Counter-propagation artificial neural network models in read-across predictions of toxicity

Drgan Viktor; Zuperl Spela; Venko Katja; Vracko Marjan; Novic Marjana

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Counter-propagation artificial neural network models in read-across predictions of toxicity

机译：读取毒性预测中的反传播人工神经网络模型

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来源
《Toxicology Letters: An International Journal Providing a Forum for Original and Pertinent Contributions in Toxicology Research》 |2017年第s1期|共1页
作者
Drgan Viktor; Zuperl Spela; Venko Katja; Vracko Marjan; Novic Marjana;
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Natl Inst Chem Dept Cheminformat Ljubljana Slovenia;

Natl Inst Chem Dept Cheminformat Ljubljana Slovenia;

Natl Inst Chem Dept Cheminformat Ljubljana Slovenia;

Natl Inst Chem Dept Cheminformat Ljubljana Slovenia;

Natl Inst Chem Dept Cheminformat Ljubljana Slovenia;

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原文格式 PDF
正文语种 eng
中图分类毒物学（毒理学）;
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入库时间 2022-08-20 07:34:51

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1. Counter-propagation artificial neural network models in read-across predictions of toxicity [J] . Drgan Viktor, Zuperl Spela, Venko Katja, Toxicology Letters: An International Journal Providing a Forum for Original and Pertinent Contributions in Toxicology Research . 2017,第S1期

机译：读取毒性预测中的反传播人工神经网络模型
2. Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm [J] . Drgan V., Zuperl S., Vracko M., SAR and QSAR in Environmental Research . 2016,第7a9期

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3. Development of models for predicting toxicity from sediment chemistry by partial least squares-discriminant analysis and counter-propagation artificial neural networks [J] . Manuel Alvarez-Guerra, Davide Ballabio, Jose Manuel Amigo, Environmental pollution . 2010,第2期

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4. Modeling the toxicity of textile industry wastewater using artificial neural networks [C] . Ruya Samli, V. Zulal Sonmez, Nuket Sivri Electric Electronics, Computer Science, Biomedical Engineerings' Meeting . 2017

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5. Modeling truck accidents at highway interchanges: Prediction models using both conventional and artificial intelligence approaches: Regression, neural networks, and fuzzy logic. [D] . Awad, Wael Hassan. 1997

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6. Hepatotoxicity Modeling Using Counter-Propagation Artificial Neural Networks: Handling an Imbalanced Classification Problem [O] . Benjamin Bajželj, Viktor Drgan 2020

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7. Integration of read-across and artificial neural network-based QSAR models for predicting systemic toxicity: A case study for valproic acid [O] . Tomoka Hisaki, Maki Aiba née Kaneko, Morihiko Hirota, 2020

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Counter-propagation artificial neural network models in read-across predictions of toxicity

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