The small and medium-sized river basins along southeast coast of China hold comparatively abundant water resources.However,the rapid resources urbanization in recent years has produced a series of water problems such ...The small and medium-sized river basins along southeast coast of China hold comparatively abundant water resources.However,the rapid resources urbanization in recent years has produced a series of water problems such as deterioration of river water quality,water shortage and exacerbated floods,which have constrained urban economic development.By applying the principle of triple supply-demand equilibrium,this paper focuses on the estimation of levels of water supply and demand in 2030 at different guarantee probabilities,with a case study of Xiamen city.The results show that water shortage and inefficient utilization are main problems in the city,as the future water supply looks daunting,and a water shortage may hit nearly 2×10^(8)m^(3)in an extraordinarily dry year.Based on current water supply-demand gap and its trend,this paper proposes countermeasures and suggestions for developing and utilizing groundwater resources and improving the utilization rate of water resources,which can supply as a reference for other southeast middle-to-small-sized basin cities in terms of sustainable water resources and water environment protection.展开更多
Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and beh...Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and behavioral analysis.In this article,we studied the application of big data analytics forecasting in supply chain demand forecasting in the automotive parts industry to propose classifications of these applications,identify gaps,and provide ideas for future research.Algorithms will then be classified and then applied in supply chain management such as neural networks,k-nearest neighbors,time series forecasting,clustering,regression analysis,support vector regression and support vector machines.An extensive hierarchical model for short-term auto parts demand assess-ment was employed to avoid the shortcomings of the earlier models and to close the gap that regarded mainly a single time series.The concept of extensive relevance assessment was proposed,and subsequently methods to reflect the relevance of automotive demand factors were discussed.Using a wide range of skills,the factors and co-factors are expressed in the form of a correlation characteristic matrix to ensure the degree of influence of each factor on the demand for automotive components.Then,it is compared with the existing data and predicted the short-term historical data.The result proved the predictive error is less than 6%,which supports the validity of the prediction method.This research offers the basis for the macroeconomic regulation of the government and the production of auto parts manufacturers.展开更多
基金This paper was funded by the Geological Survey Project of China Geological Survey"Comprehensive Geological Survey of Xiamen-Zhangzhou-Quanzhou City"(DD20190303).
文摘The small and medium-sized river basins along southeast coast of China hold comparatively abundant water resources.However,the rapid resources urbanization in recent years has produced a series of water problems such as deterioration of river water quality,water shortage and exacerbated floods,which have constrained urban economic development.By applying the principle of triple supply-demand equilibrium,this paper focuses on the estimation of levels of water supply and demand in 2030 at different guarantee probabilities,with a case study of Xiamen city.The results show that water shortage and inefficient utilization are main problems in the city,as the future water supply looks daunting,and a water shortage may hit nearly 2×10^(8)m^(3)in an extraordinarily dry year.Based on current water supply-demand gap and its trend,this paper proposes countermeasures and suggestions for developing and utilizing groundwater resources and improving the utilization rate of water resources,which can supply as a reference for other southeast middle-to-small-sized basin cities in terms of sustainable water resources and water environment protection.
文摘Demand forecasting and big data analytics in supply chain management are gaining interest.This is attributed to the wide range of big data analytics in supply chain management,in addition to demand forecasting,and behavioral analysis.In this article,we studied the application of big data analytics forecasting in supply chain demand forecasting in the automotive parts industry to propose classifications of these applications,identify gaps,and provide ideas for future research.Algorithms will then be classified and then applied in supply chain management such as neural networks,k-nearest neighbors,time series forecasting,clustering,regression analysis,support vector regression and support vector machines.An extensive hierarchical model for short-term auto parts demand assess-ment was employed to avoid the shortcomings of the earlier models and to close the gap that regarded mainly a single time series.The concept of extensive relevance assessment was proposed,and subsequently methods to reflect the relevance of automotive demand factors were discussed.Using a wide range of skills,the factors and co-factors are expressed in the form of a correlation characteristic matrix to ensure the degree of influence of each factor on the demand for automotive components.Then,it is compared with the existing data and predicted the short-term historical data.The result proved the predictive error is less than 6%,which supports the validity of the prediction method.This research offers the basis for the macroeconomic regulation of the government and the production of auto parts manufacturers.
