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01.

A Study on Improving the predict accuracy rate of Hybrid Model Technique Using Error Pattern Modeling : Using Logistic Regression and Discriminant Analysis

Cho. Yong-Jun, Hur. Joon 한국데이터정보과학회 한국데이터정보과학회지 10 Pages

한국데이터정보과학회 한국데이터정보과학회지 2006, Vol.17 No.2 269-278 (10 pages)

Cho. Yong-Jun, Hur. Joon 저

이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
- 무료
02.

Geographically Weighted Poisson Regression (GWPR) Analysis to Explore Spatial Varying Relationship Between HPAI Incidences and Topographic Factors

Son Il Pak, Ki Hyun Cho, Kwang Nyeong Lee, Han Soo Lee 대한수의학회 대한수의학회 학술대회발표집 2 Pages

대한수의학회 대한수의학회 학술대회발표집 추계학술심포지움 69 242-243 (2 pages)

Son Il Pak, Ki Hyun Cho, Kwang Nyeong Lee, Han Soo Lee 저
...
- 무료
03.

Application of Geographically Weighted Regression (GWR) to Investigate the Spatial Distribution of Highly Pathogenic Avian Influenza in Korea

Son Il Pak, Kwang Nyeong Lee, Ki Hyun Cho, Gyeong Ju Lee 대한수의학회 대한수의학회 학술대회발표집 2 Pages

대한수의학회 대한수의학회 학술대회발표집 추계학술심포지움 68 241-242 (2 pages)

Son Il Pak, Kwang Nyeong Lee, Ki Hyun Cho, Gyeong Ju Lee 저
...
- 무료
04.

An Integrated Modeling Approach for Predicting Potential Epidemics of Bacterial Blossom Blight in Kiwifruit under Climate Change

Kwang-Hyung Kim, Young Jin Koh 한국식물병리학회 The Plant Pathology Journal 14 Pages

한국식물병리학회 The Plant Pathology Journal 2019, 35권 5호 7 459-472 (14 pages)

Kwang-Hyung Kim, Young Jin Koh 저
...
- 4,300원
increasing variation in climatic conditions under climate change directly influences plant-microbe interactions. To account for as many variables as possible that may play critical roles in such interactions, the use of an integrated modeling approach is necessary. Here, we report for the first time a local impact assessment and adaptation study of future epidemics of kiwifruit bacterial blossom blight (KBB) in Jeonnam province, Korea, using an integrated modeling approach. This study included a...
05.

Nonlinear Regression Analysis to Determine Infection Models of Colletotrichum acutatum Causing Anthracnose of Chili Pepper Using Logistic Equation

한국식물병리학회 The Plant Pathology Journal 8 Pages

한국식물병리학회 The Plant Pathology Journal 2010, 26권 1호 3 17-24 (8 pages)

저
...
- 3,000원
A logistic model for describing combined effects of both temperature and wetness period on appressorium formation was developed using laboratory data on percent appressorium formation of Colletotrichum acutatum. In addition, the possible use of the logistic model for forecasting infection risks was also evaluated as compared with a first-order linear model. A simplified equilibrium model for enzymatic reactions was applied to obtain a temperature function for asymptote parameter (A) of logistic...
06.

The Influence of Maternal Factors and Child Self-regulation on Peer Initiative: A Structural Equation Modeling Approach

Seonhyung Choi, Sunhee Kim 환태평양유아교육연구학회 Asia-Pacific journal of research in early childhood education 24 Pages

환태평양유아교육연구학회 Asia-Pacific journal of research in early childhood education 2021, Vol.15 No.3 1 1-24 (24 pages)

Seonhyung Choi, Sunhee Kim 저
...
- 5,300원
or unfriendly. This study used structural equation modeling to examine the contributions of mother’s coaching competence, parenting behavior, and child self-regulation to peer initiative. Participants comprised mothers of children aged 3 to 5 years (n = 343) in Korea and their teachers (n = 39). Structural equation modeling indicated that the relationship between mothers’ coaching competence and friendly peer initiative was fully mediated by maternal affection and child self-regulation....
07.

The Impact of Sample Size on Three-Level Quadratic Cross-Classified Multiple Membership Growth Curve Modeling Estimation

정혜원(Chung Hyewon), 전현정(Jeon Hyeonjeong), 박소영(Park Soyoung) 한국교육학회 교육학연구 22 Pages

한국교육학회 교육학연구 2022, 60권 7호 1 1-22 (22 pages)

정혜원(Chung Hyewon), 전현정(Jeon Hyeonjeong), 박소영(Park Soyoung) 저
...
- 5,100원
a minimum sample size requirement for the three-level quadratic cross-classified multiple membership growth curve modeling, this study employed a simulation under a variety of conditions including the number of measurement occasions (4, 5, and 6), the number of groups (30, 50, 100, and 200), average group size (10, 30, and 50), and multiple membership rates (20% and 40%). Across all of the simulated conditions, no substantial bias was found for the fixed effect and level-one variance component...
08.

A Comparison of Three Bayesian Point Estimates for Cross-Classified Multiple Membership Growth Curve Modeling

Chung Hyewon, Jeon Hyeonjeong, Park Soyoung 한국교육학회 교육학연구 26 Pages

한국교육학회 교육학연구 2021, 59권 7호 7 167-192 (26 pages)

Chung Hyewon, Jeon Hyeonjeong, Park Soyoung 저
...
- 5,500원
mode estimates of the between-school variances in the intercept and slope were substantially overestimated. In general, with the inverse Wishart prior, the Markov chain Monte Carlo (MCMC) posterior median is recommended for cross-classified multiple membership growth curve modeling, except under certain conditions. With the uniform prior, the MCMC mode is recommended for estimating cross-classified multiple membership growth curve modeling rather than the MCMC posterior mean or posterior median.
09.

Error Forecasting Using Linear Regression Model

Lian Guey Ler, Byung Sik Kim, Gye Woon Choi, Byung Hwa Kang, Jung Jae Kwang 한국습지학회 한국습지학회지 11 Pages

한국습지학회 한국습지학회지 2011, Vol.13 No.1 2 13-23 (11 pages)

Lian Guey Ler, Byung Sik Kim, Gye Woon Choi, Byung Hwa Kang, Jung Jae Kwang 저
...
- 4,000원
10.

A Numerical Modeling of Thawing Rate for Frozen Pork using High Pressure Assisted Thawing Technique

Ryu, Hyun-Sik, Park, Sung-Hee, Min, Sang-Gi 한국축산식품학회 학술대회논문집 6 Pages

한국축산식품학회 학술대회논문집 2004년호 49 310-315 (6 pages)

Ryu, Hyun-Sik, Park, Sung-Hee, Min, Sang-Gi 저
...
- 3,000원
pork. The calculated thawing rate from the results depending on the high pressure showed the strong trend of increased thawing rate under pressurized condition(P<0.05). And then, the numerical modeling was executed to predict the thawing rate influenced by the pressure level using exponential regression, LnY=0.70623 + 0.00433 ·P (R2=0.9985 ), and it was fairly fit for the functional relation between the thawing rate(Y) and pressure(P) with comparatively high coefficient, R2 of determination.

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