| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services
|
Zhang, Caizhi
|
|
|
|
C |
p.
|
artikel
|
| 2 |
A Conditional Generative adversarial Network for energy use in multiple buildings using scarce data
|
Baasch, Gaby
|
|
|
|
C |
p.
|
artikel
|
| 3 |
A co-training style semi-supervised artificial neural network modeling and its application in thermal conductivity prediction of polymeric composites filled with BN sheets
|
Liang, Yunmin
|
|
|
|
C |
p.
|
artikel
|
| 4 |
Adaptive meta-learning extreme learning machine with golden eagle optimization and logistic map for forecasting the incomplete data of solar irradiance
|
Boriratrit, Sarunyoo
|
|
|
|
C |
p.
|
artikel
|
| 5 |
A data-driven approach for predicting long-term degradation of a fleet of micro gas turbines
|
Olsson, Tomas
|
|
|
|
C |
p.
|
artikel
|
| 6 |
A data-driven approach using machine learning for early detection of the lean blowout
|
Hasti, Veeraraghava Raju
|
|
|
|
C |
p.
|
artikel
|
| 7 |
A data-driven reduced-order model for stiff chemical kinetics using dynamics-informed training
|
Vijayarangan, Vijayamanikandan
|
|
|
|
C |
p.
|
artikel
|
| 8 |
A deep neural network based model for the prediction of hybrid electric vehicles carbon dioxide emissions
|
Maino, Claudio
|
|
|
|
C |
p.
|
artikel
|
| 9 |
A 3D indicator for guiding AI applications in the energy sector
|
Quest, Hugo
|
|
|
|
C |
p.
|
artikel
|
| 10 |
Advances of machine learning in multi-energy district communities‒ mechanisms, applications and perspectives
|
Zhou, Yuekuan
|
|
|
|
C |
p.
|
artikel
|
| 11 |
A general model for flow boiling heat transfer in microfin tubes based on a new neural network architecture
|
Lin, Lingnan
|
|
|
|
C |
p.
|
artikel
|
| 12 |
A generative adversarial network (GAN) approach to creating synthetic flame images from experimental data
|
Carreon, Anthony
|
|
|
|
C |
p.
|
artikel
|
| 13 |
A goal-oriented Design Method of CO2 Power Cycle (CPC) System
|
Zuo, Qiyao
|
|
|
|
C |
p.
|
artikel
|
| 14 |
A hybrid policy gradient and rule-based control framework for electric vehicle charging
|
Mbuwir, Brida V.
|
|
|
|
C |
p.
|
artikel
|
| 15 |
AI and freedom for evolution in energy science
|
Bejan, Adrian
|
|
|
|
C |
p.
|
artikel
|
| 16 |
AI-Assisted approach for building energy and carbon footprint modeling
|
Chen, Chih-Yen
|
|
|
|
C |
p.
|
artikel
|
| 17 |
AI-enabled materials discovery for advanced ceramic electrochemical cells
|
Bello, Idris Temitope
|
|
|
|
C |
p.
|
artikel
|
| 18 |
A machine learning framework for remaining useful lifetime prediction of li-ion batteries using diverse neural networks
|
Lee, Junghwan
|
|
|
|
C |
p.
|
artikel
|
| 19 |
A modeling and experimental study of capacity fade for lithium-ion batteries
|
Carnovale, Andrew
|
|
|
|
C |
p.
|
artikel
|
| 20 |
Analysis of PEM and AEM electrolysis by neural network pattern recognition, association rule mining and LIME
|
Günay, M. Erdem
|
|
|
|
C |
p.
|
artikel
|
| 21 |
A new hybrid AI optimal management method for renewable energy communities
|
Conte, Francesco
|
|
|
|
C |
p.
|
artikel
|
| 22 |
An explainable AI framework for robust and transparent data-driven wind turbine power curve models
|
Letzgus, Simon
|
|
|
|
C |
p.
|
artikel
|
| 23 |
An explainable AI model for power plant NOx emission control
|
Zhou, Yuanye
|
|
|
|
C |
p.
|
artikel
|
| 24 |
An introduction to multivariate probabilistic forecast evaluation
|
Bjerregård, Mathias Blicher
|
|
|
|
C |
p.
|
artikel
|
| 25 |
A novel combined multi-battery dataset based approach for enhanced prediction accuracy of data driven prognostic models in capacity estimation of lithium ion batteries
|
Nagulapati, Vijay Mohan
|
|
|
|
C |
p.
|
artikel
|
| 26 |
A novel feature susceptibility approach for a PEMFC control system based on an improved XGBoost-Boruta algorithm
|
Yuan, Xinjie
|
|
|
|
C |
p.
|
artikel
|
| 27 |
Application of Machine Learning in Optimizing Proton Exchange Membrane Fuel Cells: A Review
|
Ding, Rui
|
|
|
|
C |
p.
|
artikel
|
| 28 |
Application of machine learning to develop a real-time air-cooled condenser monitoring platform using thermofluid simulation data
|
Haffejee, Rashid A.
|
|
|
|
C |
p.
|
artikel
|
| 29 |
Application of self-adaptive temperature recognition in cold-start of an air-cooled proton exchange membrane fuel cell stack
|
Yu, Xianxian
|
|
|
|
C |
p.
|
artikel
|
| 30 |
Applications of AI in advanced energy storage technologies
|
Xiong, Rui
|
|
|
|
C |
p.
|
artikel
|
| 31 |
Applying artificial neural network to predict the viscosity of microalgae slurry in hydrothermal hydrolysis process
|
Chen, Hao
|
|
|
|
C |
p.
