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Water | Free Full-Text | Evaluation of Water Resources Carrying Capacity of Zhangye City Based on Combined Weights and TOPSIS Modeling

According to the natural condition of water resources and the economic, social, and ecological environment status of Zhangye City, the water resources carrying capacity of Zhangye City is evaluated by using the water resources carrying capacity Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) model with combination assignment. The results show that: (1) From 2010 to 2020, the water resources carrying capacity of Zhangye City was generally stable at the macro level, ranking at grades III and IV. However, from the micro level, the water resources carrying capacity fluctuates to a certain extent and shows an increasing trend year by year. (2) The steady improvement of economic and social conditions is the main driving force for the improvement of the comprehensive water resources carrying capacity of Zhangye City, and the changes in the ecological environment are also important factors affecting the carrying capacity of water resources. The results provided a dec

Canadian Solar Reports Second Quarter 2023 Results

GUELPH, ON, Aug. 22, 2023 /PRNewswire/  Canadian Solar Inc.  today announced financial results for the second quarter ended June 30, 2023. Highlights Record quarterly net income attributable to.

Minerals | Free Full-Text | Mineral Prospecting Prediction via Transfer Learning Based on Geological Big Data: A Case Study of Huayuan, Hunan, China

In the big data era, mineral explorations need to accommodate for the growth in spatial dimensions and data dimensions, as well as the data volume and the correlation between data. Aiming to overcome the problems of limited and scattered data sources, chaotic data types, questionable data quality, asymmetric data information, and small sample sizes in current mineral prospecting data, this paper improved traditional 3D prediction methods based on the characteristics and actual needs of relevant mineral prospecting data. First, for the regions with incomplete data, a new 3D prediction method based on transfer learning was proposed. Meanwhile, random noise was adopted to compensate for the limited sample size in mineral prediction. By taking the Huayuan Mn deposit in Hunan Province as the study area, 22 proposed ore-controlling variables were divided into six groups for comparative tests under different combinations, and each group was further divided into the 3D CNN prediction method an

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