• Title/Summary/Keyword: Logistic function

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Building a Nonlinear Relationship between Air and Water Temperature for Climate-Induced Future Water Temperature Prediction (기후변화에 따른 미래 하천 수온 예측을 위한 비선형 기온-수온 상관관계 구축)

  • Lee, Khil-Ha
    • Journal of Environmental Policy
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    • v.13 no.2
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    • pp.21-38
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    • 2014
  • In response to global warming, the effect of the air temperature on water temperature has been noticed. The change in water temperature in river environment results in the change in water quality and ecosystem, especially Dissolved Oxygen (DO) level, and shifts in aquatic biota. Efforts need to be made to predict future water temperature in order to understand the timing of the projected river temperature. To do this, the data collected by the Ministry of Environment and the Korea Meteororlogical Administration has been used to build a nonlinear relationship between air and water temperature. The logistic function that includes four different parameters was selected as a working model and the parameters were optimized using SCE algorithm. Weekly average values were used to remove time scaling effect because the time scale affects maximum and minimum temperature and then river environment. Generally speaking nonlinear logistic model shows better performance in NSC and RMSE and nonlinear logistic function is recommendable to build a relationship between air and water temperature in Korea. The results will contribute to determine the future policy regarding water quality and ecosystem for the decision-driving organization.

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Quality Enhancement of Medical Images by Using Nonlinear Histogram Equalization Function (비선형 히스토그램 평활화 함수에 의한 의료영상의 화질개선)

  • Cho, Yong-Hyun
    • Journal of the Korean Society of Industry Convergence
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    • v.13 no.1
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    • pp.23-30
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    • 2010
  • This paper presents a histogram equalization based on the nonlinear transformation function for enhancing the quality of medical images. The nonlinear transformation function is applied to adaptively equalize the brightness of the image according to its intensity level frequency. The logistic function is used as a nonlinear transformation function, which is calculated by only using the intensity level with maximum frequency and the maximum intensity level in an histogram, and the total number of pixels. The proposed method has been applied for equalizing 8 medical images with a different resolution and histogram distribution. The experimental results show that the proposed method has the superior enhancement performances compared with the conventional histogram equalization. And the proposed histogram equalization can be used in various multimedia systems in real-time.

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A Study on the Optimum Parameter Estimation of Software Reliability (소프트웨어 신뢰도의 적정 파라미터 도출 기법에 관한 연구)

  • Che, Gyu-Shik;Moon, Myong-Ho
    • Journal of Information Technology Applications and Management
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    • v.13 no.4
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    • pp.1-12
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    • 2006
  • Many software reliability growth models(SRGM) have been proposed since the software reliability issue was raised in 1972. The technology to estimate and grow the reliability of developing S/W to target value during testing phase were developed using them. Most of these propositions assumed the S/W debugging testing efforts be constant or even did not consider them. A few papers were presented as the software reliability evaluation considering the testing effort was important afterwards. The testing effort forms which have been presented by this kind of papers were exponential, Rayleigh, Weibull, or logistic functions, and one of these 4 types was used as a testing effort function depending on the S/W developing circumstances. I propose the methology to evaluate the SRGM using least square estimator and maximum likelihood estimator for those 4 functions, and then examine parameters applying actual data adopted from real field test of developing S/W.

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Modeling for Prediction of Potato Late Blight (Phytophthora infestans) (감자역병 진전도 예측모형 작성)

  • 안재훈;함영일;신관용
    • Korean Journal Plant Pathology
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    • v.14 no.4
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    • pp.331-338
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    • 1998
  • To develop the model for prediction of potato late blight progress, the relationship between severity index of potato late blight transformed by the logit and Gompit transformation function and cumulative severity value (CSV) processing weather data during growing period in Taegwallyeong alpine area, 1975 to 1992 were examined. When logistic model and Gompertz model were compared by determining goodness of fit for progressive degree of late blight using CSV as independent variable, the coefficients of determination were higher as 0.742 in the logistic model than 0.680 in the Gompertz model. Parameters in logistic model were composed of progressive rate and initial value of logistic model. Initial value was calculated in -3.664. The progressive rate of potato late blight was 0.137 in cv. Superior, 0.136 in cv. Irish Cobbler, and 0.070 in cv. Jopung without fungicide sprays. According to in crease of the number of spray times the progressive rate was lowered, was 0.020 in cv. Superior under the conventional program of fungicide sprays, 10 times sprays during cropping season. Equation of progressive rate, b1=0.0088 ACSV-0.033 (R2=0.976), was written by examining the relationship between the parameters of progressive rate of late blight and the average CSV (ACSV) quantifing weather information. By estimating parameters of logistic function, model able to describe the late blight progress of potato, cv. Superior was formulated in Y=4/(1+39.0·exp((0.0088 ACSV-0.033)·CSV).

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Comparing Classification Accuracy of Ensemble and Clustering Algorithms Based on Taguchi Design (다구찌 디자인을 이용한 앙상블 및 군집분석 분류 성능 비교)

  • Shin, Hyung-Won;Sohn, So-Young
    • Journal of Korean Institute of Industrial Engineers
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    • v.27 no.1
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    • pp.47-53
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    • 2001
  • In this paper, we compare the classification performances of both ensemble and clustering algorithms (Data Bagging, Variable Selection Bagging, Parameter Combining, Clustering) to logistic regression in consideration of various characteristics of input data. Four factors used to simulate the logistic model are (1) correlation among input variables (2) variance of observation (3) training data size and (4) input-output function. In view of the unknown relationship between input and output function, we use a Taguchi design to improve the practicality of our study results by letting it as a noise factor. Experimental study results indicate the following: When the level of the variance is medium, Bagging & Parameter Combining performs worse than Logistic Regression, Variable Selection Bagging and Clustering. However, classification performances of Logistic Regression, Variable Selection Bagging, Bagging and Clustering are not significantly different when the variance of input data is either small or large. When there is strong correlation in input variables, Variable Selection Bagging outperforms both Logistic Regression and Parameter combining. In general, Parameter Combining algorithm appears to be the worst at our disappointment.