|
artikel
|
| 32 |
Applying machine learning techniques to predict detonation initiation from hot spots
|
Ryu, Je Ir
|
|
|
|
C |
p.
|
artikel
|
| 33 |
Applying machine learning techniques to predict laminar burning velocity for ammonia/hydrogen/air mixtures
|
Üstün, Cihat Emre
|
|
|
|
C |
p.
|
artikel
|
| 34 |
Approximating multi-purpose AC Optimal Power Flow with reinforcement trained Artificial Neural Network
|
Wang, Zhenqi
|
|
|
|
C |
p.
|
artikel
|
| 35 |
A Reinforcement Learning approach for the continuous electricity market of Germany: Trading from the perspective of a wind park operator
|
Lehna, Malte
|
|
|
|
C |
p.
|
artikel
|
| 36 |
A review and taxonomy of wind and solar energy forecasting methods based on deep learning
|
Alkhayat, Ghadah
|
|
|
|
C |
p.
|
artikel
|
| 37 |
A review: Challenges and opportunities for artificial intelligence and robotics in the offshore wind sector
|
Mitchell, Daniel
|
|
|
|
C |
p.
|
artikel
|
| 38 |
A Review of physics-based and data-driven models for real-time control of polymer electrolyte membrane fuel cells
|
Zhao, Jian
|
|
|
|
C |
p.
|
artikel
|
| 39 |
A review on 5G technology for smart energy management and smart buildings in Singapore
|
Huseien, Ghasan Fahim
|
|
|
|
C |
p.
|
artikel
|
| 40 |
A robust autoregressive long-term spatiotemporal forecasting framework for surrogate-based turbulent combustion modeling via deep learning
|
Wu, Sipei
|
|
|
|
C |
p.
|
artikel
|
| 41 |
Artificial intelligence application in a renewable energy-driven desalination system: A critical review
|
He, Qian
|
|
|
|
C |
p.
|
artikel
|
| 42 |
Artificial intelligence in oil and gas upstream: Trends, challenges, and scenarios for the future
|
Koroteev, Dmitry
|
|
|
|
C |
p.
|
artikel
|
| 43 |
Artificial intelligence in renewable systems for transformation towards intelligent buildings
|
Zhou, Yuekuan
|
|
|
|
C |
p.
|
artikel
|
| 44 |
Artificial intelligence powered large-scale renewable integrations in multi-energy systems for carbon neutrality transition: Challenges and future perspectives
|
Liu, Zhengxuan
|
|
|
|
C |
p.
|
artikel
|
| 45 |
Artificial neural network aided real-time simulation of electric traction system
|
Bai, Hao
|
|
|
|
C |
p.
|
artikel
|
| 46 |
Artificial neural network based optimization of a six-step two-bed pressure swing adsorption system for hydrogen purification
|
Tong, Liang
|
|
|
|
C |
p.
|
artikel
|
| 47 |
Autoencoder-based anomaly root cause analysis for wind turbines
|
Roelofs, Cyriana M.A.
|
|
|
|
C |
p.
|
artikel
|
| 48 |
Automatic method for the estimation of li-ion degradation test sample sizes required to understand cell-to-cell variability
|
Strange, Calum
|
|
|
|
C |
p.
|
artikel
|
| 49 |
Battery digital twins: Perspectives on the fusion of models, data and artificial intelligence for smart battery management systems
|
Wu, Billy
|
|
|
|
C |
p.
|
artikel
|
| 50 |
Battery state-of-charge estimation using machine learning analysis of ultrasonic signatures
|
Galiounas, Elias
|
|
|
|
C |
p.
|
artikel
|
| 51 |
Big-data-accelerated aperiodic Si/Ge superlattice prediction for quenching thermal conduction via pattern analysis
|
Liu, Yida
|
|
|
|
C |
p.
|
artikel
|
| 52 |
Boosting the optimization of membrane electrode assembly in proton exchange membrane fuel cells guided by explainable artificial intelligence
|
Ding, Rui
|
|
|
|
C |
p.
|
artikel
|
| 53 |
ChemNODE: A neural ordinary differential equations framework for efficient chemical kinetic solvers
|
Owoyele, Opeoluwa
|
|
|
|
C |
p.
|
artikel
|
| 54 |
Coaxial multi-criteria optimization of a methane steam reforming reactor for effective hydrogen production and thermal management
|
Pajak, Marcin
|
|
|
|
C |
p.
|
artikel
|
| 55 |
Combining data envelopment analysis and Random Forest for selecting optimal locations of solar PV plants
|
Cattani, Gilles
|
|
|
|
C |
p.
|
artikel
|
| 56 |
Combining machine learning with 3D-CFD modeling for optimizing a DISI engine performance during cold-start
|
Ravindran, Arun C.
|
|
|
|
C |
p.
|
artikel
|
| 57 |
Comparison between conventional and deep learning-based surrogate models in predicting convective heat transfer performance of U-bend channels
|
Wang, Qi
|
|
|
|
C |
p.
|
artikel
|
| 58 |
Comparison of optimizers for model predictive thermal control of buildings
|
Andersen, Torben
|
|
|
|
C |
p.
|
artikel
|
| 59 |
Conditional Generative Adversarial Networks for modelling fuel sprays
|
Ates, Cihan
|
|
|
|
C |
p.
|
artikel
|
| 60 |
Confidence estimation in the prediction of epithermal neutron resonance self-shielding factors in irradiation samples using an ensemble neural network
|
Wilkinson, Ian M.
