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Probabilistic Modeling of Expert Knowledge Using Psychosemantics Methods (Using Environmental Data As An Example)

机译：心理学方法的专家知识概率建模（用环境数据为例）

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I.P. Kameneva; V.O. Artemchuk; A.V. Iatsyshyn;
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年度 2019
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1. Quantifying and predicting the benefits of environmental flows: Combining large‐scale monitoring data and expert knowledge within hierarchical Bayesian models [J] . Webb J. Angus, de Little Siobhan C., Miller Kimberly A., Freshwater Biology . 2018,第8期

机译：量化和预测环境流量的好处：将大规模监测数据和专家知识组合在等级贝叶斯模型中
2. Risk Characterization and Probabilistic Concentration–Response Modeling of Complex Environmental Mixtures Using New Approach Methodologies (NAMs) Data from Organotypic in Vitro Human Stem Cell Assays [J] . Nan-Hung Hsieh, Zunwei Chen, Ivan Rusyn, Environmental health perspectives. . 2021,第1期

机译：使用新方法方法（NAMS）来自体外人干细胞测定的新方法（NAMS）数据的复杂环境混合物的风险特征和概率浓度 - 响应模拟
3. Reducing the gap between experts' knowledge and data: The TOM4D methodology [J] . Laura Pomponio, Marc Le Goc Data & Knowledge Engineering . 2014,第ptaa期

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4. Extension of the RDR Method That Can Adapt to Environmental Changes and Acquire Knowledge from Both Experts and Data [C] . Takuya Wada, Tetsuya Yoshida, Hiroshi Motoda, 7th Pacific Rim International Conference on Artificial Intelligence, Aug 18-22, 2002, Tokyo, Japan . 2002

机译：扩展RDR方法以适应环境变化并从专家和数据中获取知识
5. An experimental study of the effects of application domain knowledge and data modeling on the quality of database implementations by non-experts [D] . Agboola, Isaac Olubanmi 1998

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6. Risk Characterization and Probabilistic Concentration–Response Modeling of Complex Environmental Mixtures Using New Approach Methodologies (NAMs) Data from Organotypic [O] . Nan-Hung Hsieh, Zunwei Chen, Ivan Rusyn, 2021

机译：使用新方法（NAMS）来自有机批次的复杂环境混合物的风险特征和概率浓度 - 响应建模
7. Quantifying and predicting the benefits of environmental flows: Combining large‐scale monitoring data and expert knowledge within hierarchical Bayesian models [O] . J. Angus Webb, Siobhan C. de Little, Kimberly A. Miller, 2018

机译：量化和预测环境流量的好处：将大规模监测数据和专家知识组合在等级贝叶斯模型中

Probabilistic Modeling of Expert Knowledge Using Psychosemantics Methods (Using Environmental Data As An Example)

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