Software engineering＇s lifecycle models havc proven to be very important for traditional software development. However, can these models be applied to the development of Web-based applications as well？ In recent yea...Software engineering＇s lifecycle models havc proven to be very important for traditional software development. However, can these models be applied to the development of Web-based applications as well？ In recent years, Web-based applications have become more and more complicated and a lot of efforts have been placed on introducing new technologies such as J2EE, PhP, and .NET, etc., which have been universally accepted as the development technologies for Web-based applications. However, there is no universally accepted process model for the development of Web-based applications. Moreover, shaping the process model for small medium-sized enterprises （SMEs）, which have limited resources, has been relatively neglected. Based on our previous work, this paper presents an expanded lifecycle process model for the development of Web-based applications in SMEs. It consists of three sets of processes, i.e., requirement processes, development processes, and evolution processes. Particularly, the post-delivery evolution processes are important to SMEs to develop and maintain quality web applications with limited resources and time.展开更多
With the rapid adoption of artificial intelligence(AI)in domains such as power,transportation,and finance,the number of machine learning and deep learning models has grown exponentially.However,challenges such as dela...With the rapid adoption of artificial intelligence(AI)in domains such as power,transportation,and finance,the number of machine learning and deep learning models has grown exponentially.However,challenges such as delayed retraining,inconsistent version management,insufficient drift monitoring,and limited data security still hinder efficient and reliable model operations.To address these issues,this paper proposes the Intelligent Model Lifecycle Management Algorithm(IMLMA).The algorithm employs a dual-trigger mechanism based on both data volume thresholds and time intervals to automate retraining,and applies Bayesian optimization for adaptive hyperparameter tuning to improve performance.A multi-metric replacement strategy,incorporating MSE,MAE,and R2,ensures that new models replace existing ones only when performance improvements are guaranteed.A versioning and traceability database supports comparison and visualization,while real-time monitoring with stability analysis enables early warnings of latency and drift.Finally,hash-based integrity checks secure both model files and datasets.Experimental validation in a power metering operation scenario demonstrates that IMLMA reduces model update delays,enhances predictive accuracy and stability,and maintains low latency under high concurrency.This work provides a practical,reusable,and scalable solution for intelligent model lifecycle management,with broad applicability to complex systems such as smart grids.展开更多
文摘Software engineering＇s lifecycle models havc proven to be very important for traditional software development. However, can these models be applied to the development of Web-based applications as well？ In recent years, Web-based applications have become more and more complicated and a lot of efforts have been placed on introducing new technologies such as J2EE, PhP, and .NET, etc., which have been universally accepted as the development technologies for Web-based applications. However, there is no universally accepted process model for the development of Web-based applications. Moreover, shaping the process model for small medium-sized enterprises （SMEs）, which have limited resources, has been relatively neglected. Based on our previous work, this paper presents an expanded lifecycle process model for the development of Web-based applications in SMEs. It consists of three sets of processes, i.e., requirement processes, development processes, and evolution processes. Particularly, the post-delivery evolution processes are important to SMEs to develop and maintain quality web applications with limited resources and time.
基金funded by Anhui NARI ZT Electric Co.,Ltd.,entitled“Research on the Shared Operation and Maintenance Service Model for Metering Equipment and Platform Development for the Modern Industrial Chain”(Grant No.524636250005).
文摘With the rapid adoption of artificial intelligence(AI)in domains such as power,transportation,and finance,the number of machine learning and deep learning models has grown exponentially.However,challenges such as delayed retraining,inconsistent version management,insufficient drift monitoring,and limited data security still hinder efficient and reliable model operations.To address these issues,this paper proposes the Intelligent Model Lifecycle Management Algorithm(IMLMA).The algorithm employs a dual-trigger mechanism based on both data volume thresholds and time intervals to automate retraining,and applies Bayesian optimization for adaptive hyperparameter tuning to improve performance.A multi-metric replacement strategy,incorporating MSE,MAE,and R2,ensures that new models replace existing ones only when performance improvements are guaranteed.A versioning and traceability database supports comparison and visualization,while real-time monitoring with stability analysis enables early warnings of latency and drift.Finally,hash-based integrity checks secure both model files and datasets.Experimental validation in a power metering operation scenario demonstrates that IMLMA reduces model update delays,enhances predictive accuracy and stability,and maintains low latency under high concurrency.This work provides a practical,reusable,and scalable solution for intelligent model lifecycle management,with broad applicability to complex systems such as smart grids.
