high schools offer the common curriculum courses. In addition, the results from MCLP indicated that it was possible to hold all the students. Second, although all the universities located in Seoul open the common curriculum courses, it would not be available to hold all students. On the other hand, when more than 20% of the universities open the courses, MCLP indicated that it was possible to hold the same capacity. In addition, the Office of Education should support moving to the universities offering courses for students affiliated with high schools located in the southeastern area of Seoul and in poor transportation areas. It is expected that by suggesting a problem solving framework regarding space with a spatial optimization method, the study results can be used as a basic data for selecting schools offering common curriculum courses.

A Study on the Optimal Setting of Large Uncharged Hole Boring Machine for Reducing Blast-induced Vibration Using Deep Learning (터널 발파 진동 저감을 위한 대구경 무장약공 천공 장비의 최적 세팅조건 산정을 위한 딥러닝 적용에 관한 연구)

  • Kim, Min-Seong;Lee, Je-Kyum;Choi, Yo-Hyun;Kim, Seon-Hong;Jeong, Keon-Woong;Kim, Ki-Lim;Lee, Sean Seungwon
    • Explosives and Blasting
    • /
    • v.38 no.4
    • /
    • pp.16-25
    • /
    • 2020
  • Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

Shape and Spacing Effects on Curvy Twin Sail for Autonomous Sailing Drone (무인 해상 드론용 트윈 세일의 형태와 간격에 관한 연구)

  • Pham, Minh-Ngoc;Kim, Bu-Gi;Yang, Changjo
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.26 no.7
    • /
    • pp.931-941
    • /
    • 2020
  • There is a growing interest this paper for ocean sensing where autonomous vehicles can play an essential role in assisting engineers, researchers, and scientists with environmental monitoring and collecting oceanographic data. This study was conducted to develop a rigid sail for the autonomous sailing drone. Our study aims to numerically analyze the aerodynamic characteristics of curvy twin sail and compare it with wing sail. Because racing regulations limit the sail shape, only the two-dimensional geometry (2D) was open for an optimization. Therefore, the first objective was to identify the aerodynamic performance of such curvy twin sails. The secondary objective was to estimate the effect of the sail's spacing and shapes. A viscous Navier-Stokes flow solver was used for the numerical aerodynamic analysis. The 2D aerodynamic investigation is a preliminary evaluation. The results indicated that the curvy twin sail designs have improved lift, drag, and driving force coefficient compared to the wing sails. The spacing between the port and starboard sails of curvy twin sail was an important parameter. The spacing is 0.035 L, 0.07 L, and 0.14 L shows the lift coefficient reduction because of dramatically stall effect, while flow separation is improved with spacing is 0.21 L, 0.28 L, and 0.35 L. Significantly, the spacing 0.28 L shows the maximum high pressure at the lower area and the small low pressure area at leading edges. Therefore, the highest lift was generated.

A study on the 3-step classification algorithm for the diagnosis and classification of refrigeration system failures and their types (냉동시스템 고장 진단 및 고장유형 분석을 위한 3단계 분류 알고리즘에 관한 연구)

  • Lee, Kangbae;Park, Sungho;Lee, Hui-Won;Lee, Seung-Jae;Lee, Seung-hyun
    • Journal of the Korea Convergence Society
    • /
    • v.12 no.8
    • /
    • pp.31-37
    • /
    • 2021
  • As the size of buildings increases due to urbanization due to the development of industry, the need to purify the air and maintain a comfortable indoor environment is also increasing. With the development of monitoring technology for refrigeration systems, it has become possible to manage the amount of electricity consumed in buildings. In particular, refrigeration systems account for about 40% of power consumption in commercial buildings. Therefore, in order to develop the refrigeration system failure diagnosis algorithm in this study, the purpose of this study was to understand the structure of the refrigeration system, collect and analyze data generated during the operation of the refrigeration system, and quickly detect and classify failure situations with various types and severity . In particular, in order to improve the classification accuracy of failure types that are difficult to classify, a three-step diagnosis and classification algorithm was developed and proposed. A model based on SVM and LGBM was presented as a classification model suitable for each stage after a number of experiments and hyper-parameter optimization process. In this study, the characteristics affecting failure were preserved as much as possible, and all failure types, including refrigerant-related failures, which had been difficult in previous studies, were derived with excellent results.

Evaluation Research on the Protection and Regeneration of the Urban Historical and Cultural District of Pingjiang Road, Suzhou, China (중국 쑤저우 평강로 도시역사문화거리 보존 및 재생사업 평가연구)

  • Geng, Li;Yoon, Ji-Young
    • The Journal of the Korea Contents Association
    • /
    • v.21 no.5
    • /
    • pp.561-580
    • /
    • 2021
  • This study analyses the historical and cultural streets at Pinggang Road in the city of Suzhou, by understanding the development and conservation of the area, and uses the following ways to investigate its development, re-organization, and current state. This paper comprehensively compares, collates and investigates 4 different historical and cultural areas in Insadong and Samcheong-dong in South Korea, and South Luogu Lane in China. From initial research and analysis, this paper gathers the cultural, economic, and societal perspectives as non-physical measures, and spatial structure, road structure, and building maintenance as physical factor framework. It is significant in that it can provide an evaluation model for the preservation and regeneration of historical and cultural streets by presenting the viewpoint of complex development of non-physical and physical elements in Pyeonggang-ro. In addition, it is necessary to conduct optimization and specific research on insufficient areas, such as maintenance and development of programs and signature systems for visitors, and continuous development of historical and cultural network platforms by combining on-site surveys. Basic data should be provided for reference on the street.

Regionalization of rainfall-runoff model parameters based on the correlation of regional characteristic factors (지역특성인자의 상호연관성을 고려한 강우-유출모형 매개변수 지역화)

  • Kim, Jin-Guk;Sumyia, Uranchimeg;Kim, Tae-Jeong;Kwon, Hyun-Han
    • Journal of Korea Water Resources Association
    • /
    • v.54 no.11
    • /
    • pp.955-968
    • /
    • 2021
  • A water resource plan is routinely based on a natural flow and can be estimated using observed streamflow data or a long-term continuous rainfall-runoff model. However, the watershed with the natural flow is very limited to the upstream area of the dam. In particular, for the ungauged watershed, a rainfall-runoff model is established for the gauged watershed, and the model is then applied to the ungauged watershed by transferring the associated parameters. In this study, the GR4J rainfall-runoff model is mainly used to regionalize the parameters that are estimated from the 14 dam watershed via an optimization process. In terms of optimizing the parameters, the Bayesian approach was applied to consider the uncertainty of parameters quantitatively, and a number of parameter samples obtained from the posterior distribution were used for the regionalization. Here, the relationship between the estimated parameters and the topographical factors was first identified, and the dependencies between them are effectively modeled by a Copula function approach to obtain the regionalized parameters. The predicted streamflow with the use of regionalized parameters showed a good agreement with that of the observed with a correlation of about 0.8. It was found that the proposed regionalized framework is able to effectively simulate streamflow for the ungauged watersheds by the use of the regionalized parameters, along with the associated uncertainty, informed by the basin characteristics.