|
|
|
|
C |
p.
|
artikel
|
| 61 |
Consensus-based dispatch optimization of a microgrid considering meta-heuristic-based demand response scheduling and network packet loss characterization
|
Jasim, Ali M.
|
|
|
|
C |
p.
|
artikel
|
| 62 |
Constructing representative driving cycle for heavy duty vehicle based on Markov chain method considering road slope
|
Jia, Xinyi
|
|
|
|
C |
p.
|
artikel
|
| 63 |
Correlation between microstructures and macroscopic properties of nickel/yttria-stabilized zirconia (Ni-YSZ) anodes: Meso-scale modeling and deep learning with convolutional neural networks
|
Liu, Xuhao
|
|
|
|
C |
p.
|
artikel
|
| 64 |
Crises and opportunities in terms of energy and AI technologies during the COVID-19 pandemic
|
Wang, Bowen
|
|
|
|
C |
p.
|
artikel
|
| 65 |
Current trends on the use of deep learning methods for image analysis in energy applications
|
Casini, Mattia
|
|
|
|
C |
p.
|
artikel
|
| 66 |
Data analytics in the electricity sector – A quantitative and qualitative literature review
|
Scheidt, Frederik vom
|
|
|
|
C |
p.
|
artikel
|
| 67 |
Data-based flooding fault diagnosis of proton exchange membrane fuel cell systems using LSTM networks
|
Gu, Xin
|
|
|
|
C |
p.
|
artikel
|
| 68 |
Data-driven approaches for cyber defense of battery energy storage systems
|
Kharlamova, Nina
|
|
|
|
C |
p.
|
artikel
|
| 69 |
Data–driven decision–making for lost circulation treatments: A machine learning approach
|
Alkinani, Husam H.
|
|
|
|
C |
p.
|
artikel
|
| 70 |
Data-driven modeling of power generation for a coal power plant under cycling
|
Sharma, Himanshu
|
|
|
|
C |
p.
|
artikel
|
| 71 |
Data-driven modelling of energy demand response behaviour based on a large-scale residential trial
|
Antonopoulos, Ioannis
|
|
|
|
C |
p.
|
artikel
|
| 72 |
Data-driven smart charging for heterogeneous electric vehicle fleets
|
Frendo, Oliver
|
|
|
|
C |
p.
|
artikel
|
| 73 |
3D convolutional selective autoencoder for instability detection in combustion systems
|
Gangopadhyay, Tryambak
|
|
|
|
C |
p.
|
artikel
|
| 74 |
Deep anomaly detection in horizontal axis wind turbines using Graph Convolutional Autoencoders for Multivariate Time series
|
Miele, Eric Stefan
|
|
|
|
C |
p.
|
artikel
|
| 75 |
Deep convolutional surrogates and freedom in thermal design
|
Keramati, Hadi
|
|
|
|
C |
p.
|
artikel
|
| 76 |
Deep excavation of the impact from endogenous and exogenous uncertainties on long-term energy planning
|
Li, Xiang
|
|
|
|
C |
p.
|
artikel
|
| 77 |
Deep learning for estimating energy savings of early-stage facade design decisions
|
Abediniangerabi, B.
|
|
|
|
C |
p.
|
artikel
|
| 78 |
Deep learning in fault detection and diagnosis of building HVAC systems: A systematic review with meta analysis
|
Zhang, Fan
|
|
|
|
C |
p.
|
artikel
|
| 79 |
Deep Neural Network-Based Generation of Planar CH Distribution through Flame Chemiluminescence in Premixed Turbulent Flame
|
Han, Lei
|
|
|
|
C |
p.
|
artikel
|
| 80 |
Deep reinforcement learning for home energy management system control
|
Lissa, Paulo
|
|
|
|
C |
p.
|
artikel
|
| 81 |
Deep reinforcement learning for the optimized operation of large amounts of distributed renewable energy assets
|
Specht, Jan Martin
|
|
|
|
C |
p.
|
artikel
|
| 82 |
Deep reinforcement learning with planning guardrails for building energy demand response
|
Jang, Doseok
|
|
|
|
C |
p.
|
artikel
|
| 83 |
Degradation prediction of proton exchange membrane fuel cell stack using semi-empirical and data-driven methods
|
Wang, Yupeng
|
|
|
|
C |
p.
|
artikel
|
| 84 |
Denoising and fuel spray droplet detection from light-scattered images using deep learning
|
Hasti, Veeraraghava Raju
|
|
|
|
C |
p.
|
artikel
|
| 85 |
Designing a clean and efficient air conditioner with AI intervention to optimize energy-exergy interplay
|
Saikia, Pranaynil
|
|
|
|
C |
p.
|
artikel
|
| 86 |
DetEEktor: Mask R-CNN based neural network for energy plant identification on aerial photographs
|
Schulz, Maximilian
|
|
|
|
C |
p.
|
artikel
|
| 87 |
Development and assessment of artificial neural network models for direct normal solar irradiance forecasting using operational numerical weather prediction data
|
Pereira, Sara
|
|
|
|
C |
p.
|
artikel
|
| 88 |
Development and comparison of local solar split models on the example of Central Europe
|
Schlager, E.
|
|
|
|
C |
p.
|
artikel
|
| 89 |
Development and evaluation of a vision driven sensor for estimating fuel feeding rates in combustion and gasification processes
|
Ögren, Yngve
|
|
|
|
C |
p.
