A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block mode...A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the Dynamic Programming Model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynamic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Programming Model can also be conveniently realized in computer.展开更多
Margaret Atwood is a Canadian author of more than thirty-five books and the winner of prestigious literary prizes,such as the Booker Prize,the Giller Prize,and the Governor General's Award.Her influence on Canadia...Margaret Atwood is a Canadian author of more than thirty-five books and the winner of prestigious literary prizes,such as the Booker Prize,the Giller Prize,and the Governor General's Award.Her influence on Canadian literature and contemporary literature as a whole is phenomenal.Nevertheless,little is known with respect to how Atwood represents animals covering the full range of her novels.This paper reports on the analysis of animal representations in Atwood's seventeen novels through Python programming and close reading under the framework of a new semiotic research finding,a pan-indexicality model within the context of literature and the environment.This study investigates the frequencies of animal vocabulary in the seventeen novels,the changes of animal representations in her novels before 1990s and after 1990s,and the implication of the ever-changing animal representations during the fty years.This paper concludes that nonhuman animal descriptions in Atwood's novels of 1970s and 1980s run at a high level and decrease in her novels of 1990s,while scientific animal descriptions increase in her novels of 2000s and 2010s.Nonhuman animals in her novels of 1970s and 1980s are instrumentalized as a vehicle for indigenization and national individuation from the United States,and scientific animals in her novels of 2000s and 2010s are instrumentalized in the service of environmental apocalypticism.This study suggests that the pan-indexicality model can be employed to understand the meaning of signs in literature and the environment from the perspective of authorial intention,with reference to authors'encyclopedic knowledge,personal experience,social,and cultural background information.展开更多
近年来,随着人工智能技术的发展,许多编程人员期望计算机代替他们自动完成程序代码或者代码注释的编写等任务。跨自然语言与程序语言(Natural languages and programming languages, NL-PL)生成即为此类任务,指自然语言和程序语言之间...近年来,随着人工智能技术的发展,许多编程人员期望计算机代替他们自动完成程序代码或者代码注释的编写等任务。跨自然语言与程序语言(Natural languages and programming languages, NL-PL)生成即为此类任务,指自然语言和程序语言之间的相互转换任务,包括自然语言到程序语言的生成和程序语言到自然语言的生成两类任务。最近几年,跨NL-PL生成在研究与应用方面呈现出爆发式的增长,尤其是随着深度学习(Deep learning,DL)技术的发展,越来越多研究人员开始利用DL技术来提升跨NL-PL生成任务效果。他们通过优化程序表示方式、改进神经网络模型以及设计大型预训练模型等方法,在该领域取得了众多突破性的进展。在基于DL的跨NL-PL生成技术获得迅猛发展的同时,大型互联网公司逐渐将该领域的研究成果付诸商用,因此,模型应用安全性也受到了学术界和业界的紧密关注。为了进一步系统地研究跨NL-PL生成技术,对这些已有的成果进行梳理非常必要。本文以程序生成和注释生成这两类典型跨NL-PL生成任务为切入点,对该领域具有代表性的最新文献进行归纳总结。我们从众多已有参考文献中抽象出一个基于DL的跨NL-PL生成通用实现模型,并将该模型划分为程序表示、语言处理和语言生成三大组件。在我们提出的通用实现模型的基础上,我们进一步从程序代码表示方法、网络模型结构、模型在业界的应用、应用过程中存在的安全问题与安全研究现状、该领域常用数据集和模型效果等方面详细梳理分析已有研究成果及进展脉络。最后,我们总结了该领域现阶段存在的研究问题,并展望了未来的发展方向。展开更多
This paper presents an expert-based fuzzy analytic hierarchy process( AHP) model for evaluating emergency response capacity of Chemical Industrial Park( ERCCIP) by jointly using an improved fuzzy preference programmin...This paper presents an expert-based fuzzy analytic hierarchy process( AHP) model for evaluating emergency response capacity of Chemical Industrial Park( ERCCIP) by jointly using an improved fuzzy preference programming( FPP) and 2-tuple fuzzy linguistic approach. An evaluation index system for ERCCIP is proposed. The weight of sub-criteria and criteria of the evaluation index system for ERCCIP are determined using the improved FPP. And the ratings of sub-criteria are assessed in linguistic values according to the experts' subjective opinions. Finally,the aggregated ratings of criteria and the overall ERCCIP are calculated.展开更多
Wind power prediction interval(WPPI)models in the literature have predominantly been developed for and tested on specific case studies.However,wind behavior and characteristics can vary significantly across regions.Th...Wind power prediction interval(WPPI)models in the literature have predominantly been developed for and tested on specific case studies.However,wind behavior and characteristics can vary significantly across regions.Thus,a prediction model that performs well in one case might underperform in another.To address this shortcoming,this paper proposes an ensemble WPPI framework that integrates multiple WPPI models with distinct characteristics to improve robustness.Another important and often overlooked factor is the role of probabilistic wind power prediction(WPP)in quantifying wind power uncertainty,which should be handled by operating reserve.Operating reserve in WPPI frameworks enhances the efficacy of WPP.In this regard,the proposed framework employs a novel bi-layer optimization approach that takes both WPPI quality and reserve requirements into account.Comprehensive analysis with different real-world datasets and various benchmark models validates the quality of the obtained WPPIs while resulting in more optimal reserve requirements.展开更多
文摘A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the Dynamic Programming Model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynamic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Programming Model can also be conveniently realized in computer.
