• Title/Summary/Keyword: forecasting system

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A Study on the Improvement of the Consultations on Amendment in Environmental Impact Assessment of Industrial Complex Development (산업단지 조성사업의 환경영향평가 변경협의 개선방안 연구)

  • Joo, Yong-Joon;Sagong, Hee
    • Journal of Environmental Impact Assessment
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    • v.31 no.3
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    • pp.129-140
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    • 2022
  • Environmental impact assessment on development projects is a process in which various stakeholders derive consultations by reflecting project characteristics and regional environmental status, and implementation of consultations is a prerequisite for securing sustainability of the local environment. The business plan can be changed to respond to changes in social and environmental conditions. And the business plan for which the environmental impact assessment consultation has been completed, it can be changed as a systematically prepared procedure (called Consultations on Amendment). As a result of investigating and analyzing the current status and major changes in the development project, Consultations on Amendment in industrial complexes were the most common, and the environmental impact is increasing accordingly. As the results of the analysis of operational status and the case studies, the main causes of Consultations on Amendment in industrial complex can be summarized into three categories: (1) formal demand forecasting for tenant industries, (2) excessive omission and simplification of administrative procedures under the Special Act, and (3) the use of an expedient change consultation system to facilitate environmental impact assessment consultation and shorten the period. This study proposes the following three measures to prevent the deterioration of the environmental impact assessment function due to frequent consultations on industrial complex changes; (1) Ensuring residents' participation procedures for Consultations on Amendment that changes important matters, (2) Reasonable revision of the "Simplification of Industrial Complex Procedures Act" to enhance the feasibility of industrial complex development plans and locations, (3) Development of evaluation criteria and methods for verification of real demand for objective demand management for industrial complexes, and (4) Preparation of a review guideline for Consultations on Amendment.

An Approach Using LSTM Model to Forecasting Customer Congestion Based on Indoor Human Tracking (실내 사람 위치 추적 기반 LSTM 모델을 이용한 고객 혼잡 예측 연구)

  • Hee-ju Chae;Kyeong-heon Kwak;Da-yeon Lee;Eunkyung Kim
    • Journal of the Korea Society for Simulation
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    • v.32 no.3
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    • pp.43-53
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    • 2023
  • In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

Development of Time-Cost Trade-Off Algorithm for JIT System of Prefabricated Girder Bridges (Nodular GIrder) (프리팹 교량 거더 (노듈러 거더)의 적시 시공을 위한 공기-비용 알고리즘 개발)

  • Kim, Dae-Young;Chung, Taewon;Kim, Rang-Gyun
    • Korean Journal of Construction Engineering and Management
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    • v.24 no.3
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    • pp.12-19
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    • 2023
  • In the case of the construction industry, the relationship between process and cost should be appropriately distributed so that the finished product can be delivered at the minimum fee within the construction period. At that time, it should be considered the size of the bridge, the construction method, the environment and production capacity of the factory, and the transport distance. However, due to various reasons that occur during the construction period, problems such as construction delay, construction cost increase, and quality and reliability degradation occur. Therefore, a systematic and scientific construction technique and process management technology are needed to break away from the conventional method. The prefab(Pre-Fabrication) is a representative OSC (Off-Site Construction) method manufactured in a factory and constructed onsite. This study develops a resource and process plan optimization system for the process management of the Nodular girder, a prefab bridge girder. A simulation algorithm develops to automatically test various variables in the personnel equipment mobilization plan to derive the optimal value. And, the algorithm was applied to the Paju-Pocheon Expressway Construction (Section 3) Dohwa 4 Bridge under construction, and the results compare. Based on construction work standard product calculation, actual input manpower, equipment type, and quantity were applied to the Activity Card, and the amount of work by quantity counting, resource planning, and resource requirements was reflected. In the future, we plan to improve the accuracy of the program by applying forecasting techniques including various field data.