|
artikel
|
| 90 |
Development of a Soft Actor Critic deep reinforcement learning approach for harnessing energy flexibility in a Large Office building
|
Kathirgamanathan, Anjukan
|
|
|
|
C |
p.
|
artikel
|
| 91 |
Development of surrogate-optimization models for a novel transcritical power cycle integrated with a small modular reactor
|
Zhang, Yili
|
|
|
|
C |
p.
|
artikel
|
| 92 |
Development of the ignition delay prediction model of n-butane/hydrogen mixtures based on artificial neural network
|
Cui, Yanqing
|
|
|
|
C |
p.
|
artikel
|
| 93 |
Directed message passing neural network (D-MPNN) with graph edge attention (GEA) for property prediction of biofuel-relevant species
|
Han, Xu
|
|
|
|
C |
p.
|
artikel
|
| 94 |
Dynamic energy system modeling using hybrid physics-based and machine learning encoder–decoder models
|
Machalek, Derek
|
|
|
|
C |
p.
|
artikel
|
| 95 |
Editorial Board
|
|
|
|
|
C |
p.
|
artikel
|
| 96 |
Editorial Board
|
|
|
|
|
C |
p.
|
artikel
|
| 97 |
Effective rural electrification via optimal network: Optimal path-finding in highly anisotropic search space using multiplier-accelerated A* algorithm
|
Li, Jerry C.F.
|
|
|
|
C |
p.
|
artikel
|
| 98 |
Effective thermal conductivity estimation using a convolutional neural network and its application in topology optimization
|
Adam, Andre
|
|
|
|
C |
p.
|
artikel
|
| 99 |
Electrical demand aggregation effects on the performance of deep learning-based short-term load forecasting of a residential building
|
Shaqour, Ayas
|
|
|
|
C |
p.
|
artikel
|
| 100 |
Enabling Virtual Met Masts for wind energy applications through machine learning-methods
|
Schwegmann, Sandra
|
|
|
|
C |
p.
|
artikel
|
| 101 |
Energy and AI
|
Jin, Donghan
|
|
|
|
C |
p.
|
artikel
|
| 102 |
Energy management of buildings with energy storage and solar photovoltaic: A diversity in experience approach for deep reinforcement learning agents
|
Hussain, Akhtar
|
|
|
|
C |
p.
|
artikel
|
| 103 |
Enhanced oxygen reduction kinetics by a porous heterostructured cathode for intermediate temperature solid oxide fuel cells
|
Zheng, Yun
|
|
|
|
C |
p.
|
artikel
|
| 104 |
Enhancing hourly heat demand prediction through artificial neural networks: A national level case study
|
Zhang, Meng
|
|
|
|
C |
p.
|
artikel
|
| 105 |
Ensemble Machine Learning greatly improves ERA5 skills for wind energy applications
|
Cavaiola, Mattia
|
|
|
|
C |
p.
|
artikel
|
| 106 |
Ethics in Engineering and the Role of Responsible Technology
|
Ocone, Raffaella
|
|
|
|
C |
p.
|
artikel
|
| 107 |
Evaluation on the Fuel Economy of Automated Vehicles with Data-Driven Simulation Method
|
Luo, Yueqi
|
|
|
|
C |
p.
|
artikel
|
| 108 |
Experimental and numerical study of water sprayed turbulent combustion: Proposal of a neural network modeling for five-dimensional flamelet approach
|
Honzawa, Takafumi
|
|
|
|
C |
p.
|
artikel
|
| 109 |
Explainable Artificial Intelligence (XAI) techniques for energy and power systems: Review, challenges and opportunities
|
Machlev, R.
|
|
|
|
C |
p.
|
artikel
|
| 110 |
Explainable deep transfer learning for energy efficiency prediction based on uncertainty detection and identification
|
Panjapornpon, Chanin
|
|
|
|
C |
p.
|
artikel
|
| 111 |
Feature selection for energy system modeling: Identification of relevant time series information
|
Müller, Inga M.
|
|
|
|
C |
p.
|
artikel
|
| 112 |
Finding and analysing energy research funding data: The EnArgus system
|
Oppermann, Leif
|
|
|
|
C |
p.
|
artikel
|
| 113 |
Flexible electricity price forecasting by switching mother wavelets based on wavelet transform and Long Short-Term Memory
|
Iwabuchi, Koki
|
|
|
|
C |
p.
|
artikel
|
| 114 |
Flexible networked rural electrification using levelized interpolative genetic algorithm
|
Li, Jerry C.F.
|
|
|
|
C |
p.
|
artikel
|
| 115 |
Forecast electricity demand in commercial building with machine learning models to enable demand response programs
|
Pallonetto, Fabiano
|
|
|
|
C |
p.
|
artikel
|
| 116 |
Function approximation reinforcement learning of energy management with the fuzzy REINFORCE for fuel cell hybrid electric vehicles
|
Guo, Liang
|
|
|
|
C |
p.
|
artikel
|
| 117 |
Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology
|
Wang, Yun
|
|
|
|
C |
p.
|
artikel
|
| 118 |
Generalised diagnostic framework for rapid battery degradation quantification with deep learning
|
Ruan, Haijun
|
|
|
|
C |
p.
|
artikel
|
| 119 |
Generalization performance of a deep learning based engine-out emissions model
|
Warey, Alok
|
|
|
|
C |
p.
|
artikel
|
| 120 |
Generation of meaningful synthetic sensor data — Evaluated with a reliable transferability methodology
|
Meiser, Michael
|
|
|
|
C |
p.
