Yunfei Mu
Artificial Intelligence · 2017–2019
A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 6 citations into it
Whom Yunfei Mu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Yunfei Mu overall
Papers from Yunfei Mu's perspective
Ordered by how strongly the researchers Yunfei Mu trusts endorse each paper. Same corpus, a different order for every researcher.
- Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems (Applied intelligence (Boston))
- The Ant Lion Optimizer (Advances in Engineering Software)
- Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market
- In situ self-organization of carbon black-polyaniline composites from nanospheres to nanorods: Synthesis, morphology, structure and electrical conductivity
- Graphene, related two-dimensional crystals, and hybrid systems for energy conversion and storage (Science)
- A new one-step synthesis method for coating multi-walled carbon nanotubes with cuprous oxide nanoparticles
- Electrical Energy Storage for the Grid: A Battery of Choices (Science)
- Hybrid nanostructures based on titanium dioxide for enhanced photocatalysis
- Optimal investment planning for distributed generation in a competitive electricity market (IEEE Transactions on Power Systems)
- Advanced electrochemical energy storage supercapacitors based on the flexible carbon fiber fabric-coated with uniform coral-like MnO2 structured electrodes
Their papers
- Optimal distributed generation planning in active distribution networks considering integration of energy storage (2018) — 347 citations
- Dynamic economic dispatch of a hybrid energy microgrid considering building based virtual energy storage system (2017) — 242 citations
- Vector field-based support vector regression for building energy consumption prediction (2019) — 347 citations