• Title/Summary/Keyword: supply network method

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Adaptive Web Search based on User Web Log (사용자 웹 로그를 이용한 적응형 웹 검색)

  • Yoon, Taebok;Lee, Jee-Hyong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.11
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    • pp.6856-6862
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    • 2014
  • Web usage mining is a method to extract meaningful patterns based on the web users' log data. Most existing patterns of web usage mining, however, do not consider the users' diverse inclination but create general models. Web users' keywords can have a variety of meanings regarding their tendency and background knowledge. This study evaluated the extraction web-user's pattern after collecting and analyzing the web usage information on the users' keywords of interest. Web-user's pattern can supply a web page network with various inclination information based on the users' keywords of interest. In addition, the Web-user's pattern can be used to recommend the most appropriate web pages and the suggested method of this experiment was confirmed to be useful.

Control Gain Optimization for Mobile Robots Using Neural Networks and Genetic Algorithms (신경회로망과 유전알고리즘에 기초한 이동로봇의 제어 이득 최적화)

  • Choi, Young-kiu;Park, Jin-hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.4
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    • pp.698-706
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    • 2016
  • In order to move mobile robots to desired locations in a minimum time, optimal control problems have to be solved; however, their analytic solutions are almost impossible to obtain due to robot nonlinear equations. This paper presents a method to get optimal control gains of mobile robots using genetic algorithms. Since the optimal control gains of mobile robots depend on the initial conditions, the initial condition range is discretized to form some grid points, and genetic algorithms are applied to provide the optimal control gains for the corresponding grid points. The optimal control gains for general initial conditions may be obtained by use of neural networks. So the optimal control gains and the corresponding grid points are used to train neural networks. The trained neural networks can supply pseudo-optimal control gains. Finally simulation studies have been conducted to verify the effectiveness of the method presented in this paper.

Development of Remote Field Eddy Current Pipeline Inspection System (원격장 와전류 배관 탐상 시스템 개발)

  • Jeong, Jin-Oh;Yi, Jae-Kyung;Kim, Hyoung-Jean
    • Journal of the Korean Society for Nondestructive Testing
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    • v.21 no.5
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    • pp.556-560
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    • 2001
  • Remote field eddy current testing (RFECT) with through-wall transmission characteristic is being applied to pipes ranging from small tubes of heat exchanger to natural gas supply pipelines. Cast iron pipes with nominal diameter of 100mm are used primarily as the waterline pipes. The leakage of water occurs due to defects in the pipes caused by vibration of automobiles and corrosion. But, the use of direct inspection methods such as insertion of inspection equipment inside the pipelines has been limited due to its lack of economical efficiency. Economical development of inspection equipments is possible since RFECT method can be easily employed for system integration and quantitative evaluation of both inside and outside defects. In this study, the development of underground pipeline inspection system was tarried out by using RFECT method in consideration of the characteristics of waterline network. This paper specifically describes the design and production of RFECT pipeline inspection pig using centralizer mechanism, development of remote field eddy current signal acquisition and processing software, and review of RFECT system operation procedures.

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Design and Application of Multi Concept Keyword Model based on Web-using Information (웹 사용 정보에 기반한 다중 성향 키워드 모델의 설계와 응용)

  • Yoon, Tae-Bok;Lee, Seung-Hoon;Yoon, Kwang-Ho;Lee, Jee-Hyong
    • Journal of Internet Computing and Services
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    • v.10 no.5
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    • pp.95-105
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    • 2009
  • There are various studies to provide useful information for users on huge data of web-sites. Web usage mining among them is a method to extract meaningful patterns based on web users' log data. Most of existing patterns of web usage mining, however, had not considered users' diverse inclination but created general models. Web users' keywords can have various meaning upon their tendency and background knowledge. This study is for generating Multi Concept Keyword Model (MCK-Model) by analyzing web usage information on users' keywords of interest. MCK-Model can supply web page network for various inclination based on users' keywords of interest. Also, MCK-Model can be used to recommend the most proper web pages and it has been confirmed that the suggested method is useful enough.