|
artikel
|
| 121 |
Generation of Rate-of-Injection (ROI) profile for Computational Fluid Dynamics (CFD) model of Internal Combustion Engine (ICE) using machine learning
|
Williams, Zachary
|
|
|
|
C |
p.
|
artikel
|
| 122 |
Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings
|
Luo, X.J.
|
|
|
|
C |
p.
|
artikel
|
| 123 |
GeoAI for detection of solar photovoltaic installations in the Netherlands
|
Kausika, Bala Bhavya
|
|
|
|
C |
p.
|
artikel
|
| 124 |
Geospatial assessment of rooftop solar photovoltaic potential using multi-source remote sensing data
|
Jiang, Hou
|
|
|
|
C |
p.
|
artikel
|
| 125 |
Grain boundaries induce significant decrease in lattice thermal conductivity of CdTe
|
Huang, Xiaona
|
|
|
|
C |
p.
|
artikel
|
| 126 |
Greedy nonlinear autoregression for multifidelity computer models at different scales
|
Xing, W.
|
|
|
|
C |
p.
|
artikel
|
| 127 |
Grey box modeling of supermarket refrigeration cabinets
|
Leerbeck, K.
|
|
|
|
C |
p.
|
artikel
|
| 128 |
Gym-ANM: Reinforcement learning environments for active network management tasks in electricity distribution systems
|
Henry, Robin
|
|
|
|
C |
p.
|
artikel
|
| 129 |
High-resolution peak demand estimation using generalized additive models and deep neural networks
|
Berrisch, Jonathan
|
|
|
|
C |
p.
|
artikel
|
| 130 |
Hybrid data-based modeling for the prediction and diagnostics of Li-ion battery thermal behaviors
|
Legala, Adithya
|
|
|
|
C |
p.
|
artikel
|
| 131 |
Hybrid optimization algorithm for parameter estimation of poly-phase induction motors with experimental verification
|
Abdelwanis, Mohamed I.
|
|
|
|
C |
p.
|
artikel
|
| 132 |
Identification and machine learning prediction of knee-point and knee-onset in capacity degradation curves of lithium-ion cells
|
Fermín-Cueto, Paula
|
|
|
|
C |
p.
|
artikel
|
| 133 |
Identification of non-linear autoregressive models with exogenous inputs for room air temperature modelling
|
Thilker, Christian Ankerstjerne
|
|
|
|
C |
p.
|
artikel
|
| 134 |
Identifying representative days of solar irradiance and wind speed in Brazil using machine learning techniques
|
Ribeiro, Rafaela
|
|
|
|
C |
p.
|
artikel
|
| 135 |
Identifying the validity domain of machine learning models in building energy systems
|
Rätz, Martin
|
|
|
|
C |
p.
|
artikel
|
| 136 |
Implementation for a cloud battery management system based on the CHAIN framework
|
Yang, Shichun
|
|
|
|
C |
p.
|
artikel
|
| 137 |
Implementation of artificial intelligence techniques in microgrid control environment: Current progress and future scopes
|
Trivedi, Rohit
|
|
|
|
C |
p.
|
artikel
|
| 138 |
Inclusive STEAM education in diverse disciplines of sustainable energy and AI
|
Skowronek, Michelle
|
|
|
|
C |
p.
|
artikel
|
| 139 |
Increasing power plant efficiency with clustering methods and Variable Importance Index assessment
|
Duarte, Jéssica
|
|
|
|
C |
p.
|
artikel
|
| 140 |
Integration of solar thermal and photovoltaic, wind, and battery energy storage through AI in NEOM city
|
Boretti, Alberto
|
|
|
|
C |
p.
|
artikel
|
| 141 |
Introducing the Open Energy Ontology: Enhancing data interpretation and interfacing in energy systems analysis
|
Booshehri, Meisam
|
|
|
|
C |
p.
|
artikel
|
| 142 |
Large eddy simulation of spray combustion using flamelet generated manifolds combined with artificial neural networks
|
Zhang, Yan
|
|
|
|
C |
p.
|
artikel
|
| 143 |
Lessons learned from the underrepresentation of women in STEM: AI-enabled solutions and more
|
Abuwatfa, Waad
|
|
|
|
C |
p.
|
artikel
|
| 144 |
Lithium-ion battery data and where to find it
|
dos Reis, Gonçalo
|
|
|
|
C |
p.
|
artikel
|
| 145 |
Lévy-flight moth-flame optimisation algorithm-based micro-grid equipment sizing: An integrated investment and operational planning approach
|
Mohseni, Soheil
|
|
|
|
C |
p.
|
artikel
|
| 146 |
Machine Learning and Deep Learning Methods for Enhancing Building Energy Efficiency and Indoor Environmental Quality – A Review
|
Tien, Paige Wenbin
|
|
|
|
C |
p.
|
artikel
|
| 147 |
Machine learning and price-based load scheduling for an optimal IoT control in the smart and frugal home
|
Kaur, Rachneet
|
|
|
|
C |
p.
|
artikel
|
| 148 |
Machine learning-based assessment of the impact of the manufacturing process on battery electrode heterogeneity
|
Duquesnoy, Marc
|
|
|
|
C |
p.
|
artikel
|
| 149 |
Machine learning based fault detection and state of health estimation of proton exchange membrane fuel cells
|
Nagulapati, Vijay Mohan
|
|
|
|
C |
p.
|
artikel
|
| 150 |
Machine learning based techno-economic process optimisation for CO2 capture via enhanced weathering
|
Jiang, Hai
|
|
|
|
C |
p.
|
artikel
|
| 151 |
Machine learning for advanced energy materials
|
Liu, Yun
|
|
|
|
C |
p.