基金supported by a fund from 2023 Foreign Language Elite Project of Social Science Research in Jiangsu Province(Award reference:23swB-22)a fund from Social Science Foundation of Soochow University(Award reference:NH33711320)a fund from Teaching Reform Foundation of Soochow College 2023.
文摘Margaret Atwood is a Canadian author of more than thirty-five books and the winner of prestigious literary prizes,such as the Booker Prize,the Giller Prize,and the Governor General's Award.Her influence on Canadian literature and contemporary literature as a whole is phenomenal.Nevertheless,little is known with respect to how Atwood represents animals covering the full range of her novels.This paper reports on the analysis of animal representations in Atwood's seventeen novels through Python programming and close reading under the framework of a new semiotic research finding,a pan-indexicality model within the context of literature and the environment.This study investigates the frequencies of animal vocabulary in the seventeen novels,the changes of animal representations in her novels before 1990s and after 1990s,and the implication of the ever-changing animal representations during the fty years.This paper concludes that nonhuman animal descriptions in Atwood's novels of 1970s and 1980s run at a high level and decrease in her novels of 1990s,while scientific animal descriptions increase in her novels of 2000s and 2010s.Nonhuman animals in her novels of 1970s and 1980s are instrumentalized as a vehicle for indigenization and national individuation from the United States,and scientific animals in her novels of 2000s and 2010s are instrumentalized in the service of environmental apocalypticism.This study suggests that the pan-indexicality model can be employed to understand the meaning of signs in literature and the environment from the perspective of authorial intention,with reference to authors'encyclopedic knowledge,personal experience,social,and cultural background information.
文摘近年来,随着人工智能技术的发展,许多编程人员期望计算机代替他们自动完成程序代码或者代码注释的编写等任务。跨自然语言与程序语言(Natural languages and programming languages, NL-PL)生成即为此类任务,指自然语言和程序语言之间的相互转换任务,包括自然语言到程序语言的生成和程序语言到自然语言的生成两类任务。最近几年,跨NL-PL生成在研究与应用方面呈现出爆发式的增长,尤其是随着深度学习(Deep learning,DL)技术的发展,越来越多研究人员开始利用DL技术来提升跨NL-PL生成任务效果。他们通过优化程序表示方式、改进神经网络模型以及设计大型预训练模型等方法,在该领域取得了众多突破性的进展。在基于DL的跨NL-PL生成技术获得迅猛发展的同时,大型互联网公司逐渐将该领域的研究成果付诸商用,因此,模型应用安全性也受到了学术界和业界的紧密关注。为了进一步系统地研究跨NL-PL生成技术,对这些已有的成果进行梳理非常必要。本文以程序生成和注释生成这两类典型跨NL-PL生成任务为切入点,对该领域具有代表性的最新文献进行归纳总结。我们从众多已有参考文献中抽象出一个基于DL的跨NL-PL生成通用实现模型,并将该模型划分为程序表示、语言处理和语言生成三大组件。在我们提出的通用实现模型的基础上,我们进一步从程序代码表示方法、网络模型结构、模型在业界的应用、应用过程中存在的安全问题与安全研究现状、该领域常用数据集和模型效果等方面详细梳理分析已有研究成果及进展脉络。最后,我们总结了该领域现阶段存在的研究问题,并展望了未来的发展方向。
基金Sponsored by the National Natural Science Foundation of China(Grant No.41001354)Fundamental Research Funds for the Central Universities of China(Grant No.23420110083)
文摘This paper presents an expert-based fuzzy analytic hierarchy process( AHP) model for evaluating emergency response capacity of Chemical Industrial Park( ERCCIP) by jointly using an improved fuzzy preference programming( FPP) and 2-tuple fuzzy linguistic approach. An evaluation index system for ERCCIP is proposed. The weight of sub-criteria and criteria of the evaluation index system for ERCCIP are determined using the improved FPP. And the ratings of sub-criteria are assessed in linguistic values according to the experts' subjective opinions. Finally,the aggregated ratings of criteria and the overall ERCCIP are calculated.
基金supported in part by the Natural Sciences and Engineering Research Council(NSERC)of Canada and the Saskatchewan Power Corporation(SaskPower).
文摘Wind power prediction interval(WPPI)models in the literature have predominantly been developed for and tested on specific case studies.However,wind behavior and characteristics can vary significantly across regions.Thus,a prediction model that performs well in one case might underperform in another.To address this shortcoming,this paper proposes an ensemble WPPI framework that integrates multiple WPPI models with distinct characteristics to improve robustness.Another important and often overlooked factor is the role of probabilistic wind power prediction(WPP)in quantifying wind power uncertainty,which should be handled by operating reserve.Operating reserve in WPPI frameworks enhances the efficacy of WPP.In this regard,the proposed framework employs a novel bi-layer optimization approach that takes both WPPI quality and reserve requirements into account.Comprehensive analysis with different real-world datasets and various benchmark models validates the quality of the obtained WPPIs while resulting in more optimal reserve requirements.
