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我国电力工业科研投入与行业发展的关系研究 被引量:2
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作者 李存斌 刘定 +1 位作者 李格格 董佳 《科技管理研究》 CSSCI 北大核心 2019年第24期97-104,共8页
选取电力工业科研投入和行业发展相关的7个统计指标,搜集其年度统计数据。首先,提出基于教与学优化算法(TLBO)的专家赋权法,降低专家群体研究领域交叉导致的赋权结果偏差,对电力工业科研投入和行业发展进行综合评价。然后,基于综合评价... 选取电力工业科研投入和行业发展相关的7个统计指标,搜集其年度统计数据。首先,提出基于教与学优化算法(TLBO)的专家赋权法,降低专家群体研究领域交叉导致的赋权结果偏差,对电力工业科研投入和行业发展进行综合评价。然后,基于综合评价结果,对电力工业科研投入与行业发展进行互谱分析。分析发现,从长期波动来看,我国电力工业科研投入超前行业发展6.10年,从短期波动来看,科研投入滞后行业发展2.89年。 展开更多
关键词 电力工业 科研投入 行业发展 互谱分析 教与学优化算法
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Intelligent control over chaos in the rolling process and its comparison with tracking control
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作者 RenHaipeng liuding 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2004年第2期158-162,178,共6页
Some existing methods for chaos control in engineering fields are analyzed and their drawbacks are pointed out. A tracking method can solve these problems to some extent, but it still depends on the mathematical model... Some existing methods for chaos control in engineering fields are analyzed and their drawbacks are pointed out. A tracking method can solve these problems to some extent, but it still depends on the mathematical model of the system to be controlled. An intelligent method based on fuzzy neural network (FNN) is used to control chaos in engineering fields. The FNN is employed to learn the inherent dynamics from the input and output of chaos, which can be used in the inverse system method, so that the method is free of the exact mathematical model of the system to be controlled. This intelligent method is compared with tracking method in the presence of measurement noise and model error. Simulation results show its superiority and feasibility. 展开更多
关键词 flatness control CHAOS tracking control intelligent control.
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Control of chaos solely based on RBF neural network without an analytical model
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作者 liuding 《Chinese Physics B》 SCIE EI CAS CSCD 2003年第5期568-568,共1页
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