BP-ANN for fitting the temperature-germination model and its application in predicting sowing time and region for Bermudagrass. - Wikidata - awgldk - TriplyDB

BP-ANN for fitting the temperature-germination model and its application in predicting sowing time and region for Bermudagrass.

BP-ANN for fitting the temperature-germination model and its application in predicting sowing time and region for Bermudagrass.

http://www.wikidata.org/entity/Q35070258

about

Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China.Forecasting outpatient visits using empirical mode decomposition coupled with back-propagation artificial neural networks optimized by particle swarm optimization.

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BP-ANN for fitting the temperature-germination model and its application in predicting sowing time and region for Bermudagrass.

http://www.wikidata.org/entity/Q35070258

description

2013 nî lūn-bûn

@nan

2013 թուականի Դեկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2013 թվականի դեկտեմբերին հրատարակված գիտական հոդված

@hy

2013年の論文

@ja

2013年論文

@yue

2013年論文

@zh-hant

2013年論文

@zh-hk

2013年論文

@zh-mo

2013年論文

@zh-tw

2013年论文

@wuu

name

BP-ANN for fitting the tempera ...... e and region for Bermudagrass.

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BP-ANN for fitting the tempera ...... e and region for Bermudagrass.

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type

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BP-ANN for fitting the tempera ...... e and region for Bermudagrass.

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BP-ANN for fitting the tempera ...... e and region for Bermudagrass.

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BP-ANN for fitting the tempera ...... e and region for Bermudagrass.

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BP-ANN for fitting the tempera ...... me and region for Bermudagrass

@en

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Erxu Pi

http://www.w3.org/2001/XMLSchema#string

Hongfei Lu

http://www.w3.org/2001/XMLSchema#string

Liqun Du

http://www.w3.org/2001/XMLSchema#string

Sai Ming Ngai

http://www.w3.org/2001/XMLSchema#string

P2860

Predicting germination response to temperature. II. Three-dimensional regression, statistical gridding and iterative-probit optimization using measured and interpolated-subpopulation data.

Artificial neural networks based controller for glucose monitoring during clamp test

Application of the back-error propagation artificial neural network (BPANN) on genetic variants in the PPAR-γ and RXR-α gene and risk of metabolic syndrome in a Chinese Han population.

Artificial neural network application for predicting soil distribution coefficient of nickel.

An artificial neural network (ANN)-based lung-tumor motion predictor for intrafractional MR tumor tracking.

Temperature and seed germination.

Prediction of aortic diameter values in healthy Turkish infants, children, and adolescents by using artificial neural network.

Assessment of genetic diversity of Bermudagrass (Cynodon dactylon) using ISSR markers.

Temperature requirements for seed germination and seedling development determine timing of seedling emergence of three monocotyledonous temperate forest spring geophytes.

Predicting germination response to temperature. III. Model validation under field-variable temperature conditions.

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scholarly article

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