The rapid development of artificial intelligence(AI)technology in today’s society has brought varying degrees of influence to various industries and fields,and this transformation is also playing a profound role in t...The rapid development of artificial intelligence(AI)technology in today’s society has brought varying degrees of influence to various industries and fields,and this transformation is also playing a profound role in the field of education.This paper intends to analyze the social background,cultural background,and policy background of introducing AI technology into the primary school music education system,deeply explore the important value and practical path of applying AI technology in the field of primary school music education,and provide corresponding optimization strategies for teaching,with a view to providing some theoretical references for promoting the in-depth integration of AI and primary school music education.展开更多
The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this wor...The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.展开更多
文摘The rapid development of artificial intelligence(AI)technology in today’s society has brought varying degrees of influence to various industries and fields,and this transformation is also playing a profound role in the field of education.This paper intends to analyze the social background,cultural background,and policy background of introducing AI technology into the primary school music education system,deeply explore the important value and practical path of applying AI technology in the field of primary school music education,and provide corresponding optimization strategies for teaching,with a view to providing some theoretical references for promoting the in-depth integration of AI and primary school music education.
基金Projects(61573144,61773165,61673175,61174040)supported by the National Natural Science Foundation of ChinaProject(222201717006)supported by the Fundamental Research Funds for the Central Universities,China
文摘The hybrid flow shop scheduling problem with unrelated parallel machine is a typical NP-hard combinatorial optimization problem, and it exists widely in chemical, manufacturing and pharmaceutical industry. In this work, a novel mathematic model for the hybrid flow shop scheduling problem with unrelated parallel machine(HFSPUPM) was proposed. Additionally, an effective hybrid estimation of distribution algorithm was proposed to solve the HFSPUPM, taking advantage of the features in the mathematic model. In the optimization algorithm, a new individual representation method was adopted. The(EDA) structure was used for global search while the teaching learning based optimization(TLBO) strategy was used for local search. Based on the structure of the HFSPUPM, this work presents a series of discrete operations. Simulation results show the effectiveness of the proposed hybrid algorithm compared with other algorithms.
