• Title/Summary/Keyword: price prediction

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Construction cost Prediction Model for Educational Building (학교건축의 공사비 분석 및 예측에 관한 연구)

  • Jeon Yong-Il;Chan Chan-Su;Park Tae-Keun
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2004.11a
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    • pp.290-295
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    • 2004
  • Along with social changes, school buildings are getting complex and diversified unlike the past. However, objective data analysis on construction costs fall short. In particular, ordering agencies are in a great need of objective and practical construction cost management for on-budget construction and procurement of quality goods. This paper analyzes the design diagram for a newly built school with an order from the Daejeon Metropolitan Office of Education, and compares the analysis with those of other kinds of buildings. The results are: the total construction cost of one school unit is 8,017,596,000 won on average; the cost is in the order of building, machinery and equipment, electricity, communications and civil engineering; as to activity, RC construction takes account of $30.3\%$ of the total construction cost. 1'he cost of school construction per M2 is 838,000 won, which is 6th highest of 11 kinds of constructions and slightly lower than 950,000 won, the average price of comparative constructions. When it comes to the percentage, school building takes mote percentage of the total cost than comparative building while machinery and equipment, electricity and communications takes slightly less percentage. Through simple regression analysis of gross coverage, this paper suggests a model formula with which the total construction cost, construction cost in accordance with activity, how much main construction materials are to be used are predictable.

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Estimation on Heating and Cooling Loads for a Multi-Span Greenhouse and Performance Analysis of PV System using Building Energy Simulation (BES를 이용한 연동형 온실의 냉·난방 부하 산정 및 PV 시스템 발전 성능 분석)

  • Lee, Minhyung;Lee, In-Bok;Ha, Tae-Hwan;Kim, Rack-Woo;Yeo, Uk-Hyeon;Lee, Sang-Yeon;Park, Gwanyong;Kim, Jun-Gyu
    • Journal of Bio-Environment Control
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    • v.26 no.4
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    • pp.258-267
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    • 2017
  • The price competitiveness of photovoltaic system (PV system) has risen recently due to the growth of industries, however, it is rarely applied to the greenhouse compared to other renewable energy. In order to evaluate the application of PV system in the greenhouse, power generation and optimal installation area of PV panels should be analyzed. For this purpose, the prediction of the heating and cooling loads of the greenhouse is necessary at first. Therefore, periodic and maximum energy loads of a multi-span greenhouse were estimated using Building Energy Simulation(BES) and optimal installation area of PV panels was derived in this study. 5 parameter equivalent circuit model was applied to analyzed power generation of PV system under different installation angle and the optimal installation condition of the PV system was derived. As a result of the energy simulation, the average cooling load and heating load of the greenhouse were 627,516MJ and 1,652,050MJ respectively when the ventilation rate was $60AE{\cdot}hr^{-1}$. The highest electric power production of the PV system was generated when the installation angle was set to $30^{\circ}$. Also, adjustable PV system produced about 6% more electric power than the fixed PV system. Optimal installation area of the PV panels was derived with consideration of the estimated energy loads. As a result, optimal installation area of PV panels for fixed PV system and adjustable PV system were $521m^2$ and $494m^2$ respectively.

An Analysis of the 2014 Pricing Guide for Technical Service Contracts through Comparison with Foreign Countries' Cases (해외사례 비교를 통한 2014년 개정 건설기술용역 대가기준 분석)

  • Lee, Taewon;Lee, Ghang
    • Korean Journal of Construction Engineering and Management
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    • v.16 no.3
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    • pp.152-164
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    • 2015
  • Enhancing clarity and transparency of the pricing guide for technical services for public construction works enables the prediction and reimbursement of the service cost for project owners and bidders, while it would also yield benefits for engineers who carry out the construction tasks. In order to improve the global competitiveness of construction service industry, the government revised its pricing guide for techical services for construction works recently, moving away from its previous percentage-of-construction-cost method towards the Cost Plus a Fee Method. However, since the Cost Plus a Fee Method results in the rise of the service price by 153%~197%, there is the need for a review on the method and basis of the adjustment in order to avoid controversies regarding the application of the revised method. In this context, this paper analysed the 2014 revision of the pricing guide for technical services for public construction works through comparison with foreign cases including those of the US and the UK. The analysis yielded the conclusion that, while the shift towards Cost Plus a Fee Method which is widely used in advanced economies is a very meaningful change in large measure, certain aspects still remain problematic. Unlike in advanced economies, the detailed break-down shows the direct labor cost includes certain indirect expenses. Also, indirec expenses are admitted so comprehensively as to include overhead costs and technology royalties. These problems results in redundant estimation of certain expenses, and obstructs transparency in spending details. This paper proposes various improvement measures to address these issues.

Patent data analysis using clique analysis in a keyword network (키워드 네트워크의 클릭 분석을 이용한 특허 데이터 분석)

  • Kim, Hyon Hee;Kim, Donggeon;Jo, Jinnam
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1273-1284
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    • 2016
  • In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.