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A Stochastic Bilevel Scheduling Model for the Determination of the Load Shifting and Curtailment in Demand Response Programs

  • Rad, Ali Shayegan;Zangeneh, Ali
    • Journal of Electrical Engineering and Technology
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    • v.13 no.3
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    • pp.1069-1078
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    • 2018
  • Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

Calculation of the target revenue water ratio of local waterworks considering economic feasibility (경제성을 고려한 지방상수도 목표 유수율 산정)

  • Donghong Kim;Jaebum Lee;Jungkwan Song;Taeho Choi
    • Journal of Korean Society of Water and Wastewater
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    • v.37 no.6
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    • pp.311-324
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    • 2023
  • As an advanced study on the method of calculating the target revenue water ratio of local waterworks through the leakage component analysis method proposed by Kim et al. (2022), this study developed a model to calculate the achievable revenue water ratio within the specified project cost, the required project cost to achieve the specified target revenue water ratio, and the economically appropriate target revenue water ratio level by considering the leakage reduction cost and leakage reduction benefit for each revenue water ratio improvement strategy, and conducted an applicability evaluation of the developed model using actual field data. The procedure for calculating the target revenue water ratio of local waterworks considering economics proposed in this study consists of three stages: physical data linkage model construction, leakage component analysis, and economic analysis, and the applicability was evaluated for Zone H with branch type and the Zone M network type. As a result of the application, it was calculated that approximately 32.5 billion won would be required to achieve the target revenue water ratio of 70% in the Zone H, and approximately KRW 10.5 billion would be required to achieve the target revenue water ratio of 75% in the Zone M. If the business scale of Zones H and M was corrected to 10,000 m3/day of water usage, the required project cost for a 1% improvement in the revenue water ratio of Zone H was calculated to be 0.7642 billion won and 0.4715 billion won for Zone M.

Power efficiency research for application of IoT technology (사물인터넷 기술 적용을 위한 소비전력 효율화 연구)

  • Seo, Younghoon;Park, Eun-Cheol;Kang, Sunghwan;Hwang, Jae-Mun;Yun, Junghwan;Eom, Junyoung;Gwon, Hyeong-Jun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.10a
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    • pp.669-672
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    • 2015
  • Recent Internet of Things (IoT, Internet of Things) that can be applied to various fields as the development of technology has been developed a lot of service and has been developed with the service also for crop management. To manage the essential elements of soil moisture in the crop growth but existing a direct person measuring the fluid point to carry the measuring instrument, if you take advantage of the WPAN (Wireless Personal Area Network) in this paper to manage sensor data, a fixed 3 points (30, 60, 90 cm) and can be managed can be scientifically analyzed the state of growth of the crop. Open field environment is utilized as it is less disturbance of the interference and the frequency of the radio frequency signal of the structure provides a relatively comfortable environment. Therefore, WPAN building and data transmission scheme of the minimum cost is to be developed. In addition, the operation to enter low power mode, the algorithm is necessary because a lot of restrictions on the power supply applied to the sensor nodes and the gateway is constructed in the open field. In the experiment, verifying the effectiveness by using a network configuration of each of the sensor nodes and the gateway, and provides a method for time synchronization of the operation and a low power mode. The study protocol for the RF communication with the LoRa and to enhance communication efficiency is needed in the future.

