The high-quality economic and social development of the Yellow River Basin is a combined system comprising the coordinated development of “economy–resources–environment–society”, with resources and the ecological environment bearing capacity as the constraints, and green innovative development as the driving force. Based on the systematic analysis of the structural dimensions of the composite system, this paper uses the balanced indicators and their coordinated development effectiveness to describe the development quality of the macro-composite system. In order to reveal the mechanism of the evolutionary path of the macro system, the resource- and environment-bearing capacity, regional high-quality development potential, regional innovation capacity, and high-quality development guarantee capacity are adopted as the main attributes and decision-making basis of the autonomous agents. The simulation results show that, under the existing development model, the economic development of all of the provinces in the Yellow River Basin will be constrained by resources and the environment. However, different policy scenarios significantly affect the evolutionary trends of economic development, resource consumption, and the environmental pollution situation. The mechanisms to overcome the bottleneck of the resource and ecological constraints are different for these policies, and the effects of the same policy in different provinces are also not the same.
Decoupling carbon emissions from economic growth is the key for the sustainable development of developing countries. Based on the panel data of marine aquaculture in China from 2010 to 2019, this paper employs the Tapio decoupling index model to analyze the decoupling characteristics of net carbon emissions and the economic growth of marine aquaculture. The logarithmic average weight decomposition method (LMDI model) and Tapio decoupling effort index model are also introduced to explore the contribution of various areas, provinces, and factors to the decoupling of net carbon emissions and the economic growth of marine aquaculture. Empirical results show that: (1) Net carbon emissions have a decoupling trend from the economic growth of marine aquaculture, but there is a large regional difference. (2) Regarding the degree of decoupling efforts, it is much stronger in the eastern and southern ocean economic zones than that in the northern ocean economic zone. (3) In terms of the decoupling contributions of various factors, carbon emission intensity > aquaculture scale > aquaculture efficiency > aquaculture structure, but there is heterogeneity among the different regions. Among the reasons for the inter-regional differences, carbon emission intensity > aquaculture scale > aquaculture structure > aquaculture efficiency. A further redundancy efficiency analysis explains the source of the differences. On this basis, strategies are proposed to improve the efficiency of marine aquaculture, including the construction of a modern three-dimensional aquaculture system, the improvement of the market-oriented mechanism, and the establishment of a modern marine aquaculture economic system.
Based on the panel data of 250 prefecture-level cities from 2006 to 2019, we adopted the idea and method of a “quasi-natural experiment” with difference-in-difference to assess the industrial-structure-upgrading effect of FTZ construction, analyze the factors and mechanisms influencing the effect, and further compare and analyze the regional heterogeneity and differences in spatial and temporal characteristics. We also propose policy recommendations to promote the orderly development of the FTZ. Empirical results show that, (i) compared with non-FTZ cities, the level of rationalization for industrial structures in FTZ cities increased by 9.69%, and the level of the advanced industrial structures increased by 7.01%. (ii) The innovation effect and the foreign investment effect enhance the effect of FTZ policy on industrial structure upgrading. (iii) Heterogeneity analysis found that the eastern and central FTZ have more significant roles in promoting industrial structure upgrading. (iv) Further spatial and temporal comparison analysis found that the promotion effect of the FTZ on industrial upgrading is temporally sustainable but with a certain lag. From the spatial perspective, the FTZ inhibits the level of advanced industrial structure in neighboring cities.
Short-term load prediction has always played an increasingly important part in power system administration, load dispatch, and energy transfer scheduling. However, how to build a novel model to improve the accuracy of load forecasts is not only an extremely challenging problem but also a concerning problem for the power market. Specifically, the individual model pays no attention to the significance of data selection, data preprocessing, and model optimization. So these models cannot always satisfy the time series forecasting’s requirements. With these above-mentioned ignored factors considered, to enhance prediction accuracy and reduce computation complexity, in this study, a novel and robust method were proposed for multi-step forecasting, which combines the power of data selection, data preprocessing, artificial neural network, rolling mechanism, and artificial intelligence optimization algorithm. Case studies of electricity power data from New South Wales, Australia, are regarded as exemplifications to estimate the performance of the developed novel model. The experimental results demonstrate that the proposed model has significantly increased the accuracy of load prediction in all quarters. As a result, the proposed method not only is simple, but also capable of achieving significant improvement as compared with the other forecasting models, and can be an effective tool for power load forecasting.
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