|
artikel
|
| 152 |
Machine learning for combustion
|
Zhou, Lei
|
|
|
|
C |
p.
|
artikel
|
| 153 |
Machine learning for integrating combustion chemistry in numerical simulations
|
Nguyen, Huu-Tri
|
|
|
|
C |
p.
|
artikel
|
| 154 |
Machine learning modeling for proton exchange membrane fuel cell performance
|
Legala, Adithya
|
|
|
|
C |
p.
|
artikel
|
| 155 |
Maintaining flexibility in smart grid consumption through deep learning and deep reinforcement learning
|
Gallego, Fernando
|
|
|
|
C |
p.
|
artikel
|
| 156 |
Methodology for ranking controllable parameters to enhance operation of a steam generator with a combined Artificial Neural Network and Design of Experiments approach
|
Vieira, Lara Werncke
|
|
|
|
C |
p.
|
artikel
|
| 157 |
Methodology for the disaggregation and forecast of demand flexibility in large consumers with the application of non-intrusive load monitoring techniques
|
Toledo-Orozco, Marco
|
|
|
|
C |
p.
|
artikel
|
| 158 |
Methods and applications for Artificial Intelligence, Big Data, Internet of Things, and Blockchain in smart energy management
|
Li, Joey
|
|
|
|
C |
p.
|
artikel
|
| 159 |
Multi-objective optimisation with hybrid machine learning strategy for complex catalytic processes
|
Tai, Xin Yee
|
|
|
|
C |
p.
|
artikel
|
| 160 |
Multi-objective performance optimization & thermodynamic analysis of solar powered supercritical CO2 power cycles using machine learning methods & genetic algorithm
|
Turja, Asif Iqbal
|
|
|
|
C |
p.
|
artikel
|
| 161 |
Multi-physics-resolved digital twin of proton exchange membrane fuel cells with a data-driven surrogate model
|
Wang, Bowen
|
|
|
|
C |
p.
|
artikel
|
| 162 |
Multivariate time series imputation for energy data using neural networks
|
Bülte, Christopher
|
|
|
|
C |
p.
|
artikel
|
| 163 |
Nanotwinning induced decreased lattice thermal conductivity of high temperature thermoelectric boron subphosphide (B12P2) from deep learning potential simulations
|
Huang, Xiaona
|
|
|
|
C |
p.
|
artikel
|
| 164 |
Next-generation blockchain enabled smart grid: Conceptual framework, key technologies and industry practices review
|
Uddin, Shekh S.
|
|
|
|
C |
p.
|
artikel
|
| 165 |
Non-invasive load-shed authentication model for demand response applications assisted by event-based non-intrusive load monitoring
|
Rehman, Attique Ur
|
|
|
|
C |
p.
|
artikel
|
| 166 |
Numerical Investigation of a modified Kalina cycle system for high-temperature application and genetic algorithm based optimization of the multi-phase expander's inlet condition
|
Hossain, Mohammad Masrur
|
|
|
|
C |
p.
|
artikel
|
| 167 |
Ocean energy applications for coastal communities with artificial intelligencea state-of-the-art review
|
Zhou, Yuekuan
|
|
|
|
C |
p.
|
artikel
|
| 168 |
OntoPowSys: A power system ontology for cross domain interactions in an eco industrial park
|
Devanand, Aravind
|
|
|
|
C |
p.
|
artikel
|
| 169 |
Overview on artificial intelligence in design of Organic Rankine Cycle
|
Zhao, Dongpeng
|
|
|
|
C |
p.
|
artikel
|
| 170 |
Perspective: Predicting and optimizing thermal transport properties with machine learning methods
|
Wei, Han
|
|
|
|
C |
p.
|
artikel
|
| 171 |
Physical-based training data collection approach for data-driven lithium-ion battery state-of-charge prediction
|
Li, Jie
|
|
|
|
C |
p.
|
artikel
|
| 172 |
Physics-constrained deep learning for data assimilation of subsurface transport
|
Wu, Haiyi
|
|
|
|
C |
p.
|
artikel
|
| 173 |
Predicting entropy and heat capacity of hydrocarbons using machine learning
|
Aldosari, Mohammed N.
|
|
|
|
C |
p.
|
artikel
|
| 174 |
Predicting the performance of magnetocaloric systems using machine learning regressors
|
Silva, D.J.
|
|
|
|
C |
p.
|
artikel
|
| 175 |
Prediction of effective diffusivity of porous media using deep learning method based on sample structure information self-amplification
|
Wang, H.
|
|
|
|
C |
p.
|
artikel
|
| 176 |
Prediction of future capacity and internal resistance of Li-ion cells from one cycle of input data
|
Strange, Calum
|
|
|
|
C |
p.
|
artikel
|
| 177 |
Prediction of high frequency resistance in polymer electrolyte membrane fuel cells using long short term memory based model
|
Lin, Tong
|
|
|
|
C |
p.
|
artikel
|
| 178 |
Prediction of hydrogen uptake of metal organic frameworks using explainable machine learning
|
Meduri, Sitaram
|
|
|
|
C |
p.
|
artikel
|
| 179 |
Prediction of office building electricity demand using artificial neural network by splitting the time horizon for different occupancy rates
|
Chen, Si
|
|
|
|
C |
p.
|
artikel
|
| 180 |
Prediction of sorption enhanced steam methane reforming products from machine learning based soft-sensor models
|
Nkulikiyinka, Paula
|
|
|
|
C |
p.
