• Title/Summary/Keyword: system uncertainty

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The Effects of Depreciation Methods on Investment Motivation for Solar Photovoltaic Systems (태양광 설비투자에 대한 제도적 유인방안 연구: 감가상각법의 경제적 효과 분석)

  • Kim, Kyung Nam
    • New & Renewable Energy
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    • v.16 no.4
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    • pp.65-75
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    • 2020
  • The value of tangible assets depreciates over their useful life and this depreciation should be adequately reflected in any tax or financial reports. However, the method used to calculate depreciation can impact the financial performance of solar projects due to the time value of money. Korean tax law stipulates only one method for calculating the depreciation of solar photovoltaic facilities: the straight-line method. Conversely, USA's tax law accepts other depreciation methods as solar incentives, including the modified accelerated cost recovery system (MACRS) and Bonus depreciation method. This paper compares different depreciation methods in the financial analysis of a 10 MW solar system to determine their effect on the financial results. When depreciation was calculated utilizing the MACRS and Bonus depreciation method, the internal rate of return (IRR) was 10.9% and 16.4% higher, respectively, than when the Korean straight-line depreciation method was used. Additionally, the increased IRR resulting from the use of the two US methods resulted in a 20.5% and 27.4% higher net present value, respectively. This shows that changing the depreciation calculation method can redistribute the tax amount during the project period, thereby increasing the discounted cash flow of the solar project. In addition to increasing profitability, USA's depreciation methods alleviate the uncertainty of solar projects and provide more flexibility in project financing than the Korean method. These results strongly suggest that Korean tax law could greatly benefit from adopting USA's depreciation methods as an effective incentive scheme.

Major Watershed Characteristics Influencing Spatial Variability of Stream TP Concentration in the Nakdong River Basin (낙동강 유역에서 하천 TP 농도의 공간적 변동성에 영향을 미치는 주요 유역특성)

  • Seo, Jiyu;Won, Jeongeun;Choi, Jeonghyeon;Kim, Sangdan
    • Journal of Korean Society on Water Environment
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    • v.37 no.3
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    • pp.204-216
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    • 2021
  • It is important to understand the factors influencing the temporal and spatial variability of water quality in order to establish an effective customized management strategy for contaminated aquatic ecosystems. In this study, the spatial diversity of the 5-year (2015 - 2019) average total phosphorus (TP) concentration observed in 40 Total Maximum Daily Loads unit-basins in the Nakdong River watershed was analyzed using 50 predictive variables of watershed characteristics, climate characteristics, land use characteristics, and soil characteristics. Cross-correlation analysis, a two-stage exhaustive search approach, and Bayesian inference were applied to identify predictors that best matched the time-averaged TP. The predictors that were finally identified included watershed altitude, precipitation in fall, precipitation in winter, residential area, public facilities area, paddy field, soil available phosphate, soil magnesium, soil available silicic acid, and soil potassium. Among them, it was found that the most influential factors for the spatial difference of TP were watershed altitude in watershed characteristics, public facilities area in land use characteristics, and soil available silicic acid in soil characteristics. This means that artificial factors have a great influence on the spatial variability of TP. It is expected that the proposed statistical modeling approach can be applied to the identification of major factors affecting the spatial variability of the temporal average state of various water quality parameters.

A Mixed-Integer Programming Model for Effective Distribution of Relief Supplies in Disaster (재난 구호품의 효과적 분배를 위한 혼합정수계획 모형)

  • Kim, Heungseob
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.1
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    • pp.26-36
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    • 2021
  • The topic of this study is the field of humanitarian logistics for disaster response. Many existing studies have revealed that compliance with the golden time in response to a disaster determines the success or failure of relief activities, and logistics costs account for 80% of the disaster response cost. Besides, the agility, responsiveness, and effectiveness of the humanitarian logistics system are emphasized in consideration of the disaster situation's characteristics, such as the urgency of life-saving and rapid environmental changes. In other words, they emphasize the importance of logistics activities in disaster response, which includes the effective and efficient distribution of relief supplies. This study proposes a mathematical model for establishing a transport plan to distribute relief supplies in a disaster situation. To determine vehicles' route and the amount of relief for cities suffering a disaster, it mainly considers the urgency, effectiveness (restoration rate), and uncertainty in the logistics system. The model is initially developed as a mixed-integer nonlinear programming (MINLP) model containing some nonlinear functions and transform into a Mixed-integer linear programming (MILP) model using a logarithmic transformation and piecewise linear approximation method. Furthermore, a minimax problem is suggested to search for breakpoints and slopes to define a piecewise linear function that minimizes the linear approximation error. A numerical experiment is performed to verify the MILP model, and linear approximation error is also analyzed in the experiment.

