In recent years, it has become possible to accumulate a large amount of browsing history data from users on websites and it is desirable to make use of such data for marketing purposes. In particular, customer browsin...
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In today’s competitive market, product quality holds significant importance for consumers, motivating companies to prioritise high-quality product development and enhance their competitiveness. Acceptance sampling pl...
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While extant research explores the impact of electric vehicle (EV) incentives on EV market shares, less is known about how such policies and other socioeconomic factors interact that ultimately affect the goal of tran...
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This paper considers a well-known two-plan sampling system, Tightened-Normal-Tightened (TNT) sampling scheme, which includes two single sampling plans (SSPs) with regulations for transitioning between tightened and no...
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Dialogue policy learning(DPL)is a key component in a task-oriented dialogue(TOD)*** goal is to decide the next action of the dialogue system,given the dialogue state at each turn based on a learned dialogue *** learni...
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Dialogue policy learning(DPL)is a key component in a task-oriented dialogue(TOD)*** goal is to decide the next action of the dialogue system,given the dialogue state at each turn based on a learned dialogue *** learning(RL)is widely used to optimize this dialogue *** the learning process,the user is regarded as the environment and the system as the *** this paper,we present an overview of the recent advances and challenges in dialogue policy from the perspective of *** specifically,we identify the problems and summarize corresponding solutions for RL-based dialogue policy *** addition,we provide a comprehensive survey of applying RL to DPL by categorizing recent methods into five basic elements in *** believe this survey can shed light on future research in DPL.
This study proposes a conceptual design of green hydrogen production via proton exchange membrane electrolysis powered by a floating solar photovoltaic *** system contributes to industrial decarbonization in which hyd...
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This study proposes a conceptual design of green hydrogen production via proton exchange membrane electrolysis powered by a floating solar photovoltaic *** system contributes to industrial decarbonization in which hydrogen blending with natural gas is proposed as an approach to smooth the energy *** proposed design addresses the challenge of supplying a continuous flow-rate of green hydrogen,which is typically demanded by industrial end *** study particularly considers a realistic area required for the installation of a floating solar photovoltaic *** enable the green hydrogen production of 7.5 million standard cubic feet per day,the required structure includes the floating solar photovoltaic system and Li-ion batteries with the nominal capacities of 518.4 megawatts and 780.8 *** is equivalent to the requirement for 1524765 photovoltaic modules and 3718 Li-ion *** assessment confirms the technical viability of the proposed concept of green hydrogen production,transportation and *** the present commercialization is hindered by economics due to a high green hydrogen production cost of USD 26.95 per kg,this green hydrogen pathway is expected to be competitive with grey hydrogen produced via coal gasification and via natural gas steam reforming by 2043 and 2047,respectively.
Manufacturers must meet high-quality standards and exceed customer expectations to stay competitive due to significant technological advancements in recent decades. While implementing the yield measure is useful for a...
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In modern global supply chain system strategies, the importance of risk management to prevent disruption thereto is increasing. One efficient approach for overcoming this problem is a collaboration between manufacture...
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To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage a...
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To enhance the performance of the prediction intervals (PIs), a novel very short-term probabilistic prediction method for wind speed via nonlinear quantile regression (NQR) based on adaptive least absolute shrinkage and selection operator (ALASSO) and integrated criterion (IC) is proposed. The ALASSO method is studied for shrinkage of output weights and selection of variables. Furthermore, for the better performance of PIs, composite weighted linear programming (CWLP) is proposed to modify the conventional linear programming cost function of quantile regression (QR), by combining it with Bayesian information criterion (BIC) as an IC to optimize the coefficients of PIs. Then, the multiple fold cross model (MFCM) is utilized to improve the PIs performance. Multistep probabilistic prediction of 15-minute wind speed is performed based on the real wind farm data from the northeast of China. The effectiveness of the proposed approach is validated through the performances' comparisons with conventional methods.
Electric vehicle battery recycling has emerged as a critical process in transitioning to sustainable transportation. As the demand for electric vehicles continues to rise, so does the need to address the end-of-life m...
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