随着我国经济的迅速发展,对于清洁能源项目规模的扩大愈发重视,尤其是在青海地区,它不仅能对生态环境起到一定的保护作用,而且对于社会的发展也有着不可替代的影响。本文通过构建清洁能源企业网络,将搜集到的数据进行具象化的处理,用Ge...随着我国经济的迅速发展,对于清洁能源项目规模的扩大愈发重视,尤其是在青海地区,它不仅能对生态环境起到一定的保护作用,而且对于社会的发展也有着不可替代的影响。本文通过构建清洁能源企业网络,将搜集到的数据进行具象化的处理,用Gephi做出网络图,将清洁能源企业整合成网络架构体系并进行统计分析,通过研究发现,清洁能源企业具有一定的相关关系,形成一定程度上的聚集,各企业间的联系比较密切。通过网络的方法,进一步理解清洁能源企业之间的联系,以帮助清洁能源企业做出正确的判断与决策,从而做出较为正确的选择并且建立更加完善的网络体系。With the rapid development of China’s economy, there is an increasing emphasis on the expansion of clean energy projects, especially in the Qinghai region. This is not only beneficial for the protection of the ecological environment but also irreplaceable for social development. This paper constructs a clean energy enterprise network, processing the collected data concretely, and using Gephi to create a network diagram. The clean energy enterprises are integrated into a network architecture system for statistical analysis. The study finds that there are certain correlations among clean energy enterprises, forming a degree of aggregation, and the connections between enterprises are relatively close. Through the method of networking, we can further understand the relationships between clean energy enterprises, help them make correct judgments and decisions, thus make more accurate choices, and establish a more comprehensive network system.展开更多
文摘随着我国经济的迅速发展,对于清洁能源项目规模的扩大愈发重视,尤其是在青海地区,它不仅能对生态环境起到一定的保护作用,而且对于社会的发展也有着不可替代的影响。本文通过构建清洁能源企业网络,将搜集到的数据进行具象化的处理,用Gephi做出网络图,将清洁能源企业整合成网络架构体系并进行统计分析,通过研究发现,清洁能源企业具有一定的相关关系,形成一定程度上的聚集,各企业间的联系比较密切。通过网络的方法,进一步理解清洁能源企业之间的联系,以帮助清洁能源企业做出正确的判断与决策,从而做出较为正确的选择并且建立更加完善的网络体系。With the rapid development of China’s economy, there is an increasing emphasis on the expansion of clean energy projects, especially in the Qinghai region. This is not only beneficial for the protection of the ecological environment but also irreplaceable for social development. This paper constructs a clean energy enterprise network, processing the collected data concretely, and using Gephi to create a network diagram. The clean energy enterprises are integrated into a network architecture system for statistical analysis. The study finds that there are certain correlations among clean energy enterprises, forming a degree of aggregation, and the connections between enterprises are relatively close. Through the method of networking, we can further understand the relationships between clean energy enterprises, help them make correct judgments and decisions, thus make more accurate choices, and establish a more comprehensive network system.