Future Development Plans for the Next 60 Years of the Korean Meteorological Society (한국기상학회 향후 60년을 향한 미래 발전 방안)

  • Ki-Hong Min;June-Yi Lee;Seon-Ki Park;Kyung-Ja Ha;Yun Hong;Yongsoek Seo
    • Atmosphere
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    • v.33 no.2
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    • pp.297-306
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    • 2023
  • Celebrating its 60th anniversary, this study suggests the future vision of the Korean Meteorological Society (KMS) for the next 60 years. The vision is "to advance atmospheric science and technology that contributes to human society as well as protect people from not only climate change risks but also weather, climate, and environmental disasters". Based on the suggestions from its members, this study proposes the KMS future development plan as follows. The first plan is to strengthen in leading the development and growth of atmospheric sciences in Korea, especially to improve weather, climate, and environment forecasts and to reduce uncertainty in future climate projections. The second is to enhance interaction not only among its members in academy, Korea Meteorological Administration and related organizations, meteorological industry, and science communicators but also with other related fields such as energy, water resources, agriculture, fishery, and forestry. The third is to enhance in nurturing young scientists by supporting domestic and international networks and training the state-of-the-art sciences, and to create opportunities for young scientists to advance into a wider field. The last is to expand its international activities for solving the challenges facing mankind, such as climate change risks and weather, climate, and environment disasters. The KMS should also continue the efforts to establish an integrative platform for leading fundamental and interdisciplinary research in weather, climate, and environment.

Methods to Improve Problems in The Smart Factory Operation Process (스마트공장 운영 과정에서 나타나는 문제점 개선 방안)

  • Dong-Woo Lee;Seong-Hoon Lee
    • Journal of Internet of Things and Convergence
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    • v.9 no.2
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    • pp.41-46
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    • 2023
  • Smart factory construction projects are continuously being carried out domestically and abroad. In particular, in times of increasing uncertainty, interest in smart factories is increasing to improve corporate productivity. Currently, the government-led smart factory construction project is continuously being promoted in Korea. The tangible results of this construction project are very positive in indicators such as productivity improvement, quality improvement, and cost reduction. On the other hand, various contents are revealed in the survey to identify operational difficulties after building a smart factory. In this study, we analyzed difficulties (problems) in operation after establishing the system shown in the survey conducted in 2017 and 2020, and derived improvement plans for them. If these improvement measures are implemented in the relevant process of the smart factory construction project, it is expected that the operational difficulties felt by companies will be reduced, and a system with higher satisfaction than before will be established.

A Study on the Moral Responsibility of Lethal Autonomous Weapon Systems (LAWS): Focused on Robert Sparrow's "Responsibility Gap" Theory (치명적 자율무기체계의 도덕적 책임 문제 연구 : 로버트 스패로우의 '책임간극' 이론에 대한 고찰)

  • Hyunyoung Moon;Sangsu Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.375-381
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    • 2023
  • In an increasingly hyperconnected battlefield, the reliance on battlefield networks and AI-based autonomous weapons systems creates uncertainty and raises ethical concerns. This article explores the responsibility gap in operating autonomous weapons systems, using Robert Sparrow's theory. By analyzing Sparrow's arguments, we propose overcoming the responsibility gap in lethal autonomous weapon systems (LAWS). Our objective is to establish a framework of responsibility that aligns with the evolving battlefield, promoting the development and use of responsible weapon systems.

