• 농촌계획
• /
• 제26권3호
• /
• pp.25-38
• /
• 2020

The purpose of this study is constructing a regional-level crop acreage choice model incorporating the impacts of producer risk aversion, and applying the constructed model to the Korean policy that promotes rice paddy conversion into non-rice crop fields. The study adopts the approach of Paris (2018) which estimates the absolute risk aversion coefficient inside of a positive mathematical programming model. A panel data set of 143 cities/counties is used for the empirical study where agricultural land in each region is allocated to 8 crops. Our estimated absolute risk aversion coefficients are smaller than those of Paris (2018), but are a little bit larger than those of the existing Korea studies based on survey or econometric methods. We found that there are close relationships among the estimated risk aversion, regional characteristics, and farming patterns. We also found that incorporating the estimated risk attitudes results in substantial differences in the impacts of the rice paddy conversion policy.

• 한국정보통신학회:학술대회논문집
• /
• 한국정보통신학회 2022년도 춘계학술대회
• /
• pp.484-487
• /
• 2022

이 연구에서는 생산기간에 따른 치밀오일 저류층의 미래 생산성을 예측하기 위해 XAI(eXplainable Artificial Intelligence) 기반의 머신러닝 모델을 제시하였다. XAI 알고리즘은 해석 가능한 인공지능을 뜻하며 예측한 최종 결과의 근거와 도출 과정의 타당성을 제공한다. 본 연구에서는 현장자료를 기반으로 데이터전처리를 수행한 후 생산 초기와 후기의 생산성을 예측하는 지도학습 모델을 제안하고, 모델의 결과를 바탕으로 XAI를 이용하여 생산성 예측 모델의 영향을 미치는 인자를 분석하였다.

• 한국환경과학회지
• /
• 제27권7호
• /
• pp.509-518
• /
• 2018

Weather is the most influential factor for crop cultivation. Weather information for cultivated areas is necessary for growth and production forecasting of agricultural crops. However, there are limitations in the meteorological observations in cultivated areas because weather equipment is not installed. This study tested methods of predicting the daily mean temperature in onion fields using geostatistical models. Three models were considered: inverse distance weight method, generalized additive model, and Bayesian spatial linear model. Data were collected from the AWS (automatic weather system), ASOS (automated synoptic observing system), and an agricultural weather station between 2013 and 2016. To evaluate the prediction performance, data from AWS and ASOS were used as the modeling data, and data from the agricultural weather station were used as the validation data. It was found that the Bayesian spatial linear regression performed better than other models. Consequently, high-resolution maps of the daily mean temperature of Jeonnam were generated using all observed weather information.

• 한국환경과학회지
• /
• 제16권2호
• /
• pp.203-210
• /
• 2007

The delivery load data obtained from Nakdong river basin are used for developing the model estimating the daily delivery load on the main side streams of Nakdong River. The developed model assesses the daily contamination loads of the main thirteen side streams that contribute to the main stream of Nakdong river. It is developed that the model using the simplified equation that can estimate the daily delivery loads on the side main streams of Nakdong river for a period of having no data of the water quality and flow. The developed model for estimating the daily delivery loads from the main side streams in Nakdong river basin on each item such as BOD, TN, and TP is expressed as Daily delivery load ($\frac{kg}{day}$) = Production load $(\frac{kg}{day}){\times}(1-{\alpha}){\times}(\frac{daily\;runoff}{average\;runoff\;per\;year}){\gamma}$. The estimated values obtained by using the model are almost fit to the calculated values (real data) that have been acquired from the thirteen main side streams in Nakdong river basin. The correlation coefficient values, R, that indicate the correlation between the estimated and the calculated show over 0.7 that mean the estimated values from the used model are adapted to the real data except TN values of Nam-river, Hwang-river, Gam-river, We-river. Especially, the correlation of TP values between the estimated and the calculated implies quite a creditable data to use.

• 한국농림기상학회지
• /
• 제22권1호
• /
• pp.20-25
• /
• 2020

최근 고해상도의 격자형 기상자료를 활용한 기후변화 또는 농업기후분석이 시도되고 있다. 모형구동을 위해서는 각 격자별로 재배 정보를 입력해야만 한다. 이러한 입력정보 중 Oryza2000 에서는 육묘기간 온도상승값이 필요하며 이는 지역별로 파종기에 따라 변화될 수밖에 없다. 그러나 격자형 자료를 사용하여 모의할 때는 이것들을 모든 격자에 대해서 변화된 값을 주는 것은 어렵다. 이 문제를 해결하기 위해 철원, 수원, 서산, 광주에 대해서 4 월 중순부터 6 월 중순까지 육묘온도 상승값을 0℃, 2℃, 5℃, 7℃ 및 9℃로 적용하고 가장 변이 발생이 적은 온도를 선택하였다. 0℃와 2℃는 4 월 중순의 낮은 온도가 발생하였을 때 큰 변이를 보여 적절하지 않았으며 7℃이상에서는 변이가 줄어들었으나 모몸살 효과에 따른 출수지연 효과가 지역별로 파종기별로 과대평가되는 경우가 발생할 수도 있다. 따라서 전반적으로는 5℃가 가장 안정적인 출수날짜를 보였으며, 격자형 기상자료를 구동할 때는 이를 활용하는 것이 좋을 것으로 판단된다.