An Analysis on the Preference and Use-Demand Forecasting of Bus Information (버스정보의 선호도 및 이용수요 예측에 관한 연구)

  • Lee, Won Gyu;Jung, Hun Young
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6D
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    • pp.791-799
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    • 2008
  • To build the system which has high utilization and usefulness for users, it is necessary to know the information type and use-demand that the use want. The purpose of this study is to forecast the preference and demand of utilization for bus information when bus information is offered through cellular phon. The accomplishments of this research are as follow : Firstly, importance on the level of individual factor and the value of change's figure can be evaluated, using preference analysis on bus information by conjoint analysis. Secondly, by establishing the use-demand model bus information using binary logit model, influence factor on whether or not the use of the user. Finally, ordered probit model was built by use behavior model in payment per call or per month of potential user of bus information. Through call times and sensitive analysis by payment methods, elasticity point, optimal payment fee, and use probability was analyzed. This study make application as basic to efficient bus information policy and to improve use rate of bus information in future because this study make it possible to get preference analysis, use-demand analysis and estimation of optimal payment fee which is reflecting various requirement in use of bus information user.

Real-Time Flood Forecasting by Using a Measured Data Based Nomograph for Small Streams (계측자료 기반 Nomograph를 이용한 실시간 소하천 홍수량 산정 연구)

  • Tae Sung Cheong;Changwon Choi;Sung Je Yei;Kang Min Koo
    • Ecology and Resilient Infrastructure
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    • v.10 no.4
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    • pp.116-124
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    • 2023
  • As the flood damage on small streams increase due to the increase in frequency of extreme climate events, the need to measure hydraulic data of them has increased for disaster risk management. National Disaster Management Institute, Ministry of Interior and Safety develops CADMT, a CCTV-based automatic discharge measurement technology, and operates pilot small streams to verify its performance and develop disaster risk management technology. The research selects two small streams such as the Neungmac and the Jungsunpil streams to develop the Nomograph by using the 4-Parameter Logistic method using only the observed rainfall data from the Automatic Weather System operated by the Korea Meteorological Agency closest to the small streams and discharge data collected by using the CADMT. To evaluate developed Nomograph, the research forecasts floods discharges in each small stream and compares the result with the observed discharges. As a result of the evaluations, the forecasted value is found to represent the observed value well, so if more accurate observed data are collected and the Nomograph based on it is developed in the future, the high-accuracy flood prediction and warning will be possible.

Implementation of an Automated Agricultural Frost Observation System (AAFOS) (농업서리 자동관측 시스템(AAFOS)의 구현)

  • Kyu Rang Kim;Eunsu Jo;Myeong Su Ko;Jung Hyuk Kang;Yunjae Hwang;Yong Hee Lee
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.26 no.1
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    • pp.63-74
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    • 2024
  • In agriculture, frost can be devastating, which is why observation and forecasting are so important. According to a recent report analyzing frost observation data from the Korea Meteorological Administration, despite global warming due to climate change, the late frost date in spring has not been accelerated, and the frequency of frost has not decreased. Therefore, it is important to automate and continuously operate frost observation in risk areas to prevent agricultural frost damage. In the existing frost observation using leaf wetness sensors, there is a problem that the reference voltage value fluctuates over a long period of time due to contamination of the observation sensor or changes in the humidity of the surrounding environment. In this study, a datalogger program was implemented to automatically solve these problems. The established frost observation system can stably and automatically accumulate time-resolved observation data over a long period of time. This data can be utilized in the future for the development of frost diagnosis models using machine learning methods and the production of frost occurrence prediction information for surrounding areas.

Study on Weather Modification Hybrid Rocket Experimental Design and Application (기상조절용 하이브리드 로켓의 실험 설계 및 활용연구)