A Study of a Video-based Simulation Input Modeling Procedure in a Construction Equipment Assembly Line (건설기계 조립라인의 동영상 기반 시뮬레이션 입력 모델링 절차 연구)

  • Hoyoung Kim;Taehoon Lee;Bonggwon Kang;Juho Lee;Soondo Hong
    • The Journal of Bigdata
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    • v.7 no.1
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    • pp.99-111
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    • 2022
  • A simulation technique can be used to analyze performance measures and support decision makings in manufacturing systems considering operational uncertainty and complexity. The simulation requires an input modeling procedure to reflect the target system's characteristics. However, data collection to build a simulation is quite limited when a target system includes manual productions with a lot of operational time such as construction equipment assembly lines. This study proposes a procedure for simulation input modeling using video data when it is difficult to collect enough input data to fit a probability distribution. We conducted a video-data analysis and specify input distributions for the simulation. Based on the proposed procedure, simulation experiments were conducted to evaluate key performance measures of the target system. We also expect that the proposed procedure may help simulation-based decision makings when obtaining input data for a simulation modeling is quite challenging.

Development of Real-Time Optimal Bus Scheduling Models (실시간 버스 운행계획수립 모형 개발)

  • Kim, Wongil;Son, Bongsoo;Chung, Jin-Hyuk;Lee, Jeomho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5D
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    • pp.587-595
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    • 2008
  • Many studies on bus scheduling optimization have been done from the 1960s to recent years for establishing rational bus schedule plan that can improve convenience of bus passengers and minimize unnecessary runs. After 2000, as part of the Intelligent Transport Systems (ITS), the importance of the schedule management and providing schedule information through bus schedule optimization has become a big issue, and much research is being done to develop optimization models that will increase bus passenger convenience and, on the side of bus management, minimize unnecessary bus operation. The purpose of this study is to calculate the optimal bus frequency and create a timetable for each bus stop by applying DTR or DTRC model that use data for each bus stop and route segment. Model verification process was implemented using data collected from bus management system (BMS) and integrated transit-fare card system for bus route of Seoul's No. 472 line. In order to evaluate the reliability and uncertainty of optimal solution, sensitivity analysis was implemented for the various parameters and assumptions used in the bus scheduling model.

Generative AI Jeonse Fraud Prevention System (생성형 인공지능 전세 사기 방지 시스템)

  • Yeon-Jae Oh
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.1
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    • pp.173-180
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    • 2024
  • Along with its importance, the real estate market poses risks of various fraudulent activities. Recently, a surge in real estate-related scams, such as lease fraud, has caused great financial damage to many ordinary people. These problems are often caused by the complexity of real estate transactions and information imbalance. Therefore, there is an urgent need to secure reliability and improve transparency in the transaction process. In this paper, to solve this real estate fraud problem, we propose a chatbot system using digital technology and artificial intelligence, especially GPT (Generative Pre-Trained Transformer). This system serves to protect users from fraud by providing them with precautions and confirmations in the lease transaction process. In addition, GPT-based chatbots respond to questions from users in time, contributing to reducing uncertainty in the transaction process and increasing reliability.

Fuel Consumption Modeling for a VLCC Using Added Resistance Test Results and Operation Data in Seaways (부가저항 모형시험 결과와 실해역 운항 자료를 이용한 VLCC의 연료 소모량 모델 개발)

  • Seungbeom Lee;Dong-Hwan Kim;Jeonghwa Seo;Kwanwoo Kim;Sangmin Han;Mintae Kim;Sungwook Chung
    • Journal of the Society of Naval Architects of Korea
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    • v.61 no.5
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    • pp.359-369
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    • 2024
  • Data-driven model for estimating fuel oil consumption in seaways is suggested using the model test results and operation data. The data-driven model requires the forecasted wind speed, direction, and the desired ship speed as inputs to predict the engine speed, power, and fuel oil consumption. The structure of the data-driven model is based on the deterministic model of added power of a similar vessel of which model test results in the calm water and head seas are accessible. For a given wind speed, the wind resistance and added resistance in irregular waves presented by Pierson-Moskowitz spectrum are computed to be applied to the propulsion performance prediction. The deterministic model takes a cubic approximation between the wind speed and engine speed. The model is tuned by actual operation data in seaways with various wind direction groups. The shaft power and fuel oil consumption estimation are added to the model to be validated with the operation data. The prediction model is validated with the operation data to confirm that the estimation of the engine speed is the most significant uncertainty source.