human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "optimal v2g scheduling of electric vehicles and unit commitment using chemical reaction optimization"
  Abstract: An electric vehicle (EV) may be used as energy storage which allows the bi-directional electricity flow between the vehicle's battery and the electric power grid. In order to flatten the load profile of the electricity system, EV scheduling has become a hot research topic in recent years. In this paper, we propose a new formulation of the joint scheduling of EV and Unit Commitment (UC), called EVUC. Our formulation considers the characteristics of EVs while optimizing the system total running cost. We employ Chemical Reaction Optimization (CRO), a general-purpose optimization algorithm to solve this problem and the simulation results on a widely used set of instances indicate that CRO can effectively optimize this problem.

Connected through hyperedge HE-1 (induced by source paper "a social spider algorithm for solving the non convex economic load dispatch problem"):
  with members:
    - "parameter sensitivity analysis of social spider algorithm"
    - "a social spider algorithm for global optimization"
    - "base station switching problem for green cellular networks with social spider algorithm"

Connected through hyperedge HE-2 (induced by source paper "chemical reaction optimization for the set covering problem"):
  with members:
    - "sensor deployment for air pollution monitoring using public transportation system"
    - "real coded chemical reaction optimization with different perturbation functions"
    - "evolutionary artificial neural network based on chemical reaction optimization"
    - "an indirect genetic algorithm for set covering problems"
    - "an efficient mean field approach to the set covering problem"

Connected through hyperedge HE-3 (induced by source paper "an inter molecular adaptive collision scheme for chemical reaction optimization"):
  with members:
    - "sensor deployment for air pollution monitoring using public transportation system"
    - "real coded chemical reaction optimization with different perturbation functions"
    - "evolutionary artificial neural network based on chemical reaction optimization"

Connected through hyperedge HE-4 (induced by source paper "electric vehicle charging station placement formulation complexity and solutions"):
  with members:
    - "a multi layer market for vehicle to grid energy trading in the smart grid"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NE(Neural and Evolutionary Computing)