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A Competitiveness Analysis of the Logistic Hub Cities in China (중국 물류거점도시의 경쟁력 분석)

  • Lee, Myung-Hun;Lee, Jun-Yeop
    • Journal of Korea Port Economic Association
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    • v.22 no.4
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    • pp.59-79
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    • 2006
  • In this paper, we analyse the comparative competitiveness of the 10 major logistic hub cities in China. First, using the input distance function, we calculated the technical efficiencies and the opportunity costs of the transport infra structure investments. Then, based on not only these supply side factors but also demand side, the overall comparative competitiveness by cities are analyzed. Our main findings are as follows: early developed, larger cities such as Shanghai, Guangzhou, Shenzhen are technically efficient but their opportunity costs of the additional transport investments are higher than the other cities. We also found that overall competitiveness of these larger and leading logistic hub cities are dominant over the small and newly developed logistic cities.

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A Study on the Imperfect Debugging of Logistic Testing Function (로지스틱 테스트함수의 불완전 디버깅에 관한 연구)

  • Che, Gyu-Shik;Moon, Myung-Ho;Yang, Kye-Tak
    • Journal of Advanced Navigation Technology
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    • v.14 no.1
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    • pp.119-126
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    • 2010
  • The software reliability growth model(SRGM) has been developed in order to estimate such reliability measures as remaining fault number, failure rate and reliability for the developing stage software. Almost of them assumed that the faults detected during testing were eventually removed. Namely, they have studied SRGM based on the assumption that the faults detected during testing were perfectly removed. The fault removing efficiency, however, is imperfect and it is widely known as so in general. It is very difficult to remove detected fault perfectly because the fault detecting is not easy and new error may be introduced during debugging and correcting. Therefore, We want to study imperfect software testing effort for the logistic testing effort which is thought to be the most adequate in this paper.

JND-based Mobile Phone Optimal Vibration Frequency (JND를 이용한 휴대폰의 최적 진동 주파수 설계)

  • Lee, Bongwang;Park, Hyunho;Myung, Rohae
    • Journal of Korean Institute of Industrial Engineers
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    • v.30 no.1
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    • pp.27-35
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    • 2004
  • A study was conducted to investigate an optimal vibration frequency for mobile phones with just noticeable difference(JND). The just noticeable difference, Weber's law, is the minimum amount by which stimulus intensity must be changed in order to produce a noticeable variation in sensory experience. In order to find the optimal vibration frequency, sixteen frequencies ranged from 24Hz to 603Hz were selected. Subjects then wereasked to differentiate a pair of vibration frequencies. For the analysis, the psychometric function to determine the optimal vibration frequency and the logistic regression to validate the determined frequency were used. The results show that the 2nd order polynomial equations were best fitted for the JND psychometric function and the optimal mobile phone vibrations were determined at 140Hz, 151 Hz, and 160Hz. With the ogive-shaped psychometric function developed by the logistic regression, the results of this study was validated that the determined vibration frequencies (140Hz, 151 Hz, and 160Hz) were optimal mobile phone vibration frequencies.

Prediction model of surface subsidence for salt rock storage based on logistic function

  • Wang, Jun-Bao;Liu, Xin-Rong;Huang, Yao-Xian;Zhang, Xi-Cheng
    • Geomechanics and Engineering
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    • v.9 no.1
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    • pp.25-37
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    • 2015
  • To predict the surface subsidence of salt rock storage, a new surface subsidence basin model is proposed based on the Logistic function from the phenomenological perspective. Analysis shows that the subsidence curve on the main section of the model is S-shaped, similar to that of the actual surface subsidence basin; the control parameter of the subsidence curve shape can be changed to allow for flexible adjustment of the curve shape. By using this model in combination with the MMF time function that reflects the single point subsidence-time relationship of the surface, a new dynamic prediction model of full section surface subsidence for salt rock storage is established, and the numerical simulation calculation results are used to verify the availability of the new model. The prediction results agree well with the numerical simulation results, and the model reflects the continued development of surface subsidence basin over time, which is expected to provide some insight into the prediction and visualization research on surface subsidence of salt rock storage.

A new formulation for calculation of longitudinal displacement profile (LDP) on the basis of rock mass quality

  • Rooh, Ali;Nejati, Hamid Reza;Goshtasbi, Kamran
    • Geomechanics and Engineering
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    • v.16 no.5
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    • pp.539-545
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    • 2018
  • Longitudinal Displacement Profile (LDP) is an appropriate tool for determination of the displacement magnitude of the tunnel walls as a function of the distance to the tunnel face. Some useful formulations for calculation of LDP have been developed based on the monitoring data on site or by 3D numerical simulations. However, the presented equations are only based on the tunnel dimensions and for different quality of rock masses proposed a unique LDP. In the present study, it is tried to present a new formulation, for calculation of LDP, on the basis of Rock mass quality. For this purpose, a comprehensive numerical simulation program was developed to investigate the effect of rock mass quality on the LDP. Results of the numerical modelling were analyzed and the least square technique was used for fitting an appropriate curve on the derived data from the numerical simulations. The proposed formulation in the present study, is a logistic function and the constants of the logistic function were predicted by rock mass quality index (GSI). Results of this study revealed that, the LDP curves of the tunnel surrounded by rock masses with high quality (GSI>60) match together; because the rock mass deformation varies over an elastic range.