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COP 28: Challenge of coping with climate crisis
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作者 Tong Jiang Xiaojia He +4 位作者 Buda Su Peni Hausia Havea Ke Wei Zbigniew W.Kundzewicz Dong Liu 《The Innovation》 EI 2024年第1期21-22,共2页
The 28th Conference of Parties(COP 28)of the United Nations Framework Convention on Climate Change(UNFCCC)is being held in Dubai,United Arab Emirates,from November 30 to December 12,2023,with the participation of over... The 28th Conference of Parties(COP 28)of the United Nations Framework Convention on Climate Change(UNFCCC)is being held in Dubai,United Arab Emirates,from November 30 to December 12,2023,with the participation of over 160 world leaders(Figure 1).The tone of the COP 28 is set by the observation that,clearly,the nationally determined contributions related to CO_(2) emission reduction are not on track to curb the temperature rise as per the Paris Agreement.In order to hold the increase in global mean temperature to well below 2℃ above the pre-industrial level and to pursue efforts to limit the warming to 1.5℃,there is a need for ratcheting up ambition for near-term climate action. 展开更多
关键词 FIGURE LIMIT COP
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Decision Model for Market of Performing Arts with Factorization Machine
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作者 徐勇 唐倩 +1 位作者 侯林早 李冕 《Journal of Shanghai Jiaotong university(Science)》 EI 2018年第1期74-84,共11页
Performing arts and movies have become commercial products with high profit and great market potential. Previous research works have developed comprehensive models to forecast the demand for movies. However,they did n... Performing arts and movies have become commercial products with high profit and great market potential. Previous research works have developed comprehensive models to forecast the demand for movies. However,they did not pay enough attention to the decision support for performing arts which is a special category unlike movies. For performing arts with high-dimensional categorical attributes and limit samples, determining ticket prices in different levels is still a challenge job faced by the producers and distributors. In terms of these difficulties, factorization machine(FM), which can handle huge sparse categorical attributes, is used in this work first. Adaptive stochastic gradient descent(ASGD) and Markov chain Monte Carlo(MCMC) are both explored to estimate the model parameters of FM. FM with ASGD(FM-ASGD) and FM with MCMC(FM-MCMC) both can achieve a better prediction accuracy, compared with a traditional algorithm. In addition, the multi-output model is proposed to determine the price in multiple price levels simultaneously, which avoids the trouble of the models' repeating training. The results also confirm the prediction accuracy of the multi-output model, compared with those from the general single-output model. 展开更多
关键词 performing arts factorization machine(FM) Markov chain Monte Carlo(MCMC) adaptive stochastic gradient descent(ASGD)
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