This paper focuses on the historical transition of human being's activities and the eco-environment in the upper reaches of Minjiang River. The history is divided into 4 periods, each with its own feature. During ...This paper focuses on the historical transition of human being's activities and the eco-environment in the upper reaches of Minjiang River. The history is divided into 4 periods, each with its own feature. During the period of nomad immigration, the top-line of the subalpine forest was forced downward by the expanding subalpine meadow. During the period of farming nationality immigration, the bottom-line of middle mountain forest had moved upward forced by the needs for land or timber of the increasing population in the valley basia During the period of the early exploiting, the focus resource was the timber. The total output was limited, comparing with the later period, because of the bad accessibility. But it was large enough to impact the forest ecosystem of the deforesting area. The recent 50 years is the crucial period of economic development and eco-environment degradation. This paper points out that the impact of human being's activities for environment lies on 3 factors: 1) physical features control the location and tendency eco-environmental change; 2) population and productivity control the scale and speed of eco-environmental change; 3) regional accessibility controls the time and location of eco-environmental change.展开更多
Screening similar historical fault-free candidate data would greatly affect the effectiveness of fault detection results based on principal component analysis(PCA).In order to find out the candidate data,this study co...Screening similar historical fault-free candidate data would greatly affect the effectiveness of fault detection results based on principal component analysis(PCA).In order to find out the candidate data,this study compares unweighted and weighted similarity factors(SFs),which measure the similarity of the principal component subspace corresponding to the first k main components of two datasets.The fault detection employs the principal component subspace corresponding to the current measured data and the historical fault-free data.From the historical fault-free database,the load parameters are employed to locate the candidate data similar to the current operating data.Fault detection method for air conditioning systems is based on principal component.The results show that the weighted principal component SF can improve the effects of the fault-free detection and the fault detection.Compared with the unweighted SF,the average fault-free detection rate of the weighted SF is 17.33%higher than that of the unweighted,and the average fault detection rate is 7.51%higher than unweighted.展开更多
基金Supported by the Knowledge Innovative program of Chinese Academy of Sciences(KSCX1-07-03)
文摘This paper focuses on the historical transition of human being's activities and the eco-environment in the upper reaches of Minjiang River. The history is divided into 4 periods, each with its own feature. During the period of nomad immigration, the top-line of the subalpine forest was forced downward by the expanding subalpine meadow. During the period of farming nationality immigration, the bottom-line of middle mountain forest had moved upward forced by the needs for land or timber of the increasing population in the valley basia During the period of the early exploiting, the focus resource was the timber. The total output was limited, comparing with the later period, because of the bad accessibility. But it was large enough to impact the forest ecosystem of the deforesting area. The recent 50 years is the crucial period of economic development and eco-environment degradation. This paper points out that the impact of human being's activities for environment lies on 3 factors: 1) physical features control the location and tendency eco-environmental change; 2) population and productivity control the scale and speed of eco-environmental change; 3) regional accessibility controls the time and location of eco-environmental change.
基金Research Project of China Ship Development and Design Center。
文摘Screening similar historical fault-free candidate data would greatly affect the effectiveness of fault detection results based on principal component analysis(PCA).In order to find out the candidate data,this study compares unweighted and weighted similarity factors(SFs),which measure the similarity of the principal component subspace corresponding to the first k main components of two datasets.The fault detection employs the principal component subspace corresponding to the current measured data and the historical fault-free data.From the historical fault-free database,the load parameters are employed to locate the candidate data similar to the current operating data.Fault detection method for air conditioning systems is based on principal component.The results show that the weighted principal component SF can improve the effects of the fault-free detection and the fault detection.Compared with the unweighted SF,the average fault-free detection rate of the weighted SF is 17.33%higher than that of the unweighted,and the average fault detection rate is 7.51%higher than unweighted.
