• Title/Summary/Keyword: Prediction Unit

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A Quantity Prediction Model for Reinforced Concrete and Bricks in Education Facilities Using Regression Analysis

  • Lee, Jong-Kyun;Kim, Boo-Young;Kim, Jang-Young;Kim, Tae-Hui;Son, Kiyoung
    • Journal of the Korea Institute of Building Construction
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    • v.13 no.5
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    • pp.506-512
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    • 2013
  • Since the amendment of the law on the private sector investment in social infrastructure in January of 2005, the government has been actively promoting Build-Transfer-Lease (BTL) projects. Notably, most new educational facilities have been built as BTL projects. For these facilities, the unit cost per unit area has been applied to predict construction costs. However, since construction costs are mostly managed after the detailed design phase, the costs can be estimated incorrectly. For this reason, cost management is needed in the planning phase, with a sound approximate estimate to prevent the wasteful use of funds. To address this shortcoming, this study aims to develop a quantity prediction model for education facilities using regression analysis in the planning phase. The developed model is focused on the required quantities of reinforced concrete and bricks. In order to achieve the objective, the data of 44 educational facility projects collected from Gyeonggi-do was used in the regression model. This study can be utilized by major stakeholders to accurately predict construction costs by estimating the appropriate quantities of reinforced concrete and bricks in the planning design phase.

Gated Recurrent Unit Architecture for Context-Aware Recommendations with improved Similarity Measures

  • Kala, K.U.;Nandhini, M.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.538-561
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    • 2020
  • Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

Comparisons of RDII Predictions Using the RTK-based and Regression Methods (RTK 방법 및 회귀분석 방법을 이용한 RDII 예측 결과 비교)

  • Kim, Jungruyl;Lee, Jaehyun;Oh, Jeill
    • Journal of Korean Society of Water and Wastewater
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    • v.30 no.2
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    • pp.179-185
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    • 2016
  • In this study, the RDII predictions were compared using two methodologies, i.e., the RTK-based and regression methods. Long-term (1/1/2011~12/31/2011) monitoring data, which consists of 10-min interval streamflow and the amount of precipitation, were collected at the domestic study area (1.36 km2 located in H county), and used for the construction of the RDII prediction models. The RTK method employs super position of tri-triangles, and each triangle (called, unit hydrograph) is defined by three parameters (i.e., R, T and K) determined/optimized using Genetic Algorithm (GA). In regression method, the MovingAverage (MA) filtering was used for data processing. Accuracies of RDII predictions from these two approaches were evaluated by comparing the root mean square error (RMSE) values from each model, in which the values were calculated to 320.613 (RTK method) and 420.653 (regression method), respectively. As a results, the RTK method was found to be more suitable for RDII prediction during extreme rainfall event, than the regression method.

Comparison of Sediment Yield by IUSG and Tank Model in River Basin (하천유역의 유사량의 비교연구)

  • Lee, Yeong-Hwa
    • Journal of Environmental Science International
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    • v.18 no.1
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    • pp.1-7
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    • 2009
  • In this study a sediment yield is compared by IUSG, IUSG with Kalman filter, tank model and tank model with Kalman filter separately. The IUSG is the distribution of sediment from an instantaneous burst of rainfall producing one unit of runoff. The IUSG, defined as a product of the sediment concentration distribution (SCD) and the instantaneous unit hydrograph (IUH), is known to depend on the characteristics of the effective rainfall. In the IUSG with Kalman filter, the state vector of the watershed sediment yield system is constituted by the IUSG. The initial values of the state vector are assumed as the average of the IUSG values and the initial sediment yield estimated from the average IUSG. A tank model consisting of three tanks was developed for prediction of sediment yield. The sediment yield of each tank was computed by multiplying the total sediment yield by the sediment yield coefficients; the yield was obtained by the product of the runoff of each tank and the sediment concentration in the tank. A tank model with Kalman filter is developed for prediction of sediment yield. The state vector of the system model represents the parameters of the tank model. The initial values of the state vector were estimated by trial and error.

Prediction of Permeability for Braided Preform (브레이드 프리폼의 투과율 계수 예측)

  • Youngseok Song;Youn, Jae-Roun
    • Proceedings of the Korean Society For Composite Materials Conference
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    • 2003.04a
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    • pp.184-187
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    • 2003
  • Complete prediction of second order permeability tensor for three dimensional circular braided preform is critical to understand the resin transfer molding process of composites. The permeability can be predicted by considering resin flow through the multi-axial fiber structure. In this study, permeability tensor for a 3-D circular braided preform is calculated by solving a boundary problem of a periodic unit cell. Flow field through the unit cell is obtained by using a 3-D finite volume method (FVM) and Darcy's law is utilized to obtain permeability tensor. Flow analysis for two cases that a fiber tow is regarded as impermeable solid and permeable porous medium is carried out respectively. It is found that the flow within the intra-tow region of the braided preform is negligible if inter-tow porosity is relatively high but the flow through the tow must be considered when the porosity is low. To avoid checkerboard pressure field and improve the efficiency of numerical computation, a new interpolation function for velocity variation is proposed on the basis of analytic solutions. Permeability of the braided preform is measured through a radial flow experiment and compared with the permeability predicted numerically.

