• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.11
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• pp.1111-1117
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• 2011

This paper proposed a fault detection and diagnosis (FDD) algorithm using nonlinear regression models, focusing especially on heat exchanger faults. This research concerned four working modes: those with no fault, evaporator fault, condenser fault, and evaporator and condenser faults. This research used no fault mode data to create an FDD algorithm. Using the no fault mode data, correlation functions for predicting the degree of superheat or subcool of heat exchangers (an evaporator and a condenser) were derived. Each correlation function has five inputs and one output. Based on these correlation functions, it is possible to predict the degree of superheat or subcool of each heat exchanger under various working conditions. The FDD algorithm was developed by comparing the predicted value and the simulation value. The FDD algorithm works well in all four working modes.

• Annual Conference of KIPS
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• 2019.10a
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• pp.578-580
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• 2019

우리 나라의 딸기 수경재배 면적은 2002년 5ha로 시작해서, 2007년에는 84ha, 2012년에는 317ha, 2017년에 1,575ha로 매년 30% 이상 급속하게 성장하고 있다. 이런 경향은 수경재배가 토양재배보다 작업이 용이하여 노동시간이 절약되며, 수량을 더 많이 생산할 수 있기 때문이다. 하지만, 공급양액을 배액으로 흘려버리는 비순환식 수경재배 방식이 증가 하면서 환경오염을 유발시킬 뿐만 아니라 수경재배 운영비용의 증가를 가져오고 있다. 본 논문은 작물 생장에 최적화된 양액공급을 위해 상관관계 분석 및 다중 선형 회귀 모델 기반의 딸기 수경재배 환경에서의 최적 양액 흡수량을 분석하고 추정해 보았다. 분석 결과, 수경재배 환경정보(일사량, 온도, 습도, CO₂ 등)를 대상으로 일사량 및 온도가 습도 및 CO₂에 비해 딸기재배를 위한 양액 흡수량에 더 큰 영향을 주는 것으로 분석되었고, 다중 선형 회귀 모델을 통한 회귀식의 R-Square값은 0.358으로 나타났다.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.5
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• pp.23-29
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• 2008

This study investigates the dynamic instability of strength-limited bilinear single degree of freedom (SDF) systems under seismic excitation. The strength-limited bilinear hysteretic model best replicates the hysteretic behavior of the steel moment resisting frames. To estimate the dynamic instability of SDF systems, the collapse strength ratio is used, which is the yield-strength reduction factor when collapse occurs. Statistical studies are carried out to estimate median collapse strength ratios and those dispersions of strength-limited bilinear SDF systems with given natural periods, hardening stiffness ratios, post-capping stiffness ratios, ductility and damping ratios ranging from 2 to 20% subjected to 240 earthquake ground motions recorded on stiff soil sites. Equations to calculate median and standard deviation of collapse strength ratios in strength-limited bilinear SDF systems are obtained through nonlinear regression analysis. By using the proposed equations, this study estimated the probabilistic distribution of collapse strength ratios, and compared this with the exact values from which the accuracy of the proposed equations was verified.

• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• The Journal of Engineering Geology
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• v.20 no.1
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• pp.35-45
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• 2010

The soil tests have been performed on the specimens obtained from about 1,150 sites including landslides and non-landslides areas in natural terrains for last 10 years. Based on the results of those tests, the average soil properties are estimated and the simple equations for estimating permeability are proposed according to geologic conditions. The average permeability in Granite and Mudstone sites is higher than other sites and the content of silt and clay in Mudstone and Gneiss sites is higher than other sites. The correlation analysis and the regression analysis were performed to estimate the coefficient of permeability according to geological conditions. As the result of the correlation analysis, the coefficient of permeability is selected as a dependent variable, and the silt and clay contents, the water contents and the dry unit weights are selected as independent variables. As the result of the regression analysis, the silt and clay contents and the void ratio were involved commonly in the linear regression equations according to geological conditions. To verify the proposed the linear regression equations, the measured result of the coefficient of permeability at other sites was compared with the result predicted with the proposed equations. As the result of comparison, there were a little bit different between them for some data. However the difference was relatively small. Therefore, the linear regression equations for estimating the coefficient of permeability according to geological conditions may be applied to Korean soils. However, these equations should be verified and corrected continuously to improve the accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.105-116
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• 2002

In this paper, an analytical model to predict the resisting capacity of slender RC columns is introduced. Material and geometric nonlinearities are taken into account, and the layer approach is adopted to simulate the different material properties across the sectional depth. On the basis of the obtained numerical analysis results, an improved design equation as a function of concrete strength, slenderness ratio, steel ratio and eccentricity for slender RC columns, which can be used effectively in the preliminary design stage, is introduced. Finally, P-M interaction diagrams constructed by the introduced equation are compared with the ACI method with the objective of establishing the relative efficiencies of the introduced equation.

