On June 20,the 7th China-Latin America and Caribbean Think Tank Forum was held in Beijing.The forum carried the theme“Working Together to Build a China-LAC Community with a Shared Future.”Assistant Foreign Minister ...On June 20,the 7th China-Latin America and Caribbean Think Tank Forum was held in Beijing.The forum carried the theme“Working Together to Build a China-LAC Community with a Shared Future.”Assistant Foreign Minister Miao Deyu attended the opening ceremony and delivered remarks.Leonel Caraballo Maqueira,Vice President of the Cuban Diplomatic Academy,and Martin Charles,Ambassador of Dominica to China and Representative of the Latin American and Caribbean Diplomatic Corps in China,attended the meeting and delivered speeches.展开更多
Despite the maturity of ensemble numerical weather prediction(NWP),the resulting forecasts are still,more often than not,under-dispersed.As such,forecast calibration tools have become popular.Among those tools,quantil...Despite the maturity of ensemble numerical weather prediction(NWP),the resulting forecasts are still,more often than not,under-dispersed.As such,forecast calibration tools have become popular.Among those tools,quantile regression(QR)is highly competitive in terms of both flexibility and predictive performance.Nevertheless,a long-standing problem of QR is quantile crossing,which greatly limits the interpretability of QR-calibrated forecasts.On this point,this study proposes a non-crossing quantile regression neural network(NCQRNN),for calibrating ensemble NWP forecasts into a set of reliable quantile forecasts without crossing.The overarching design principle of NCQRNN is to add on top of the conventional QRNN structure another hidden layer,which imposes a non-decreasing mapping between the combined output from nodes of the last hidden layer to the nodes of the output layer,through a triangular weight matrix with positive entries.The empirical part of the work considers a solar irradiance case study,in which four years of ensemble irradiance forecasts at seven locations,issued by the European Centre for Medium-Range Weather Forecasts,are calibrated via NCQRNN,as well as via an eclectic mix of benchmarking models,ranging from the naïve climatology to the state-of-the-art deep-learning and other non-crossing models.Formal and stringent forecast verification suggests that the forecasts post-processed via NCQRNN attain the maximum sharpness subject to calibration,amongst all competitors.Furthermore,the proposed conception to resolve quantile crossing is remarkably simple yet general,and thus has broad applicability as it can be integrated with many shallow-and deep-learning-based neural networks.展开更多
Enterprise mergers and acquisitions(M&A)are vital strategies for companies worldwide to expand markets,enhance competitiveness,and achieve strategic goals.The Chinese government’s strong support for the new energ...Enterprise mergers and acquisitions(M&A)are vital strategies for companies worldwide to expand markets,enhance competitiveness,and achieve strategic goals.The Chinese government’s strong support for the new energy industry has created a favorable policy environment for the development of the lithium battery sector.Against this backdrop,Tianqi Lithium Corp’s acquisition of Sociedad Química y Minera(SQM)in Chile has garnered widespread attention.This paper takes Tianqi Lithium Corp’s acquisition of SQM as the research subject,conducting a detailed analysis of the motives behind the M&A.Subsequently,financial indicators are employed to conduct a performance analysis from a financial perspective,examining the impact of the M&A.Finally,based on the findings of the case analysis,relevant suggestions are proposed to offer a reference for the development of enterprise mergers and acquisitions.展开更多
[Objective] This study aimed to improve classification accuracy of RS images using rough set theory in the growth of crops. [Method] Technique methods of data mining and knowledge discovery have been used. The develop...[Objective] This study aimed to improve classification accuracy of RS images using rough set theory in the growth of crops. [Method] Technique methods of data mining and knowledge discovery have been used. The development status of spatial data mining and knowledge discovery （SDMKD） is presented and data mining techniques in remote sensing were deeply analyzed. Then, SDMKD of TM image are researched using method of rough set, mainly including four methods （rough set, apriori algorithms, inductive learning, clustering）. [Result] The proposed method raises efficiency of land use and land reclaim. Based on the SDMKD, the characteristics of TM showed that the information after using rough set is more intensive than that of none. Especially, much better results can be gained while kinds of corps are less than five. [Conclusion] This study laid significant basis for further research on data mining in the growth of crops.展开更多
Chemical engineering has played an important role in the development of petrochemical industry. Some important advances in chemical engineering have been discussed in detail, i. e. petroleum refining, organic chemical...Chemical engineering has played an important role in the development of petrochemical industry. Some important advances in chemical engineering have been discussed in detail, i. e. petroleum refining, organic chemicals,synthetic resin, synthetic fibers and relevant raw materials, synthetic rubber, and process energy integration. The main business targets of China Petroleum & Chemical Corporation (SINOPEC Corp.) and the focus of further researches are also addressed.展开更多
文摘On June 20,the 7th China-Latin America and Caribbean Think Tank Forum was held in Beijing.The forum carried the theme“Working Together to Build a China-LAC Community with a Shared Future.”Assistant Foreign Minister Miao Deyu attended the opening ceremony and delivered remarks.Leonel Caraballo Maqueira,Vice President of the Cuban Diplomatic Academy,and Martin Charles,Ambassador of Dominica to China and Representative of the Latin American and Caribbean Diplomatic Corps in China,attended the meeting and delivered speeches.