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Analyzing the Impact of Multivariate Inputs on Deep Learning-Based Reservoir Level Prediction and Approaches for Mid to Long-Term Forecasting (다변량 입력이 딥러닝 기반 저수율 예측에 미치는 영향 분석과 중장기 예측 방안)

  • Hyeseung Park;Jongwook Yoon;Hojun Lee;Hyunho Yang
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.4
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    • pp.199-207
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    • 2024
  • Local reservoirs are crucial sources for agricultural water supply, necessitating stable water level management to prepare for extreme climate conditions such as droughts. Water level prediction is significantly influenced by local climate characteristics, such as localized rainfall, as well as seasonal factors including cropping times, making it essential to understand the correlation between input and output data as much as selecting an appropriate prediction model. In this study, extensive multivariate data from over 400 reservoirs in Jeollabuk-do from 1991 to 2022 was utilized to train and validate a water level prediction model that comprehensively reflects the complex hydrological and climatological environmental factors of each reservoir, and to analyze the impact of each input feature on the prediction performance of water levels. Instead of focusing on improvements in water level performance through neural network structures, the study adopts a basic Feedforward Neural Network composed of fully connected layers, batch normalization, dropout, and activation functions, focusing on the correlation between multivariate input data and prediction performance. Additionally, most existing studies only present short-term prediction performance on a daily basis, which is not suitable for practical environments that require medium to long-term predictions, such as 10 days or a month. Therefore, this study measured the water level prediction performance up to one month ahead through a recursive method that uses daily prediction values as the next input. The experiment identified performance changes according to the prediction period and analyzed the impact of each input feature on the overall performance based on an Ablation study.

Accessibility Analysis Method based on Public Facility Attraction Index Using SNS Data (SNS 데이터를 이용한 공공시설 매력도지수에 따른 접근성 분석기법)

  • Lee, Ji Won;Yu, Ki Yun;Kim, Ji Young
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.1
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    • pp.29-42
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    • 2019
  • In order to expand the qualitative aspects of public facility, this study used SNS data to derive user-oriented preference factors for public facilities and then were quantified in terms of supply side and demand side. To derive preference factor, LDA, one of topic modeling, was used and attraction index was calculated for each facility. In addition we analyzed spatial accessibility to measure the degree of service experience of users by using 2SFCA model. The study area covered public libraries of Seoul, Korea. As a result of study, five topics were extracted as preference factors for the public library: Circumstance, Scale of facility, Cultural program, Parenting, Books and materials. In particular topic of circumstance and parenting were newly derived preference factors unknown in previous studies. As a result of calculating attraction index for each library, the index of Songpa Library, Jungdok Library, and Namsan Library was high. Songpa library has received good evaluation in parenting factor, and Jungdok & Namsan library in circumstance factor. The accessibility of each region seems to better in center of Seoul where public libraries are crowded, but shrinking toward the outskirts. We expect that the proposed method will contribute to user-oriented public facility evaluation and policy decision making.

A Study on Economic Evaluation Modeling of MVDC Distribution System for Hosting Capacity of PV System (태양광전원 수용을 위한 MVDC 배전망의 경제성평가 모델링에 관한 연구)

  • Lee, Hu-Dong;Kim, Ki-Young;Kim, Mi-Sung;Rho, Dae-Seok
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.1-12
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    • 2021
  • Technologies for an MVDC(medium voltage direct current) distribution system are being considered as an effective alternative to overcome the interconnection delay issues of PV systems. However, the implementation of a DC distribution system might lead to economic problems because of the development of DC devices. Therefore, this paper deals with the scale of a PV plant based on its capacity and proposes hosting-capacity models for PV systems to establish a network to evaluate the feasibility of an MVDC distribution system. The proposed models can be classified as AC and DC distribution systems by the power-supply method. PV systems with hundreds of MW, dozens of MW, and a few MW can be categorized as large-scale, medium-scale, and small-scale models, respectively. This paper also performed modeling for an economic evaluation of MVDC distribution system by considering both the cost of AC and DC network construction, converter replacement, operation, etc. The profit was composed of the SMP and REC rate of a PV plant. A simulation for economic evaluation was done for the MVDC distribution system using the present worth and equal-principal costs repayment method. The results confirmed that the proposed model is a useful tool to evaluate economic issues of a DC distribution system.