A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is...A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is used to identifying which active session a request should belong to. The competitive method is applied to determine the end of the sessions. Compared with other algorithms, more successful sessions are additionally detected by semantic outlier analysis.展开更多
The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station pe...The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station performance by analyzing power consumption efficiency,station utilization rates,no-power session occurrences,and CO_(2)reduction metrics.A dataset of 17,500 charging sessions from 305 stations across a regional network was analyzed to identify operational inefficiencies and opportunities for infrastructure optimization.Results indicate a strong correlation between station utilization and energy efficiency,highlighting the importance of strategic station placement.The findings also emphasize the impact of no-power sessions on network inefficiency and the need for real-time station monitoring.CO_(2)reduction analysis demonstrates that optimizing EV charging performance can significantly contribute to sustainability goals.Based on these insights,this study recommends the implementation of predictive maintenance strategies,real-time user notifications,and diversified provider networks to improve station availability and efficiency.The proposed data-driven framework offers actionable solutions for policymakers,charging network operators,and urban planners to enhance EV infrastructure reliability and sustainability.展开更多
基金Supported by the Huo Yingdong Education Foundation of China(91101)
文摘A semantic session analysis method partitioning Web usage logs is presented. Semantic Web usage log preparation model enhances usage logs with semantic. The Markov chain model based on ontology semantic measurement is used to identifying which active session a request should belong to. The competitive method is applied to determine the end of the sessions. Compared with other algorithms, more successful sessions are additionally detected by semantic outlier analysis.
文摘The increasing global adoption of electric vehicles(EVs)has led to a growing demand for a cost-effective and reliable charging infrastructure.This study presents a novel data-driven approach to assessing EV station performance by analyzing power consumption efficiency,station utilization rates,no-power session occurrences,and CO_(2)reduction metrics.A dataset of 17,500 charging sessions from 305 stations across a regional network was analyzed to identify operational inefficiencies and opportunities for infrastructure optimization.Results indicate a strong correlation between station utilization and energy efficiency,highlighting the importance of strategic station placement.The findings also emphasize the impact of no-power sessions on network inefficiency and the need for real-time station monitoring.CO_(2)reduction analysis demonstrates that optimizing EV charging performance can significantly contribute to sustainability goals.Based on these insights,this study recommends the implementation of predictive maintenance strategies,real-time user notifications,and diversified provider networks to improve station availability and efficiency.The proposed data-driven framework offers actionable solutions for policymakers,charging network operators,and urban planners to enhance EV infrastructure reliability and sustainability.