• Journal of the Korean Society of Marine Environment & Safety
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• v.18 no.6
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• pp.545-550
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• 2012

Wind resource assessment is necessary when designing wind farm. To get the assessment, we must use a long term(20 years) observed wind data but it is so hard. so that we usually measured more than a year on the planned site. From the wind data, we can calculate wind energy related with the wind farm site. However, it calculate wind energy to collect the long term data from Met-mast(Meteorology Mast) station on the site since the Met-mast is unstable from strong wind such as Typhoon or storm surge which is Non-periodic. To solve the lack of the long term data of the site, we usually derive new data from the long term observed data of AWS(Automatic Weather Station) around the wind farm area using mathematical interpolation method. The interpolation method is called MCP(Measure-Correlative-Predict). In this study, based on the MCP Regression Model proposed by us, we estimated the wind energy at Handong site using AEP(Annual Energy Production) from Gujwa AWS data in Jeju. The calculated wind energy at Handong was shown a good agreement between the predicted and the measured results based on the linear regression MCP. Short term AEP was about 7,475MW/year. Long term AEP was about 7,205MW/year. it showed an 3.6% of annual prediction different. It represents difference of 271MW in annual energy production. In comparison with 20years, it shows difference of 5,420MW, and this is about 9 months of energy production. From the results, we found that the proposed linear regression MCP method was very reasonable to estimate the wind resource of wind farm.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.781-793
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• 2017

In this study, applicabilities of aerodynamic approaches for the estimation of pan evaporation were evaluated on 56 study stations in South Korea. To accomplish this study purpose, previous researchers' evaporation estimation equations based on aerodynamic approaches were grouped into seven generalized evaporation models. Furthermore, four multiple linear regression (MLR) models were developed and tested. The independent variables of MLR models are meteorological variables such as wind speed, vapor pressure deficit, air temperature, and atmospheric pressure. These meteorological variables are required for the application of aerodynamic approaches. In order to consider the effect of autocorrelation, MLR models were developed after differencing variables. The applicability of MLR models with differenced variables was compared with that of MLR models with undifferenced variables and the comparison results showed no significant difference between the two methods. The study results have indicated that there is strong correlation between estimated pan evaporation (using aerodynamic models and MLR models) and measured pan evaporation. However, pan evaporation are overestimated during August, September, October, November, and December. Most of meteorological variables that are used for MLR models show statistical significance in the estimation of pan evaporation. Vapor pressure deficit was turned out to be the most significant meteorological variable. The second most significant variable was air temperature; wind speed was the third most significant variable, followed by atmospheric pressure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.429-432
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• 2004

본 논문은 기존의 퍼지 다항식 뉴럴 네트워크 (Fuzzy Polynomial Neural Networks ; FPNN) 모델을 이용하여 비선형성 데이터에 대한 추론을 제안한다. 복잡한 비선형 시스템의 모델동정을 위하여 생성된 GMDH 방법에 기초한 FPNN의 각 노드는 퍼지 규칙을 기반으로 구축되었으며, 층이 진행되는 동안 모델 스스로 노드의 선택과 제거를 통해 최적의 네트워크 구조를 생성할 수 있는 유연성을 가지고 있다. FPNN 각각의 활성노드를 퍼지다항식 뉴론(Fuzzy Polynomial Neuron ; FPN)이라고 표현한다. FPNN의 후반부 구조는 입출력 변수 사이 의 간략과 회귀다항식 (1차, 2차, 변형된 2차식) 함수에 의해 구현된다. 규칙의 전반부 멤버쉽 함수는 삼각형과 가우시안형의 멤버쉽 함수가 사용된다. 또한 유전자 알고리즘을 사용하여 각노드의 부분표현식을 구성하는 입력변수의 수, 입력변수와 차수의 선택 동조를 통하여 최적의 Genetic Algorithms(GAs)을 이용한 FPNN모델을 설계하는 것이 유용하고 효과적임을 보인다.

• Journal of Korean Society of Forest Science
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• v.100 no.3
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• pp.402-407
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• 2011

The objectives of this study were to analyze the crown vertical structure, crown bulk density, and to develop regression models for predicting crown fuel load using the data from 10 destructively sampled Pinus densiflora trees in Bonghwa, Gyeongbuk. The fuel loads were observed higher in the middle portion of the vertical distribution of crown followed by the lower portion and upper portion of Pinus densiflora, respectively. Approximately 25% crown fuel load was found in the needle while 33% was observed in the branches with <1 cm diameter with a total of 58% available fuel loads. The average crown bulk density was $0.45kg/m^3$, and $0.27kg/m^3$ of this was available in the needles and branches with <1 cm diameters. The resulting models in linear equations were able to account for 84% and 88% of the observed variation, while the allometric equations with diameter at breast height as the single predictor showed better results to account for 90% and 95% of the observed variation in the available crown fuel loads and total crown fuel loads, respectively. The suggested equations in this study could provide quantitative fuel load attributes for crown fire behavior models and fire management of red pine stands in Bonghwa areas.