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: "a compartmental model for traffic networks and its dynamical behavior"
  Abstract: We propose a macroscopic traffic network flow model suitable for analysis as a dynamical system, and we qualitatively analyze equilibrium flows as well as convergence. Flows at a junction are determined by downstream supply of capacity as well as upstream demand of traffic wishing to flow through the junction. This approach is rooted in the celebrated Cell Transmission Model for freeway traffic flow. Unlike related results which rely on certain system cooperativity properties, our model generally does not possess these properties. We show that the lack of cooperativity is in fact a useful feature that allows traffic control methods, such as ramp metering, to be effective. Finally, we leverage the results of the paper to develop a linear program for optimal ramp metering.

Connected through hyperedge HE-1 (induced by source paper "social cost guarantees in smart route guidance"):
  with members:
    - "truthful facility assignment with resource augmentation an exact analysis of serial dictatorship"
    - "social welfare in one sided matchings random priority and beyond"
    - "a market inspired approach for intersection management in urban road traffic networks"
    - "approximately optimal mechanism design via differential privacy"

Connected through hyperedge HE-2 (induced by source paper "optimal regulation of flow networks with transient constraints"):
  with members:
    - "on resilient control of dynamical flow networks"
    - "modeling and control of hvdc transmission systems from theory to practice and back"
    - "zero forcing sets and controllability of dynamical systems defined on graphs"
    - "zero forcing number constrained matchings and strong structural controllability"
    - "an internal model approach to optimal frequency regulation in power grids with time varying voltages"
    - "dynamic coupling design for nonlinear output agreement and time varying flow control"

Connected through hyperedge HE-3 (induced by source paper "on resilient control of dynamical flow networks"):
  with members:
    - "separability of lyapunov functions for contractive monotone systems"
    - "mixed monotonicity of partial first in first out traffic flow models"
    - "robust network routing under cascading failures"
    - "design of multi path data routing algorithm based on network reliability"

Connected through hyperedge HE-4 (induced by source paper "a contractive approach to separable lyapunov functions for monotone systems"):
  with members:
    - "on existence of separable contraction metrics for monotone nonlinear systems"
    - "separability of lyapunov functions for contractive monotone systems"
    - "a differential lyapunov framework for contraction analysis"

Connected through hyperedge HE-5 (induced by source paper "separability of lyapunov functions for contractive monotone systems"):
  with members:
    - "a differential lyapunov framework for contraction analysis"

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.SY(Systems and Control)