中国环境科学
中國環境科學
중국배경과학
CHINA ENVIRONMENTAL SCIENCE
2014年
7期
1890-1896
,共7页
浓度加和%独立作用%化学混合物%农药
濃度加和%獨立作用%化學混閤物%農藥
농도가화%독립작용%화학혼합물%농약
concentration addition%independent action%chemical mixture%pesticide
目前,准确预测混合物毒性仍然面临着挑战,为改进现有整合加和模型INFCIM,将该模型中“浓度=浓度+效应”形式修改为更加科学合理的“浓度=浓度+浓度”形式。利用分子电性距离矢量(MEDV)表征混合物组分的分子结构,以模糊数学中的隶属函数表征混合物组分的相似性和相异性,从而构建新的整合加和模型。利用6组六元混合物(共72个样本)验证模型的预测能力,结果表明,改进的模型能够准确预测无相互作用混合物毒性。在改进的模型中,利用多组混合物作为校正集,克服了INFCIM模型仅使用少量混合物数据作为校正集的缺点,使之更加可靠和具有代表性。
目前,準確預測混閤物毒性仍然麵臨著挑戰,為改進現有整閤加和模型INFCIM,將該模型中“濃度=濃度+效應”形式脩改為更加科學閤理的“濃度=濃度+濃度”形式。利用分子電性距離矢量(MEDV)錶徵混閤物組分的分子結構,以模糊數學中的隸屬函數錶徵混閤物組分的相似性和相異性,從而構建新的整閤加和模型。利用6組六元混閤物(共72箇樣本)驗證模型的預測能力,結果錶明,改進的模型能夠準確預測無相互作用混閤物毒性。在改進的模型中,利用多組混閤物作為校正集,剋服瞭INFCIM模型僅使用少量混閤物數據作為校正集的缺點,使之更加可靠和具有代錶性。
목전,준학예측혼합물독성잉연면림착도전,위개진현유정합가화모형INFCIM,장해모형중“농도=농도+효응”형식수개위경가과학합리적“농도=농도+농도”형식。이용분자전성거리시량(MEDV)표정혼합물조분적분자결구,이모호수학중적대속함수표정혼합물조분적상사성화상이성,종이구건신적정합가화모형。이용6조륙원혼합물(공72개양본)험증모형적예측능력,결과표명,개진적모형능구준학예측무상호작용혼합물독성。재개진적모형중,이용다조혼합물작위교정집,극복료INFCIM모형부사용소량혼합물수거작위교정집적결점,사지경가가고화구유대표성。
Recently, the accurately prediction of mixture toxicity remains a challenge. In order to modify the existed integrated addition model INFCIM (integrated fuzzy concentration addition-independent action model), the form of “concentration = concentration + effect” for the INFCIM model was modified into a reasonable form of “concentration = concentration + concentration”. The molecular electronegativity distance vector was used to characterize the molecular structures of mixture components. The fuzzy set theory was used to describe the degree of similarity and dissimilarity of mixture components. A new integrated addition model was then developed. Six mixtures (including 72 samples) with six components were used to test the predictive ability of the modified model. The results show that the modified model can accurately predict the non-interactive mixture toxicity. The proposed model based on the multiple mixtures overcomes the disadvantage of the model that only uses a single mixture data as calibration set. Thus, the modified model is more reliability and representativeness than the model based on a single mixture.