Research on load-balanced construction algorithm of logical carrying network by Hao-xue WANG, Ming JIANG, Ji FU

“…To improve the extensibility of network service,constructing algorithm of logical carrying network was pro-posed by mapping the demands of network service into substrate network.To solve the problem of construction efficiency,on-demand carrying strategy was introduced to provide different resources to meet different service requirements.Based on available resource and current link load,an improved multi-commodity flow model was proposed to compute the re-source allocation.Simulation results indicate this al ithm can improve network service capability from construction success rate and average construction profit.…”
Get full text

Initialization Methods for FPGA-Based EMT Simulations by Xin Ma, Xiao-Ping Zhang

Get full text

From Concept to Market: Ensemble Predictive Model for Research Project Crowdfunding Readiness by Andreea Cristina Ionica, Stanislav Cseminschi, Monica Leba

Get full text

Deep reinforcement learning based resource provisioning for federated edge learning by Xingyun Chen, Junjie Pang, Tonghui Sun

“…The MFLD algorithm leverages Deep Reinforcement Learning (DRL) techniques to automatically select UEs and allocate the computation resources according to the task requirement. …”
Get full text

Electricity pinch analysis method for flexibility supply-demand matching in power systems by Yaling Mao, Tiejiang Yuan, Xueqin Tian, Yue Teng

“…First, the net-load profile is decomposed by successive variational mode decomposition (SVMD) optimized with the Red-billed Blue Magpie Optimization (RBMO) algorithm to construct a flexibility demand model. …”
Get full text

Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. …”
Get full text