Simulation-Based Stochastic Markup Estimation System $(S^2ME)$ (시뮬레이션을 기반(基盤)으로 하는 영업이윤율(營業利潤率) 추정(推定) 시스템)

  • Yi, Chang-Yong;Kim, Ryul-Hee;Lim, Tae-Kyung;Kim, Wha-Jung;Lee, Dong-Eun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2007.11a
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    • pp.109-113
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    • 2007
  • This paper introduces a system, Simulation based Stochastic Markup Estimation System (S2ME), for estimating optimum markup for a project. The system was designed and implemented to better represent the real world system involved in construction bidding. The findings obtained from the analysis of existing assumptions used in the previous quantitative markup estimation methods were incorporated to improve the accuracy and predictability of the S2ME. The existing methods has four categories of assumption as follows; (1) The number of competitors and who is the competitors are known, (2) A typical competitor, who is fictitious, is assumed for easy computation, (3) the ratio of bid price against cost estimate (B/C) is assumed to follow normal distribution, (4) The deterministic output obtained from the probabilistic equation of existing models is assumed to be acceptable. However, these assumptions compromise the accuracy of prediction. In practice, the bidding patterns of the bidders are randomized in competitive bidding. To complement the lack of accuracy contributed by these assumptions, bidding project was randomly selected from the pool of bidding database in the simulation experiment. The probability to win the bid in the competitive bidding was computed using the profile of the competitors appeared in the selected bidding project record. The expected profit and probability to win the bid was calculated by selecting a bidding record randomly in an iteration of the simulation experiment under the assumption that the bidding pattern retained in historical bidding DB manifest revival. The existing computation, which is handled by means of deterministic procedure, were converted into stochastic model using simulation modeling and analysis technique as follows; (1) estimating the probability distribution functions of competitors' B/C which were obtained from historical bidding DB, (2) analyzing the sensitivity against the increment of markup using normal distribution and actual probability distribution estimated by distribution fitting, (3) estimating the maximum expected profit and optimum markup range. In the case study, the best fitted probability distribution function was estimated using the historical bidding DB retaining the competitors' bidding behavior so that the reliability was improved by estimating the output obtained from simulation experiment.

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Discharge Rate Prediction of a new Sandbypassing System in a Field (새로운 샌드바이패싱 시스템의 토출율 예측을 위한 현장실험 연구)

  • Kweon, Hyuck-Min;Park, Sang-Shin;Kwon, Oh-Kyun
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.23 no.4
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    • pp.292-303
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    • 2011
  • A new type of sand bypassing system is proposed for recovering the eroded beach in this study. This system provides an added methodology to the soft defence which is main recovery method for the coastal shore protection in the world. The study proposes a conceptional design and manufacturing procedure for the relatively small size machine of sand bypassing. In order to get the discharging volume information, the power capacity of the system is tested in the field. The discharge rate of the new system shows up to the expected maximum of 618 ton/hr which is 9.6% lower than that by theoretical calculation. It gives a resonable agreement in this system when the flow is assumed to be of the high density. In this study, the delivering volume of sand is estimated according to the discharge rate. The combination of 300 mm(12 inch) intake and 250 mm(10 inch) discharge pipe line has the pumping capacity of $103\;m^3/hr$ which is nearly the same as that of South Lake Worth Inlet sand bypassing system, Florida, U.S.A.. The proposed system added the mobility to its merit. The unit price of Florida's sand bypassing is $$8~9/m^3$ (US). The system would be economically suitable for small volume of sand because no additional equipment is necessary for the intake. The diesel fuel of 25~30 l/hr was consumed during the system operation. The multiple working system would be the next investigation target for large volume of sand.

Development of an Intelligent Trading System Using Support Vector Machines and Genetic Algorithms (Support Vector Machines와 유전자 알고리즘을 이용한 지능형 트레이딩 시스템 개발)

  • Kim, Sun-Woong;Ahn, Hyun-Chul
    • Journal of Intelligence and Information Systems
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    • v.16 no.1
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    • pp.71-92
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    • 2010
  • As the use of trading systems increases recently, many researchers are interested in developing intelligent trading systems using artificial intelligence techniques. However, most prior studies on trading systems have common limitations. First, they just adopted several technical indicators based on stock indices as independent variables although there are a variety of variables that can be used as independent variables for predicting the market. In addition, most of them focus on developing a model that predicts the direction of the stock market indices rather than one that can generate trading signals for maximizing returns. Thus, in this study, we propose a novel intelligent trading system that mitigates these limitations. It is designed to use both the technical indicators and the other non-price variables on the market. Also, it adopts 'two-threshold mechanism' so that it can transform the outcome of the stock market prediction model based on support vector machines to the trading decision signals like buy, sell or hold. To validate the usefulness of the proposed system, we applied it to the real world data-the KOSPI200 index from May 2004 to December 2009. As a result, we found that the proposed system outperformed other comparative models from the perspective of 'rate of return'.