基金supported by the National Natural Science Foundation of China (Project No.42375192)the China Meteorological Administration Climate Change Special Program (CMA-CCSP+1 种基金Project No.QBZ202315)support by the Vector Stiftung through the Young Investigator Group"Artificial Intelligence for Probabilistic Weather Forecasting."
文摘Despite the maturity of ensemble numerical weather prediction(NWP),the resulting forecasts are still,more often than not,under-dispersed.As such,forecast calibration tools have become popular.Among those tools,quantile regression(QR)is highly competitive in terms of both flexibility and predictive performance.Nevertheless,a long-standing problem of QR is quantile crossing,which greatly limits the interpretability of QR-calibrated forecasts.On this point,this study proposes a non-crossing quantile regression neural network(NCQRNN),for calibrating ensemble NWP forecasts into a set of reliable quantile forecasts without crossing.The overarching design principle of NCQRNN is to add on top of the conventional QRNN structure another hidden layer,which imposes a non-decreasing mapping between the combined output from nodes of the last hidden layer to the nodes of the output layer,through a triangular weight matrix with positive entries.The empirical part of the work considers a solar irradiance case study,in which four years of ensemble irradiance forecasts at seven locations,issued by the European Centre for Medium-Range Weather Forecasts,are calibrated via NCQRNN,as well as via an eclectic mix of benchmarking models,ranging from the naïve climatology to the state-of-the-art deep-learning and other non-crossing models.Formal and stringent forecast verification suggests that the forecasts post-processed via NCQRNN attain the maximum sharpness subject to calibration,amongst all competitors.Furthermore,the proposed conception to resolve quantile crossing is remarkably simple yet general,and thus has broad applicability as it can be integrated with many shallow-and deep-learning-based neural networks.
文摘Enterprise mergers and acquisitions(M&A)are vital strategies for companies worldwide to expand markets,enhance competitiveness,and achieve strategic goals.The Chinese government’s strong support for the new energy industry has created a favorable policy environment for the development of the lithium battery sector.Against this backdrop,Tianqi Lithium Corp’s acquisition of Sociedad Química y Minera(SQM)in Chile has garnered widespread attention.This paper takes Tianqi Lithium Corp’s acquisition of SQM as the research subject,conducting a detailed analysis of the motives behind the M&A.Subsequently,financial indicators are employed to conduct a performance analysis from a financial perspective,examining the impact of the M&A.Finally,based on the findings of the case analysis,relevant suggestions are proposed to offer a reference for the development of enterprise mergers and acquisitions.
基金Supported by the by Research Fund for the Doctoral Program of Higher Education of China(20096121120001)Science Research Program of Educational Commission of Shaanxi Province of China(12JK0781)~~
文摘[Objective] This study aimed to improve classification accuracy of RS images using rough set theory in the growth of crops. [Method] Technique methods of data mining and knowledge discovery have been used. The development status of spatial data mining and knowledge discovery （SDMKD） is presented and data mining techniques in remote sensing were deeply analyzed. Then, SDMKD of TM image are researched using method of rough set, mainly including four methods （rough set, apriori algorithms, inductive learning, clustering）. [Result] The proposed method raises efficiency of land use and land reclaim. Based on the SDMKD, the characteristics of TM showed that the information after using rough set is more intensive than that of none. Especially, much better results can be gained while kinds of corps are less than five. [Conclusion] This study laid significant basis for further research on data mining in the growth of crops.
文摘Chemical engineering has played an important role in the development of petrochemical industry. Some important advances in chemical engineering have been discussed in detail, i. e. petroleum refining, organic chemicals,synthetic resin, synthetic fibers and relevant raw materials, synthetic rubber, and process energy integration. The main business targets of China Petroleum & Chemical Corporation (SINOPEC Corp.) and the focus of further researches are also addressed.