  • Joo Wan Cha;Bu-Yo Kim;Miloslav Belorid;Yonghun Ro;A-Reum Ko;Sun Hee Kim;Dong-Ho Park;Ji Man Park;Hae Jung Koo;Ki-Ho Chang;Hong Hee Lee;Soojong Kim
    • Atmosphere
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    • v.34 no.2
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    • pp.203-216
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    • 2024
  • The National Institute of Meteorological Sciences in Korea has developed the Weather Modification Hybrid Rocket (WMHR), an advanced system that offers enhanced stability and cost-effectiveness over conventional solid-fuel rockets. Designed for precise operation, the WMHR enables accurate control over the ejection altitude of pyrotechnics by modulating the quantity of oxidizer, facilitating specific cloud seeding at various atmospheric layers. Furthermore, the rate of descent for pyrotechnic devices can be adjusted by modifying parachute sizes, allowing for controlled dispersion time and concentration of seeding agents. The rocket's configuration also supports adjustments in the pyrotechnic device's capacity, permitting tailored seeding agent deployment. This innovation reflects significant technical progression and collaborations with local manufacturers, in addition to efforts to secure testing sites and address hybrid rocket production challenges. Notable outcomes of this project include the creation of a national framework for weather modification technology utilizing hybrid rockets, enhanced cloud seeding methods, and the potential for broader meteorological application of hybrid rockets beyond precipitation augmentation. An illustrative case study confirmed the WMHR's operational effectiveness, although the impact on cloud seeding was limited by unfavorable weather conditions. This experience has provided valuable insights and affirmed the system's potential for varied uses, such as weather modification and deploying high-altitude meteorological sensors. Nevertheless, the expansion of civilian weather rocket experiments in Korea faces challenges due to inadequate infrastructure and regulatory limitations, underscoring the urgent need for advancements in these areas.

Analysis of PM2.5 Impact and Human Exposure from Worst-Case of Mt. Baekdu Volcanic Eruption (백두산 분화 Worst-case로 인한 우리나라 초미세먼지(PM2.5) 영향분석 및 노출평가)

  • Park, Jae Eun;Kim, Hyerim;Sunwoo, Young
    • Korean Journal of Remote Sensing
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    • v.36 no.5_4
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    • pp.1267-1276
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    • 2020
  • To quantitatively predict the impacts of large-scale volcanic eruptions of Mt. Baekdu on air quality and damage around the Korean Peninsula, a three-dimensional chemistry-transport modeling system (Weather Research & Forecasting - Sparse Matrix Operation Kernel Emission - Comunity Multi-scale Air Quality) was adopted. A worst-case meteorology scenario was selected to estimate the direct impact on Korea. This study applied the typical worst-case scenarios that are likely to cause significant damage to Korea among worst-case volcanic eruptions of Mt. Baekdu in the past decade (2005~2014) and assumed a massive VEI 4 volcanic eruption on May 16, 2012, to analyze the concentration of PM2.5 caused by the volcanic eruption. The effects of air quality in each region-cities, counties, boroughs-were estimated, and vulnerable areas were derived by conducting an exposure assessment reflecting vulnerable groups. Moreover, the effects of cities, counties, and boroughs were analyzed with a high-resolution scale (9 km × 9 km) to derive vulnerable areas within the regions. As a result of analyzing the typical worst-case volcanic eruptions of Mt. Baekdu, a discrepancy was shown in areas between high PM2.5 concentration, high population density, and where vulnerable groups are concentrated. From the result, PM2.5 peak concentration was about 24,547 ㎍/㎥, which is estimated to be a more serious situation than the eruption of Mt. St. Helensin 1980, which is known for 540 million tons of volcanic ash. Paju, Gimpo, Goyang, Ganghwa, Sancheong, Hadong showed to have a high PM2.5 concentration. Paju appeared to be the most vulnerable area from the exposure assessment. While areas estimated with a high concentration of air pollutants are important, it is also necessary to develop plans and measures considering densely populated areas or areas with high concentrations of susceptible population or vulnerable groups. Also, establishing measures for each vulnerable area by selecting high concentration areas within cities, counties, and boroughs rather than establishing uniform measures for all regions is needed. This study will provide the foundation for developing the standards for disaster declaration and preemptive response systems for volcanic eruptions.

Dispersion of Air Pollutants from Ship Based Sources in Incheon Port (인천항의 선박오염원에서 배출된 대기오염물질의 확산)