• Asian-Australasian Journal of Animal Sciences
• /
• 제10권5호
• /
• pp.505-509
• /
• 1997

Data were from four institutional herds and four field data collection centers involved in a progeny testing program for Nili-Ravi buffaloes in Pakistan. The REML with a single trait animal model, employed on 2,353 lactations, from 901 daughters of 66 sires, gave a heritability estimate of 0.18 for milk yield with repeatability (between lactations) of 0.43. Estimated milk yield was highest at 65 months of age for the first parity and 81 months for later parities. Correction factors for age at calving, standardized to 60 months in the second and later parities, were developed.

• 시스템엔지니어링학술지
• /
• 제17권2호
• /
• pp.1-8
• /
• 2021

This study proposes a systems engineering approach for the development of an advanced planning & scheduling (APS) system for a cosmetic case manufacturing factory. The APS system makes production plans and schedules based on the injection process, which consists of 27 plastic injection machines in parallel to control recommended inventory of products. The system uses machine operation/failure information and defective product/work-in-process tracking information to support intelligent scheduling. Furthermore, a genetic algorithm model is applied to handle the complexity of heuristic rules and machine/quality constraints in this process. As a result of the development, the recommended inventory compliance rate is improved by scheduling the 30-day production plan for 15 main products.

• Nuclear Engineering and Technology
• /
• 제38권8호
• /
• pp.803-808
• /
• 2006

The neutron induced nuclear cross section data for Ir-191 and Ir-193 were calculated and evaluated from unresolved resonance energy to 20MeV. The energy-dependent optical model potential parameters were determined based on the experimental data and applied up to 20MeV. A spherical optical model, a statistical model in an equilibrium energy region, and a multistep direct and multistep compound model in a pre-equilibrium energy region were used in the calculations. The direct capture model enhanced the fast neutron capture in the pre-equilibrium energy. The theoretically calculated cross sections were compared with the experimental data and the evaluated files. The calculations were found to be in good agreement with the experiment data. The evaluated cross section results were compiled with the ENDF-6 format. The fast energy results will be merged with the resonance parts to create a full evaluation library. The improvement of the neutron-induced cross section data will contribute to an increase in the efficiency of the production of Ir-192 as a radiation source.

• Journal of the Korean Data and Information Science Society
• /
• 제28권3호
• /
• pp.617-624
• /
• 2017

주로 노지에서 재배되는 배추는 기상 여건에 따라 생산량의 변화가 크고, 대체 작물의 존대로 인해 가격 변동이 크게 나타난다. 기존의 연구에서는 실제 기상정보를 활용해 배추의 생산량을 예측하였으나, 본 연구에서는 실제 기상정보가 아닌 웹상의 비정형 농업기상 정보를 활용하여 도매가격을 예측하였다. 2009년 1월부터 2016년 10월까지 포털사이트에서 배추를 포함한 문서를 수집하여, 수집된 문서 내에 나타난 기상 관련 키워드를 추출하였다. 도매가격만을 이용해 자기회귀 (autoregressive; AR)모형으로 작형별 출하시기인 1, 5, 8, 11월을 예측한 단순모형과 비정형 농업기상 정보를 추가적으로 활용해 AR모형으로 예측한 농업기상모형을 비교하였다. 그 결과 비정형 농업기상 정보를 활용한 농업기상모형의 성능이 더 우수하고 예측력에 도움이 되는 것으로 나타났다.

• Structural Engineering and Mechanics
• /
• 제47권1호
• /
• pp.27-44
• /
• 2013

A finite element computational procedure for the accurate analysis of quasistatic thermorheological complex structures response is developed. The geometrical nonlinearity, arising from large displacements and rotations (but small strains), is accounted for by the total Lagrangian description of motion. The Schapery's nonlinear single-integral viscoelastic constitutive model is modified for a time-stress-temperature-dependent behavior. The nonlinear thermo-viscoelastic constitutive equations are incrementalized leading to a recursive relationship and thereby the resulting finite element equations necessitate data storage from the previous time step only, and not the entire deformation history. The Newton-Raphson iterative scheme is employed to obtain a converged solution for the non-linear finite element equations. The developed numerical model is verified with the previously published works and a good agreement with them is found. The applicability of the developed model is demonstrated by analyzing two examples with different thermal/mechanical loading histories.