This paper delves into Agile Development Methods in Software Engineering,contrasting them with the traditional Waterfall model and analyzing their efficiency.Agile methods,known for their adaptability and customer-cen...This paper delves into Agile Development Methods in Software Engineering,contrasting them with the traditional Waterfall model and analyzing their efficiency.Agile methods,known for their adaptability and customer-centric approach,have gained prominence in the fast-paced software development industry.These methods,including Scrum,Kanban,and Extreme Programming(XP),are characterized by iterative cycles,collaborative efforts,and a focus on rapid delivery and quality improvement.The paper compares these agile methodologies to the sequential and rigid Waterfall model,highlighting agile’s superior flexibility,adaptability,and responsiveness to changing requirements.It emphasizes the importance of customer involvement in agile processes,which leads to higher satisfaction and better alignment with user expectations.The analysis reveals that agile methods not only enhance the speed of delivery but also improve the overall quality of the software product.The paper concludes that agile methodologies are more effective in today's dynamic software development environment,providing a robust framework for managing complex projects and ensuring the delivery of high-quality,relevant software solutions.展开更多
Benefiting from the progress of power electronics technology,distributed generation technology is developing rapidly.Since microgrids cannot rely on traditional multi-time scale control strategies to ensure the high-q...Benefiting from the progress of power electronics technology,distributed generation technology is developing rapidly.Since microgrids cannot rely on traditional multi-time scale control strategies to ensure the high-quality frequency stability control and economic dispatch in the same time scale,this paper proposes an extreme dynamic programming algorithm.The proposed algorithm takes an adaptive dynamic programming algorithm as the framework,an extreme learning machine as a kernel of the evaluation module,a model module,an implementation module and a new prediction module.The resulting unified time scale intelligent control algorithm better realizes the combined functions of“droop control+automatic generation control+economic dispatch”in the traditional opermode.Finally,in order to verify the effectiveness of the proposed algorithm,a microgrid model of 8 nodes is simulated.The results confirm the feasibility and validity of the proposed extreme dynamic programming algorithm.展开更多
文摘This paper delves into Agile Development Methods in Software Engineering,contrasting them with the traditional Waterfall model and analyzing their efficiency.Agile methods,known for their adaptability and customer-centric approach,have gained prominence in the fast-paced software development industry.These methods,including Scrum,Kanban,and Extreme Programming(XP),are characterized by iterative cycles,collaborative efforts,and a focus on rapid delivery and quality improvement.The paper compares these agile methodologies to the sequential and rigid Waterfall model,highlighting agile’s superior flexibility,adaptability,and responsiveness to changing requirements.It emphasizes the importance of customer involvement in agile processes,which leads to higher satisfaction and better alignment with user expectations.The analysis reveals that agile methods not only enhance the speed of delivery but also improve the overall quality of the software product.The paper concludes that agile methodologies are more effective in today's dynamic software development environment,providing a robust framework for managing complex projects and ensuring the delivery of high-quality,relevant software solutions.
基金This work was supported in part by the National Natural Science Foundation of China(51777078,51477055).
文摘Benefiting from the progress of power electronics technology,distributed generation technology is developing rapidly.Since microgrids cannot rely on traditional multi-time scale control strategies to ensure the high-quality frequency stability control and economic dispatch in the same time scale,this paper proposes an extreme dynamic programming algorithm.The proposed algorithm takes an adaptive dynamic programming algorithm as the framework,an extreme learning machine as a kernel of the evaluation module,a model module,an implementation module and a new prediction module.The resulting unified time scale intelligent control algorithm better realizes the combined functions of“droop control+automatic generation control+economic dispatch”in the traditional opermode.Finally,in order to verify the effectiveness of the proposed algorithm,a microgrid model of 8 nodes is simulated.The results confirm the feasibility and validity of the proposed extreme dynamic programming algorithm.