  • Kim, Kwang-Ho;Kwon, Byung Hyuk;Kim, Min-Seong;Lee, Don-Chool
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.5
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    • pp.488-496
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    • 2017
  • Emissions of pollutants from ship-based sources are controlled by the International Maritime Organization (IMO). Since pollutants emitted from ship may be dispersed to the land, controlling emissions from ships is necessary for efficient air quality management in Incheon, where exposure to ship-based pollution is frequent. It has been noted that the ratios of air pollutant emissions from coastal areas to inland areas are about 14% for NOx and 10% for SOx. The air quality of coastal urban areas is influenced by the number of ships present and the dispersion pattern of the pollutants released depending on the local circulation system. In this study, the dispersion of pollutants from ship-based sources was analyzed using the numerical California Puff Model (CALPUFF) based on a meteorological field established using the Weather Research and Forecasting Model (WRF). Air pollutant dispersion modeling around coastal urban regions such as Incheon should consider point and line sources emitted from both anchored and running ships, respectively. The total average NOx emissions from 82-84 ships were 6.2 g/s and 6.8 g/s, entering and leaving, respectively. The total average SOx emissions from 82-84 ships, entering and leaving, were 3.6 g/s and 5.1 g/s, respectively. The total average emissions for NOx and SOx from anchored ships were 0.77 g/s and 1.93 g/s, respectively. Due to the influence of breezes from over land, the transport of pollutants from Incheon Port to inland areas was suppressed, and the concentration of NOx and SOx inland were temporarily reduced. NOx and SOx were diffused inland by the sea breeze, and the concentration of NOx and SOx gradually increased inland. The concentration of pollutants in the area adjacent to Incheon Port was more influenced by anchored ship in the port than sea breezes. We expect this study to be useful for setting emission standards and devising air quality policies in coastal urban regions.

Keyword Network Analysis for Technology Forecasting (기술예측을 위한 특허 키워드 네트워크 분석)

  • Choi, Jin-Ho;Kim, Hee-Su;Im, Nam-Gyu
    • Journal of Intelligence and Information Systems
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    • v.17 no.4
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    • pp.227-240
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    • 2011
  • New concepts and ideas often result from extensive recombination of existing concepts or ideas. Both researchers and developers build on existing concepts and ideas in published papers or registered patents to develop new theories and technologies that in turn serve as a basis for further development. As the importance of patent increases, so does that of patent analysis. Patent analysis is largely divided into network-based and keyword-based analyses. The former lacks its ability to analyze information technology in details while the letter is unable to identify the relationship between such technologies. In order to overcome the limitations of network-based and keyword-based analyses, this study, which blends those two methods, suggests the keyword network based analysis methodology. In this study, we collected significant technology information in each patent that is related to Light Emitting Diode (LED) through text mining, built a keyword network, and then executed a community network analysis on the collected data. The results of analysis are as the following. First, the patent keyword network indicated very low density and exceptionally high clustering coefficient. Technically, density is obtained by dividing the number of ties in a network by the number of all possible ties. The value ranges between 0 and 1, with higher values indicating denser networks and lower values indicating sparser networks. In real-world networks, the density varies depending on the size of a network; increasing the size of a network generally leads to a decrease in the density. The clustering coefficient is a network-level measure that illustrates the tendency of nodes to cluster in densely interconnected modules. This measure is to show the small-world property in which a network can be highly clustered even though it has a small average distance between nodes in spite of the large number of nodes. Therefore, high density in patent keyword network means that nodes in the patent keyword network are connected sporadically, and high clustering coefficient shows that nodes in the network are closely connected one another. Second, the cumulative degree distribution of the patent keyword network, as any other knowledge network like citation network or collaboration network, followed a clear power-law distribution. A well-known mechanism of this pattern is the preferential attachment mechanism, whereby a node with more links is likely to attain further new links in the evolution of the corresponding network. Unlike general normal distributions, the power-law distribution does not have a representative scale. This means that one cannot pick a representative or an average because there is always a considerable probability of finding much larger values. Networks with power-law distributions are therefore often referred to as scale-free networks. The presence of heavy-tailed scale-free distribution represents the fundamental signature of an emergent collective behavior of the actors who contribute to forming the network. In our context, the more frequently a patent keyword is used, the more often it is selected by researchers and is associated with other keywords or concepts to constitute and convey new patents or technologies. The evidence of power-law distribution implies that the preferential attachment mechanism suggests the origin of heavy-tailed distributions in a wide range of growing patent keyword network. Third, we found that among keywords that flew into a particular field, the vast majority of keywords with new links join existing keywords in the associated community in forming the concept of a new patent. This finding resulted in the same outcomes for both the short-term period (4-year) and long-term period (10-year) analyses. Furthermore, using the keyword combination information that was derived from the methodology suggested by our study enables one to forecast which concepts combine to form a new patent dimension and refer to those concepts when developing a new patent.