|
artikel
|
| 181 |
Prediction of voltage distribution using deep learning and identified key smart meter locations
|
Mokhtar, Maizura
|
|
|
|
C |
p.
|
artikel
|
| 182 |
Prognostic for fuel cell based on particle filter and recurrent neural network fusion structure
|
Xie, Renyou
|
|
|
|
C |
p.
|
artikel
|
| 183 |
Prognostics and health management of alkaline water electrolyzer: Techno-economic analysis considering replacement moment
|
Lee, Hyunjun
|
|
|
|
C |
p.
|
artikel
|
| 184 |
Prognostics for Lithium-ion batteries for electric Vertical Take-off and Landing aircraft using data-driven machine learning
|
Mitici, Mihaela
|
|
|
|
C |
p.
|
artikel
|
| 185 |
Prognostics of radiation power degradation lifetime for ultraviolet light-emitting diodes using stochastic data-driven models
|
Fan, Jiajie
|
|
|
|
C |
p.
|
artikel
|
| 186 |
Q-learning based control for energy management of series-parallel hybrid vehicles with balanced fuel consumption and battery life
|
Ahmadian, Saeid
|
|
|
|
C |
p.
|
artikel
|
| 187 |
Quantifying key factors for optimised manufacturing of Li-ion battery anode and cathode via artificial intelligence
|
Niri, Mona Faraji
|
|
|
|
C |
p.
|
artikel
|
| 188 |
Quasi-optimal control of a solar thermal system via neural networks
|
Friese, Jana
|
|
|
|
C |
p.
|
artikel
|
| 189 |
Real-time security margin control using deep reinforcement learning
|
Hagmar, Hannes
|
|
|
|
C |
p.
|
artikel
|
| 190 |
Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings
|
Nweye, Kingsley
|
|
|
|
C |
p.
|
artikel
|
| 191 |
Reconstructing hourly residential electrical load profiles for Renewable Energy Communities using non-intrusive machine learning techniques
|
Giannuzzo, Lorenzo
|
|
|
|
C |
p.
|
artikel
|
| 192 |
Reinforcement learning and A* search for the unit commitment problem
|
de Mars, Patrick
|
|
|
|
C |
p.
|
artikel
|
| 193 |
Reinforcement learning-driven local transactive energy market for distributed energy resources
|
Zhang, Steven
|
|
|
|
C |
p.
|
artikel
|
| 194 |
Reinforcement learning for whole-building HVAC control and demand response
|
Azuatalam, Donald
|
|
|
|
C |
p.
|
artikel
|
| 195 |
Response surface methodology-based parameter optimization of single-cylinder diesel engine fueled with graphene oxide dosed sesame oil/diesel fuel blend
|
Simsek, Suleyman
|
|
|
|
C |
p.
|
artikel
|
| 196 |
Reviewing 40 years of artificial intelligence applied to power systems – A taxonomic perspective
|
Heymann, F.
|
|
|
|
C |
p.
|
artikel
|
| 197 |
Review of dynamic performance and control strategy of supercritical CO2 Brayton cycle
|
Wang, Xuan
|
|
|
|
C |
p.
|
artikel
|
| 198 |
Rule-based scheduling of air conditioning using occupancy forecasting
|
Dorokhova, Marina
|
|
|
|
C |
p.
|
artikel
|
| 199 |
Safe reinforcement learning for multi-energy management systems with known constraint functions
|
Ceusters, Glenn
|
|
|
|
C |
p.
|
artikel
|
| 200 |
Scarcity events analysis in adequacy studies using CN2 rule mining
|
Heymann, Fabian
|
|
|
|
C |
p.
|
artikel
|
| 201 |
Segmented thermoelectric generator modelling and optimization using artificial neural networks by iterative training
|
Zhu, Yuxiao
|
|
|
|
C |
p.
|
artikel
|
| 202 |
Selecting decision trees for power system security assessment
|
Bugaje, Al-Amin B.
|
|
|
|
C |
p.
|
artikel
|
| 203 |
Semantic 3D City Agents—An intelligent automation for dynamic geospatial knowledge graphs
|
Chadzynski, Arkadiusz
|
|
|
|
C |
p.
|
artikel
|
| 204 |
Semantic 3D City Database — An enabler for a dynamic geospatial knowledge graph
|
Chadzynski, Arkadiusz
|
|
|
|
C |
p.
|
artikel
|
| 205 |
Sensitivity analysis to reduce duplicated features in ANN training for district heat demand prediction
|
Chen, Si
|
|
|
|
C |
p.
|
artikel
|
| 206 |
Separable Shadow Hamiltonian Hybrid Monte Carlo for Bayesian Neural Network Inference in wind speed forecasting
|
Mbuvha, Rendani
|
|
|
|
C |
p.
|
artikel
|
| 207 |
Site adaptation with machine learning for a Northern Europe gridded global solar irradiance product
|
Zainali, Sebastian
|
|
|
|
C |
p.
|
artikel
|
| 208 |
Smart energy management system framework for population dynamics modelling and suitable energy trajectories identification in islanded micro-grids
|
Mounsif, Mehdi
|
|
|
|
C |
p.
|
artikel
|
| 209 |
SolarGAN: Synthetic annual solar irradiance time series on urban building facades via Deep Generative Networks
|
Zhang, Yufei
|
|
|
|
C |
p.
|
artikel
|
| 210 |
Stepped machine learning for the development of mineral models: Concepts and applications in the pre-salt reservoir carbonate rocks
|
de Oliveira, Lucas Abreu Blanes
|
|
|
|
C |
p.