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A Numerical Study on a Prediction of Performance of the Metal Hydride Thermal Conversion System through the Propagation Phenomena of Superadiabatic Thermal Waves (초단열 열파동의 전파현상을 활용하는 수소저장합금 열변환 시스템의 성능예측을 위한 수치해석적 연구)

  • Kim, Gyu-Jeong;Kim, Gwan-Yeong;Chae, Jae-U
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.25 no.4
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    • pp.572-582
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    • 2001
  • A method of metal-hydride thermal conversion that is an alternative to the traditional method is proposed and investigated. The unit heat pump consists of reactors of two different metal-hydrides are distributed inside parallel channels filled with porous media. The channels are blown through with a heat-transfer agent. Thermal conversion develops as a set of successive heat waves. By a numerical-modeling method it is shown that the maximum thermal effect is attained in synchronous motion of the heat wave and the heat source (or sink) that accompanies the phase transition in the succession of unit metal-hydride pumps. The results are presented in a form convenient for prediction of the thermal and energy efficiency of the proposed thermal-conversion method in real devices.

Prediction of Agricultural Prices Using LSTM (LSTM 모델을 이용한 농산물 가격 예측에 관한 연구)

  • Yoo, Dong-wan;Park, Jong-beom
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.710-712
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    • 2022
  • Agricultural products take a large part of the wholesale and retail market as a necessity for daily consumption, and the consumption and price of agricultural products affect the supply and demand of agricultural products, consumer spending, and agricultural household income. Therefore, in this study, It was conducted on unit price prediction using LSTM to trade agricultural products, weather observation, import and export performance and fresh food index data. In order to study the supply and demand management of agricultural products and appropriate prices in the wholesale and retail market, unit prices are predicted for garlic, cabbage, and onions with high consumer price index weights among items subject to vegetable price stabilizers.

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DEVELOPMENT OF A WEB-BASED COST AND DURATION MANAGEMENT SYSTEM FOR MEGA-PROJECTS

  • Chang-Taek Hyun;Run-Zhi Jin;Myoung-Jin Son;Seung-Yoon Shin
    • International conference on construction engineering and project management
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    • 2011.02a
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    • pp.510-515
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    • 2011
  • Urban renewal projects, in the form of mega-projects, are being actively implemented both nationally and internationally to revitalize inactive cities. These programs, however, are difficult to manage efficiently due to their need for a large budget over a long period of time and due to conflicts with stockholders. Moreover, existing cost and duration management systems are structured with emphasis on the design and construction stage of unit projects, thus limiting their application to long-term mega-projects that are integrated with various facilities. To solve these problems, this study developed a web-based system that can collectively manage the cost and duration of mega-projects at a program level. The unit modules included in the system--CBS organization, construction cost and duration prediction, and total cost and duration prediction--can support decision-making at the early stage of the program. Furthermore, the modules, which include contract management, execution management, change management, and program progress management, support the program operations for its successful accomplishment. The web-based cost and duration management system developed in this study is expected to be used as a valuable tool that supports the successful accomplishment of mega-projects through their efficient management throughout their life cycle.

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Evaluation of Point Bearing Capacity using Field Model Pile Test (현장 축소모형 말뚝 시험을 이용한 선단지지력 예측)

  • Lee, Chang-Ho;Lee, Woo-Jin;Jeong, Hun-Jun;Han, Shin-In
    • Journal of the Korean GEO-environmental Society
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    • v.6 no.3
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    • pp.47-54
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    • 2005
  • In many practical cases, design methods of pile have been used mainly semi empirical bearing capacity equations. It can be done that confirmation of pile bearing capacities through using of dynamic and static tests during constructing or after constructions. If a prediction of layered point pile bearing capacity could be done through simple tests during field investigation, it could be done that more reliable design of pile than a prediction of using semi empirical equations or static formulations. This paper suggests a method to estimated point bearing capacity during in-situ investigation by using the dynamic rod model pile and verifies the point bearing capacity compare with results of static pile load tests. From test results, the unit ultimate point bearing capacities are relatively similar through a dynamic rod model pile tests and static pile load tests. The unit ultimate point bearing capacity by using N value is shown about 50 % value of measured unit ultimate point bearing capacity from field test result and the prediction of the unit ultimate point bearing capacity by using N value is shown very conservative, illogical and uneconomical pile designs.

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A Study on the Prediction of the Construction Cost in Planning Stage of Local Housing Union Project (지역주택조합사업 기획단계의 공사비 예측에 관한 연구)

  • Lee, Jin-Kyu
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.12
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    • pp.653-659
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    • 2018
  • The accurate prediction of construction cost is a key factor in a project's success. However, it is hard to predict the construction costs in the planning stages rapidly and precisely when drawings, specifications, construction cost calculation statements are incomplete, among other factors. Accurate construction-cost prediction in the planning stage of a project is also important for project feasibility studies and successful completion. Therefore, various techniques have been applied to accurately predict construction costs at an early stage when project information is limited. There are many factors that affect the construction cost prediction. This paper presents a construction-cost prediction method as multiple regression model with seven construction factors as independent variables. The method was used to predict the construction cost of a local housing union project, and the error rate was 4.87%. It is not possible to compare the cost of the project at the planning stage of the local housing union project, but it has high prediction accuracy compared to the unit price of an existing unit area. It is likely to be applied in construction-cost calculation work and to contribute to the establishment of the budget for the local housing union project.