生物加工过程2012，Vol.10Issue(6)：65-69,5.DOI:10.3969/j.issn.1672-3678.2012.06.014
BP神经网络优化微生物浸矿工艺
Optimization of bioleaching conditions with back-propagation artificial neural network
摘要
Abstract
Chalcopyrite hydrolyte was used as bioleaching material for the production of copper ion and it could increase the value of low grade chalcopyrite. In this paper, the orthogonal experimental design and back-propagation artificial neural network ( BP-ANN) were employed to evaluate the optimal bioleaching results affected by parameters of inoculum rate, ore grade, and Fe ( II ) addition, and leaching solution pH. The results showed the optimal bioleaching condition predicted by each approach, and the orthogonal experimental design showed that 128. 753 mg/L copper ion was optimal under the condition. It showed that BP-ANN performed the experiment to be better than orthogonal experimental design. Under the optimal conditions (inoculum rate 12% , ore grade 0. 3% , Fe2+ addition 24 g/L, and leaching solution pH 1.7), the yield of copper ion was achieved in a 500 mL flask.关键词
微生物浸矿/BP神经网络/正交设计/黄铜矿溶液Key words
bioleaching/BP neural network/orthogonal design/chalcopyrite hydrolyte分类
生物科学引用本文复制引用
孙超,庞昕..BP神经网络优化微生物浸矿工艺[J].生物加工过程,2012,10(6):65-69,5.基金项目
国家重点基础研究发展计划(973计划)资助项目(2004CB619202) （973计划）