|
artikel
|
| 211 |
Stress testing electrical grids: Generative Adversarial Networks for load scenario generation
|
Rizzato, Matteo
|
|
|
|
C |
p.
|
artikel
|
| 212 |
Study of degradation of fuel cell stack based on the collected high-dimensional data and clustering algorithms calculations
|
Niu, Tong
|
|
|
|
C |
p.
|
artikel
|
| 213 |
Synthetic demand data generation for individual electricity consumers : Generative Adversarial Networks (GANs)
|
Yilmaz, Bilgi
|
|
|
|
C |
p.
|
artikel
|
| 214 |
Synthetic demand data generation for individual electricity consumers: Inpainting
|
Dobrovolskij, Dascha
|
|
|
|
C |
p.
|
artikel
|
| 215 |
Temporally resolving premixed turbulent flame structures using self-supervised adversarial reconstruction of CH-PLIF
|
Oh, Ji-Hun
|
|
|
|
C |
p.
|
artikel
|
| 216 |
The balance of contradictory factors in the selection of biodiesel and jet biofuels on algae fixation of flue gas
|
Liu, Ziyu
|
|
|
|
C |
p.
|
artikel
|
| 217 |
The effect of catalyst layer design on catalyst utilization in PEMFC studied via stochastic reconstruction method
|
Zhao, Congfan
|
|
|
|
C |
p.
|
artikel
|
| 218 |
The equality, diversity and inclusion in energy and AI: Call for actions
|
Xuan, Jin
|
|
|
|
C |
p.
|
artikel
|
| 219 |
The future of sustainable chemistry and process: Convergence of artificial intelligence, data and hardware
|
Tai, Xin Yee
|
|
|
|
C |
p.
|
artikel
|
| 220 |
Thermodynamic and kinetics of hydrogen photoproduction enhancement by concentrated sunlight with CO2 photoreduction by heterojunction photocatalysts
|
Liu, Ziyu
|
|
|
|
C |
p.
|
artikel
|
| 221 |
Total process of fault diagnosis for wind turbine gearbox, from the perspective of combination with feature extraction and machine learning: A review
|
Xu, Xinhua
|
|
|
|
C |
p.
|
artikel
|
| 222 |
Toward cost-effective residential energy reduction and community impacts: A data-based machine learning approach
|
Naji, Adel
|
|
|
|
C |
p.
|
artikel
|
| 223 |
Towards electric digital twin grid: Technology and framework review
|
Sifat, Md. Mhamud Hussen
|
|
|
|
C |
p.
|
artikel
|
| 224 |
Towards online optimisation of solid oxide fuel cell performance: Combining deep learning with multi-physics simulation
|
Xu, Haoran
|
|
|
|
C |
p.
|
artikel
|
| 225 |
Transfer learning in demand response: A review of algorithms for data-efficient modelling and control
|
Peirelinck, Thijs
|
|
|
|
C |
p.
|
artikel
|
| 226 |
Transfer learning of deep neural networks for predicting thermoacoustic instabilities in combustion systems
|
Mondal, Sudeepta
|
|
|
|
C |
p.
|
artikel
|
| 227 |
Transformations of trust in society: A systematic review of how access to big data in energy systems challenges Scandinavian culture
|
Godoy, Jaqueline de
|
|
|
|
C |
p.
|
artikel
|
| 228 |
Turbulent flame image classification using Convolutional Neural Networks
|
Roncancio, Rathziel
|
|
|
|
C |
p.
|
artikel
|
| 229 |
Two-stage capacity optimization approach of multi-energy system considering its optimal operation
|
Luo, X.J.
|
|
|
|
C |
p.
|
artikel
|
| 230 |
Typical load profile-supported convolutional neural network for short-term load forecasting in the industrial sector
|
Walser, Thilo
|
|
|
|
C |
p.
|
artikel
|
| 231 |
Understanding electricity prices beyond the merit order principle using explainable AI
|
Trebbien, Julius
|
|
|
|
C |
p.
|
artikel
|
| 232 |
Unsupervised machine learning to classify crystal structures according to their structural distortion: A case study on Li-argyrodite solid-state electrolytes
|
Gallo-Bueno, A.
|
|
|
|
C |
p.
|
artikel
|
| 233 |
Upsampling Monte Carlo neutron transport simulation tallies using a convolutional neural network
|
Osborne, Andrew
|
|
|
|
C |
p.
|
artikel
|
| 234 |
Using Bayesian deep learning approaches for uncertainty-aware building energy surrogate models
|
Westermann, Paul
|
|
|
|
C |
p.
|
artikel
|
| 235 |
Using physics to extend the range of machine learning models for an aerodynamic, hydraulic and combusting system: The toy model concept
|
Brahma, Indranil
|
|
|
|
C |
p.
|
artikel
|
| 236 |
Vertical power flow forecast with LSTMs using regular training update strategies
|
Brauns, Katharina
|
|
|
|
C |
p.
|
artikel
|
| 237 |
VISION-iT: A Framework for Digitizing Bubbles and Droplets
|
Suh, Youngjoon
|
|
|
|
C |
p.
|
artikel
|
| 238 |
Visualization-based prediction of dendritic copper growth in electrochemical cells using convolutional long short-term memory
|
Kumar, Roshan
|
|
|
|
C |
p.
|
artikel
|
| 239 |
Wind power forecasting based on new hybrid model with TCN residual modification
|
Zhu, Jiaojiao
|
|
|
|
C |
p.
|
artikel
|
Tijdschrift beschrijving