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Data-Driven Physics-Informed Neuro-Symbolic Planning for Low-Carbon Port Integrated Energy Systems
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Physics Informed Piecewise Linear Neural Networks for Process Optimization
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Development of surrogate-optimization models for a novel transcritical power cycle integrated with a small modular reactor
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The Benders decomposition algorithm: A literature review
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Techno-economic assessment of coordinated energy management in multi-vector systems: Cost-effective integration of underground storage and AI-Based maritime scheduling
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A Review of Hydrogen Production from Onboard Ammonia Decomposition: Maritime Applications of Concentrated Solar Energy and Boil-Off Gas Recovery
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Flexible production of green hydrogen and ammonia from variable solar and wind energy: Case study of Chile and Argentina
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A novel integration of a green power-to-ammonia to power system: Reversible solid oxide fuel cell for hydrogen and power production coupled with an ammonia synthesis unit
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Innovation trends and evolutionary paths of green fuel technologies in maritime field: A global patent review
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Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
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Solving Constrained Pseudoconvex Optimization Problems with deep learning-based neurodynamic optimization
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A multi-objective planning tool for the optimal supply of green hydrogen for an industrial port area decarbonization
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The role of hydrogen as enabler of industrial port area decarbonization
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Optimal design of multiuse hybrid microgrids power by green hydrogen–ammonia
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From fertilizer to fuel: Ammonia’s evolution and role in global decarbonization
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Physics-informed machine learning
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Machine-Learning-Assisted Optimization for Antenna Geometry Design
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AI-Assisted Antenna Optimization: Integrating Evolutionary and Inverse Cascade Neural Networks With Differential Evolution
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Explainable AI (XAI): Core Ideas, Techniques, and Solutions
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Recent Advances in Bayesian Optimization
inferredcites →https://doi.org/10.1287/opre.2021.0707openalex-snapshot
Mixed-Integer Optimization with Constraint Learning
inferredcites →https://doi.org/10.30574/ijsra.2025.16.1.2019openalex-snapshot
Neuro-Symbolic Generative AI for Explainable Reasoning
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Neuro-symbolic AI for enterprise systems: Transforming CRM & ERP through logical and statistical AI integration
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Safety Assessment of the Ammonia Bunkering Process in the Maritime Sector: A Review
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Methanol, a Plugin Marine Fuel for Green House Gas Reduction—A Review
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Realizing the Role of Hydrogen Energy in Ports: Evidence from Ningbo Zhoushan Port
inferredcites →https://doi.org/10.3390/jmse13101960openalex-snapshot
Multi-Fuel SOFC System Modeling for Ship Propulsion: Comparative Performance Analysis and Feasibility Assessment of Ammonia, Methanol and Hydrogen as Marine Fuels
inferredcites →https://doi.org/10.3390/su16052204openalex-snapshot
A Quantitative Risk Analysis during Truck-to-Ship Ammonia Bunkering
inferredcites →https://doi.org/10.55041/ijsrem45503openalex-snapshot
Ammonia as a Marine Fuel: Navigating the Tides of Decarbonization in the Maritime Industry
inferredcites →https://doi.org/10.55248/gengpi.2022.31271openalex-snapshot
Neuro-Symbolic AI: Bringing a new era of Machine Learning
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RetenNet: A Deployable Machine Learning Pipeline with Explainable AI and Prescriptive Optimization for Customer Churn Management
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