Cashew reject meal in diets of laying chickens: nutritional and economic suitability

  • Akande, Taiwo O;Akinwumi, Akinyinka O;Abegunde, Taye O
    • Journal of Animal Science and Technology
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    • v.57 no.5
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    • pp.17.1-17.6
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    • 2015
  • The present study investigated the nutritional and economic suitability of cashew reject meal (full fat and defatted) as replacement for groundnut cake (GNC) in the diets of laying chickens. A total of eighty four brown shavers at 25 weeks of age were randomly allotted into seven dietary treatments each containing 6 replicates of 2 birds each. The seven diets prepared included diet 1, a control with GNC at $220gkg^{-1}$ as main protein source in the diet. Diets 2, 3 and 4 consist of gradual replacement of GNC with defatted cashew reject meal (DCRM) at 50%, 75% and 100% on weight for weight basis respectively while diets 5, 6 and 7 consist of gradual inclusion of full fat cashew reject meal (FCRM) to replace 25%, 35% and 50% of GNC protein respectively. Each group was allotted a diet in a completely randomized design in a study that lasted eight weeks during which records of the chemical constituent of the test ingredients, performance characteristics, egg quality traits and economic indicators were measured. Results showed that the crude protein were 22.10 and 35.4% for FCRM and DCRM respectively. Gross energy of DCRM was 5035 kcal/kg compared to GNC, 4752 kcal/kg. Result of aflatoxin $B_1$ revealed moderate level between 10 and $17{\mu}g/Kg$ in DCRM and GNC samples respectively. Birds on control gained 10 g, while those on DCRM and FCRM gained about 35 g and 120 g respectively. Feed intake declined (P < 0.05) with increased level of FCRM. Hen day production was highest in birds fed DCRM, followed by control and lowest value (P < 0.05) was recorded for FCRM. No significant change (P > 0.05) was observed for egg weight and shell thickness. Fat deposition and cholesterol content increased (P > 0.05) with increasing level of FCRM. The cost of feed per kilogram decreased gradually with increased inclusion level of CRM. The prediction equation showed the relative worth of DCRM compared to GNC was 92.3% whereas the actual market price of GNC triples that of DCRM. It was recommended that GNC could be completely replaced by DCRM in layer's diets in regions where this by product is abundant. However, FCRM should be cautiously used in diets of laying chickens.

A Study on the Influence of Elderly Household Characteristics on Housing Consumption according to Public Pension Receipt (중·고령자 가구의 소득의 특성이 주택소비규모에 미치는 영향: 공적연금수령유무를 중심으로)

  • Jung, Sang Joon;Lee, Chang Moo;Shin, Hye Young
    • Korea Real Estate Review
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    • v.28 no.1
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    • pp.105-114
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    • 2018
  • According to Statistics Korea, South Korea has entered the realm of the "aging society" with the rapid development of the country's population. Researchers anticipate that the extremely high (73%) ratio of real estate property to total assets for mid-age to aged households in South Korea that do not have a fixed income may cause serious problems in the future. For example, the real estate market in South Korea may be bombarded with properties listed for sale, causing the average property price to drop due to the abundant supply. Although this prediction may be reasonable, this concept has excluded the idea of pension (which is crucial as it can be considered a consistent and fixed income) due to the limited amount of available data thereon; as such, it is important to include this factor to improve the pertinent research. Thus, this research was conducted using the data from the $3^{rd}$ and $5^{th}$ Korea Retirement and Income Study. For the study results, it was found that variables such as net asset, gender, education, and number of family members have the same impact as that found in the previous studies. To extend from here, two new factors were introduced: the existence of pensions and the amount of pension received by a household. From there, it was found that the existence of a consistent and fixed income such as a pension has led to an increase in housing consumption, the area of interest of the authors.

Long Range Forecast of Garlic Productivity over S. Korea Based on Genetic Algorithm and Global Climate Reanalysis Data (전지구 기후 재분석자료 및 인공지능을 활용한 남한의 마늘 생산량 장기예측)

  • Jo, Sera;Lee, Joonlee;Shim, Kyo Moon;Kim, Yong Seok;Hur, Jina;Kang, Mingu;Choi, Won Jun
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.4
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    • pp.391-404
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    • 2021
  • This study developed a long-term prediction model for the potential yield of garlic based on a genetic algorithm (GA) by utilizing global climate reanalysis data. The GA is used for digging the inherent signals from global climate reanalysis data which are both directly and indirectly connected with the garlic yield potential. Our results indicate that both deterministic and probabilistic forecasts reasonably capture the inter-annual variability of crop yields with temporal correlation coefficients significant at 99% confidence level and superior categorical forecast skill with a hit rate of 93.3% for 2 × 2 and 73.3% for 3 × 3 contingency tables. Furthermore, the GA method, which considers linear and non-linear relationships between predictors and predictands, shows superiority of forecast skill in terms of both stability and skill scores compared with linear method. Since our result can predict the potential yield before the start of farming, it is expected to help establish a long-term plan to stabilize the demand and price of agricultural products and prepare countermeasures for possible problems in advance.