新陈代谢断裂理论是马克思主义理论的重要组成部分,是马克思吸收了近代自然科学发展突出成就,对资本主义社会人与自然、人与社会全面异化现象展开分析后,总结凝练出的科学理论。当前,资本主义全球化态势依旧猛烈,在逐利本性的驱使下,资...新陈代谢断裂理论是马克思主义理论的重要组成部分,是马克思吸收了近代自然科学发展突出成就,对资本主义社会人与自然、人与社会全面异化现象展开分析后,总结凝练出的科学理论。当前,资本主义全球化态势依旧猛烈,在逐利本性的驱使下,资本主义大工业利用新兴科学技术,更加无节制地开采自然资源,并且向自然环境中排放更多的废弃物,全球生态空间的稳定性造成严重破坏。立足马克思新陈代谢断裂理论的生态空间向度,对资本主义生产及其制度反生态本质进行剖析,揭示当代全球范围内新陈代谢断裂现象频发、生态空间失稳严重的根源,并通过我国生态文明建设探寻修复新陈代谢断裂、恢复生态空间稳定的有效路径,透射出马克思新陈代谢断裂理论的当代价值。The theory of metabolic rupture is an important part of Marxist theory, which is a scientific theory summarised and condensed by Marx after absorbing the outstanding achievements of the de- velopment of modern natural science and analysing the phenomenon of comprehensive alienation between human beings and nature, and between human beings and society in capitalist society. At present, the trend of capitalist globalisation is still fierce. Driven by the nature of profit-seeking, the capitalist big industries make use of the new science and technology to exploit the natural resources more unrestrainedly and discharge more wastes into the natural environment, which causes serious damage to the stability of the global ecological space. Based on the eco-spatial dimension of Marx’s theory of metabolic rupture, we analyse the anti-ecological nature of capitalist production and its system, reveal the root causes of the frequent occurrence of metabolic rupture and the serious destabilisation of eco-spatial space in the contemporary global context, and explore effective paths for repairing metabolic rupture and restoring the stability of eco-spatial space through the construction of China’s eco-civilisation, thus projecting the contemporary value of Marx’s theory of metabolic rupture.展开更多
煤炭是我国能源资源安全的压舱石,“双碳”背景下实现煤炭清洁加工与高效利用意义重大,而灰分检测对煤炭清洁化和智能化发展尤为重要。针对现有灰分检测存在的检测精度有待提高的突出问题,以两淮矿区典型煤样为研究对象,通过慢灰和X射...煤炭是我国能源资源安全的压舱石,“双碳”背景下实现煤炭清洁加工与高效利用意义重大,而灰分检测对煤炭清洁化和智能化发展尤为重要。针对现有灰分检测存在的检测精度有待提高的突出问题,以两淮矿区典型煤样为研究对象,通过慢灰和X射线荧光(X ray fluorescence,XRF)测试系统地探究了煤样的灰分和元素组成分布规律,并结合机器学习理论构建了灰分-元素特征数据集;结合灰色系统理论和新陈代谢算法,构建了自适应的GM(1,N)动态网络灰分拟合优化模型,并详细设计了动态网络算法流程;提出了GM(1,N)动态模型的关键超参数,并通过与常规拟合方法对比,全面地评价了模型拟合性能。结果表明:两淮矿区煤可视为由可燃元素和成灰元素共同构成,且成灰元素中质量分数占比最高为Si和Al,次之为S、Fe和Ca等,最少为P和Cl等,并且煤中成灰元素总含量与灰分呈正相关,而可燃元素与之相反;以灰分为标签值、以组成元素为特征值,形成了煤的灰分-元素特征数据集;以样本数据划分→动态网络灰分拟合→模型评价机制→动态拟合模型自适应优化→鲁棒性提升→多轮迭代优化为主线设计了GM(1,N)动态网络灰分拟合模型及其算法流程,有效提升了数据集稳定性和新鲜度,并且迭代收敛速度快,灰分误差阈值5%时其准确率达100%;对比经典GM(1,N)模型和常规多元线性回归模型,证明了新模型的灰分拟合性能得到显著提升,其相对误差为0.16%~4.96%、误差均值仅2.29%。展开更多
文摘新陈代谢断裂理论是马克思主义理论的重要组成部分,是马克思吸收了近代自然科学发展突出成就,对资本主义社会人与自然、人与社会全面异化现象展开分析后,总结凝练出的科学理论。当前,资本主义全球化态势依旧猛烈,在逐利本性的驱使下,资本主义大工业利用新兴科学技术,更加无节制地开采自然资源,并且向自然环境中排放更多的废弃物,全球生态空间的稳定性造成严重破坏。立足马克思新陈代谢断裂理论的生态空间向度,对资本主义生产及其制度反生态本质进行剖析,揭示当代全球范围内新陈代谢断裂现象频发、生态空间失稳严重的根源,并通过我国生态文明建设探寻修复新陈代谢断裂、恢复生态空间稳定的有效路径,透射出马克思新陈代谢断裂理论的当代价值。The theory of metabolic rupture is an important part of Marxist theory, which is a scientific theory summarised and condensed by Marx after absorbing the outstanding achievements of the de- velopment of modern natural science and analysing the phenomenon of comprehensive alienation between human beings and nature, and between human beings and society in capitalist society. At present, the trend of capitalist globalisation is still fierce. Driven by the nature of profit-seeking, the capitalist big industries make use of the new science and technology to exploit the natural resources more unrestrainedly and discharge more wastes into the natural environment, which causes serious damage to the stability of the global ecological space. Based on the eco-spatial dimension of Marx’s theory of metabolic rupture, we analyse the anti-ecological nature of capitalist production and its system, reveal the root causes of the frequent occurrence of metabolic rupture and the serious destabilisation of eco-spatial space in the contemporary global context, and explore effective paths for repairing metabolic rupture and restoring the stability of eco-spatial space through the construction of China’s eco-civilisation, thus projecting the contemporary value of Marx’s theory of metabolic rupture.
文摘煤炭是我国能源资源安全的压舱石,“双碳”背景下实现煤炭清洁加工与高效利用意义重大,而灰分检测对煤炭清洁化和智能化发展尤为重要。针对现有灰分检测存在的检测精度有待提高的突出问题,以两淮矿区典型煤样为研究对象,通过慢灰和X射线荧光(X ray fluorescence,XRF)测试系统地探究了煤样的灰分和元素组成分布规律,并结合机器学习理论构建了灰分-元素特征数据集;结合灰色系统理论和新陈代谢算法,构建了自适应的GM(1,N)动态网络灰分拟合优化模型,并详细设计了动态网络算法流程;提出了GM(1,N)动态模型的关键超参数,并通过与常规拟合方法对比,全面地评价了模型拟合性能。结果表明:两淮矿区煤可视为由可燃元素和成灰元素共同构成,且成灰元素中质量分数占比最高为Si和Al,次之为S、Fe和Ca等,最少为P和Cl等,并且煤中成灰元素总含量与灰分呈正相关,而可燃元素与之相反;以灰分为标签值、以组成元素为特征值,形成了煤的灰分-元素特征数据集;以样本数据划分→动态网络灰分拟合→模型评价机制→动态拟合模型自适应优化→鲁棒性提升→多轮迭代优化为主线设计了GM(1,N)动态网络灰分拟合模型及其算法流程,有效提升了数据集稳定性和新鲜度,并且迭代收敛速度快,灰分误差阈值5%时其准确率达100%;对比经典GM(1,N)模型和常规多元线性回归模型,证明了新模型的灰分拟合性能得到显著提升,其相对误差为0.16%~4.96%、误差均值仅2.29%。
