• Journal of Environmental Science International
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• v.28 no.8
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• pp.701-707
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• 2019

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.297-306
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• 2019

Soil moisture monitoring is an important task to cope with climate change, and soil water prediction can provide large-scale soil moisture information. Therefore, this study was conducted to evaluate the relationship between the measured and predicted soil water content, and to estimate the correlation between the soil characteristics and soil water content. The selected sites in soil moisture monitoring network were 76, and the soil with high sand content (sand, loamy sand, and sandy loam in soil texture) accounted for 77% of the total. Organic matter and bulk density were 0.03 to 3.50% and 1.01 to 1.69 Mg m^-3, respectively. Predicting values of field capacity and wilting point were lower than the measured soil water content, and the correlation coefficient between the measured and predicted values were low as 0.548 to 0.748. However, a significantly high positive correlation (p<0.01) found between the measured and predicted soil water content. Soil water (field water capacity and wilting point) content was highly positively correlated with silt, clay, and organic matter (p<0.01) and highly negatively correlated with sand (p<0.01).

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.3
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• pp.101-110
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• 1996

The aim of the work described in this paper is to develope a constitutive model for the prediction of an unsaturated clayey soil and to confirm the application of the model. To this end a series of suction controlled isotropic and triaxial compression tests are conducted on clayey soils. Matric suction is controlled by the axis translation technique using high air entry ceramic disk. Total volume change, air and water volume changes are measured by the device made for the experiment. The specimens are compacted by dynamic compaction using a half of Proctor compaction energy with the water contents of 5% drier than the optimum moisture contents. From test results, volume changes and deviator stresses are analyzed at each state and their relationships are formulated. And the application of the model to clayey soils is confirmed by the comparison between test and predicted results. During drying-wetting and loading-unloading processes for isotropic states, the agreement between predicted and test results are satisfactory. And predicted deviator stresses are well agreed with the test results in shearing process, but volumetric strain is not well agreed with the test results in high suctions.

• Korean Journal of Soil Science and Fertilizer
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• v.34 no.4
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• pp.278-283
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• 2001

The overall objective of this research was to show a NIR soil analyzer assessing soil fertility by measuring soil properties rapidly. A total of 140 soil samples were used to obtain calibrations and validation estimating soil properties. The soil samples were ground to pass 0.2mm sieve openings. Partial least square regression analysis was used to develop a calibration for soil analysis. The results indicated that NIR soil analyzer could be used as a routine method for quantitatively determining pH, OM, total nitrogen, CEC, extractable Ca, Mg, K, available $SiO_2$ and soil moisture simultaneously within one minute. Therefore, the NIR soil analyzer may be suitable for quick estimation of soil fertility estimation in fertilizer assessments.

• Journal of Korea Water Resources Association
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• v.44 no.1
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• pp.51-64
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• 2011

The objective of this study is to develop a continuous rainfall-runoff model for flood prediction on a large-scale basin. For this study, the hourly surface runoff estimation method based on the variable retention parameter and runoff curve number is developed. This model is composed that the soil moisture to continuous rainfall can be simulated with applying the hydrologic components to the continuous equation for soil moisture. The runoff can be simulated by linking the hydrologic components with the storage function model continuously. The runoff simulation to large basins can be performed by using channel storage function model. Nakdong river basin is selected as the study area. The model accuracy is evaluated at the 8 measurement sites during flood season in 2006 (calibration period) and 2007~2008 (verification period). The calibrated model simulations are well fitted to the observations. Nash and Sutcliffe model efficiencies in the calibration and verification periods exist in the range of 0.81 to 0.95 and 0.70 to 0.94, respectively. The behavior of soil moisture depending on the rainfall and the annual loadings of simulated hydrologic components are rational. From this results, continuous rainfall-runoff model developed in this study can be used to predict the discharge on large basins.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.330-334
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• 2022

In light of the decreasing crop production and shortage of food across the world, one of the crucial criteria of agriculture nowadays is selecting the right crop for the right piece of land at the right time. First problem is that How Farmers can predict the right crop for cultivation because famers have no knowledge about prediction of crop. Second problem is that which algorithm is best that provide the maximum accuracy for crop prediction. Therefore, in this research Author proposed a method that would help to select the most suitable crop(s) for a specific land based on the analysis of the affecting parameters (Temperature, Humidity, Soil Moisture) using machine learning. In this work, the author implemented Random Forest Classifier, Support Vector Machine, k-Nearest Neighbor, and Decision Tree for crop selection. The author trained these algorithms with the training dataset and later these algorithms were tested with the test dataset. The author compared the performances of all the tested methods to arrive at the best outcome. In this way best algorithm from the mention above is selected for crop prediction.

