摘要
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。
In this paper,seven statistical indicators related to scientific research investment and industrial development of the power industry are selected to collect its annual statistical data.Firstly,an expert weighting method based on Teaching-learning-based Optimization Algorithm(TLBO)is proposed to comprehensively evaluate the scientific research investment and industrial development.The method fully considers the intersection of expert research fields,and reduces the deviation of the weighting results caused by expert preference.Then,based on the comprehensive evaluation results,cross-spectrum analysis is conducted on the scientific research investment and industry development.And it is found that in terms of long-term fluctuations,the scientific research investment of China’s power industry is 6.10 years ahead of the industry development.Moreover in terms of short-term fluctuations,the scientific research scientific lags behind the industry development by 2.89 years.
作者
李存斌
刘定
李格格
董佳
Li Cunbin;LiuDing;Li Gege;Dong Jia(Beijing Key Laboratory of New Energy Power and Low-Carbon Development,North China Electric Power University,Beijing 102206,China)
出处
《科技管理研究》
CSSCI
北大核心
2019年第24期97-104,共8页
Science and Technology Management Research
基金
国家自然科学基金资助项目“能源互联网电力与信息深度融合的风险元传递理论模型与应用研究”(71671065)
国家自然科学基金应急项目“动态视角下电力系统灾变风险演化传递机理研究”(71840004)
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
electric power industry
scientific research investment
industry development
cross-spectrum analysis
teaching-learning-based optimization algorithm
