A novel reinforcement learning-based multi-operator differential evolution with cubic spline for the path planning problem
Sign Up to like & getrecommendations! Published in 2025 at "Artificial Intelligence Review"
DOI: 10.1007/s10462-025-11129-6
Abstract: Path planning in autonomous driving systems remains a critical challenge, requiring algorithms capable of generating safe, efficient, and reliable routes. Existing state-of-the-art methods, including graph-based and sampling-based approaches, often produce sharp, suboptimal paths and struggle… read more here.
Keywords: path planning; path; operator differential; differential evolution ... See more keywords
A novel hybrid multi operator evolutionary algorithm for dynamic distributed generation optimization and optimal feeder reconfiguration
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-17776-7
Abstract: This study addresses the integration of distributed generations (DG) and network reconfiguration in distribution networks, that has not been thoroughly investigated in prior research. The importance of technical objectives, such as power loss, voltage deviation,… read more here.
Keywords: hybrid multi; voltage; reconfiguration; optimization ... See more keywords
Multi operator-stable random measures and fields
Sign Up to like & getrecommendations! Published in 2019 at "Stochastic Models"
DOI: 10.1080/15326349.2019.1618714
Abstract: Abstract In this paper we construct vector-valued multi operator-stable random measures that behave locally like operator-stable random measures. The space of integrable functions is characterized in terms of a certain quasi-norm. Moreover, a multi operator-stable… read more here.
Keywords: operator stable; random measures; stable random; multi operator ... See more keywords
Multi-Operator Network Sharing for Massive IoT
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Communications Magazine"
DOI: 10.1109/mcom.2019.1800272
Abstract: A recent study predicts that by 2020, up to 50 billion Internet of Things (IoT) devices will be connected to the Internet, straining the capacity of the wireless infrastructure, which has already been overloaded with… read more here.
Keywords: network sharing; operator network; iot; network ... See more keywords
Multi-operator-based model-driven self-supervised learning for fluorescence diffusion tomography.
Sign Up to like & getrecommendations! Published in 2025 at "Optics letters"
DOI: 10.1364/ol.572740
Abstract: Supervised learning's reliance on high-fidelity labeled data limits its application in fluorescence diffusion tomography (FDT). Here, we propose a multi-operator-based model-driven self-supervised learning (MMSL) for FDT to eliminate the need for labeled data. Our approach… read more here.
Keywords: supervised learning; operator based; fluorescence diffusion; model ... See more keywords