Collection
Computer Science SDG 7: Affordable and Clean Energy
This collection compiles papers from across the Springer computer science portfolio which relate to SDG 7, Affordable and Clean Energy. Read more about the Springer Sustainable Development Goals Program here.
Articles (1246 in this collection)
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Learning team-based navigation: a review of deep reinforcement learning techniques for multi-agent pathfinding
Authors (first, second and last of 4)
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NeuralGLS: learning to guide local search with graph convolutional network for the traveling salesman problem
Authors (first, second and last of 5)
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Energy efficient power cap configurations through Pareto front analysis and machine learning categorization
Authors (first, second and last of 5)
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A maneuvering target tracking based on fastIMM-extended Viterbi algorithm
Authors (first, second and last of 8)
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Monitoring and analyzing as a service (MAaaS) through cloud edge based on intelligent transportation applications
Authors (first, second and last of 4)
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A collaborative ledger storing model for lightweight blockchains based on Chord Ring
Authors (first, second and last of 4)
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ARO-RTP: Performance analysis of an energy efficient opportunistic routing for underwater IoT networks
Authors (first, second and last of 4)
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Joint optimization of energy and delay for computation offloading in vehicular edge computing
Authors
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An optimal task scheduling method in IoT-Fog-Cloud network using multi-objective moth-flame algorithm
Authors (first, second and last of 7)
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Energy data classification at the edge: a comparative study for energy efficiency applications
Authors (first, second and last of 4)
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EMCP: evolutionary multi-objective clustering protocol for prolonged lifetime of heterogeneous IoT networks
Authors (first, second and last of 4)
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Public sentiment toward renewable energy in Morocco: opinion mining using a rule-based approach
Authors (first, second and last of 6)
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I/O-signature-based feature analysis and classification of high-performance computing applications
Authors (first, second and last of 4)
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Performance analysis of neural network-based unified physical layer for indoor hybrid LiFi–WiFi flying networks
Authors (first, second and last of 5)
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Surrogate gradient scaling for directly training spiking neural networks
Authors (first, second and last of 5)
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Joint DNN partitioning and resource allocation for completion rate maximization of delay-aware DNN inference tasks in wireless powered mobile edge computing
Authors (first, second and last of 4)
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Joint optimization of IoT devices access and bandwidth resource allocation for network slicing in edge-enabled radio access networks
Authors (first, second and last of 4)
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Research on electric energy information acquisition system based on embedded platform
Authors (first, second and last of 5)
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Long-term prediction of daily solar irradiance using Bayesian deep learning and climate simulation data
Authors (first, second and last of 5)
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Automated construction management platform with image analysis using deep learning neural networks
Authors (first, second and last of 6)
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A novel energy-efficient adaptive superframe structure for OWC-based real-time bio-sensor networks
Authors
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Electric charging station management using IoT and cloud computing framework for sustainable green transportation
Authors (first, second and last of 6)
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Performance benchmark of deep learning human pose estimation for UAVs
Authors (first, second and last of 4)
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Security in internet of things: a review on approaches based on blockchain, machine learning, cryptography, and quantum computing
Authors (first, second and last of 5)
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A lightweight vehicle mounted multi-scale traffic sign detector using attention fusion pyramid
Authors (first, second and last of 7)
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Deep Learning Based Hybrid Intrusion Detection Systems to Protect Satellite Networks
Authors (first, second and last of 5)
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A Novel Ensemble-Learning-Based Convolution Neural Network for Handling Imbalanced Data
Authors (first, second and last of 5)
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A study on the placement of photovoltaic units in the North and South of Vietnam for energy loss reduction by using a proposed slime mould algorithm
Authors (first, second and last of 4)
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Energy load forecasting: one-step ahead hybrid model utilizing ensembling
Authors (first, second and last of 5)