• KIEAE Journal
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• v.10 no.4
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• pp.75-80
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• 2010

Generally, ground-source heat pump (GSHP) systems have a higher performance than conventional air-source systems. However, the major fault of GSHP systems is their expensive boring costs. Therefore, it is important issue that to reduce initial cost and ensure stability of system through accurate prediction of the heat extraction and injection rates of the ground heat exchanger. Conventional analysis methods employed by line source theory are used to predict heat transfer rate between ground heat exchanger and soil. Shape of ground heat exchanger was simplified by equivalent diameter model, but these methods do not accurately reflect the heat transfer characteristics according to the heat exchanger geometry. In this study, a numerical model that combines a user subroutine module that calculates circulation water conditions in the ground heat exchanger and FEFLOW program which can simulate heat/moisture transfer in the soil, is developed. Heat transfer performance was evaluated for 3 different types ground heat exchanger(U-tube, Double U-tube, Coaxial).

• Journal of Ocean Engineering and Technology
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• v.27 no.1
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• pp.16-23
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• 2013

By carrying out numerical analyses and model experiments, this paper presents the attenuation characterization of an L(0,2) guided ultrasonic wave propagating in a buried steel pipe. From this investigation, we first find that the L(0,2) mode has a better attenuation property. Second, it is shown from the numerical analyses that the attenuation increases with increases in the soil embedment length (0, 500, 1000, and 1500 mm) and degrees of saturation (0, 50, 99, and 100%). Third, it is also shown from the model experiment that the attenuation increases as the embedment lengths and soil moisture quantities (0, 10, 20, and 30 kg) increase. Finally, we find that an exponential extrapolation gives a better attenuation prediction because the extrapolation gives similar attenuation patterns between the numerical and experimental results.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.153-153
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• 2020

우리나라에선 크고 작은 가뭄 피해가 자주 일어나고 있으며 최근엔 유래 없는 다년가뭄이 발생하면서 가뭄에 대한 경각심이 커지고 있다. 가뭄에 적절하게 대응하여 피해를 경감시키기 위해서는 신뢰도 높은 가뭄 예측이 선행되어야 한다. 이에 본 연구는 앙상블 예측과 베이즈이론(Bayes' theorem)을 수문학적 가뭄지수 중 하나인 SRI(Standardized Runoff Index)에 적용해 가뭄 확률 전망을 실시했으며 이를 EDP(Ensemble Drought Prediction)라고 칭하였다. 국내 8개 댐유역에서 EDP를 생성하고 개선하는 과정은 다음과 같이 진행된다. 우선 TANK모형을 활용한 1개월 선행 유량 예측(Ensemble Streamflow Prediction, ESP)의 결과를 SRI로 변환하여 EDP 확률분포를 생성한다. 그런 다음, EDP를 개선하기 위해 그 기초인 ESP에서 미흡한 토양수분 초기조건을 보완하고자 베이즈이론을 활용했다. APCC(APEC Climate Center)의 위성 관측 SMI(Soil Moisture Index) 자료로 SRI와의 회귀식을 구축, 이를 우도함수로 정의해 사전 EDP 분포를 업데이트한 EDP+ 확률분포를 생성했다. 그 결과, EDP와 EDP+ 모두 심도가 깊은 가뭄을 전망할수록 예측력이 기후학적 예측보다 좋지 않았다. 그럼에도 우도함수로 사용한 회귀식의 정확도가 높을수록 EDP+의 정확도도 향상되는 경향이 나타났으며, 이는 베이즈이론을 사용한다면 가뭄 확률 전망을 개선할 수 있다는 것을 의미하고 있다. 하지만, 확정 전망 정확도는 확률 전망 정확도와는 관계가 없었는데 이는 확정 전망과 확률 전망이 본질적으로 다르기 때문인 것으로 사료된다.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.34-38
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• 2003

A mathematical model was developed for estimating the mechanical interrelation between characteristics of soil and main design factors of a tracked vehicle, and predicting the tractive performance of the tracked vehicle. Based on the mathematical model, a computer simulation program (TPPMTV) was developed in the study. The model considered the continuous change in tension for the whole track of a tracked vehicle, the analysis of shape and tension of the track segment between sprocket and first roadwheel, and the side thrust on both sides of grouser by the active earth pressure theory in predicting the tractive performance of a tracked vehicle. Also, the model contained not only sinkage depth of the track but the pressure distribution under the track in analyzing the side thrust. The effectiveness of the developed model was verified by performing the draw bar pull tests with a tracked vehicle reconstructed for test in loam soil with moisture content of 18.92％. The predicted drawbar pulls by the model were well matched to the measured ones. Such results implied that the model developed in the study could estimate the drawbar pulls well at various soil conditions, and would be very useful as a simulation tool for designing a tracked vehicle and predicting its tractive performance.