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: "lyapunov functions family approach to transient stability assessment"
  Abstract: Analysis of transient stability of strongly nonlinear post-fault dynamics is one of the most computationally challenging parts of dynamic security assessment. This paper proposes a novel approach for assessment of transient stability of the system. The approach generalizes the idea of energy methods, and extends the concept of energy function to a more general Lyapunov functions family (LFF) constructed via semidefinite programming techniques. Unlike the traditional energy function and its variations, the constructed Lyapunov functions are proven to be decreasing only in a finite neighborhood of the equilibrium point. However, we show that they can still certify stability of a broader set of initial conditions in comparison to the energy function in the closest-UEP method. Moreover, the certificates of stability can be constructed via a sequence of convex optimization problems that are tractable even for large scale systems. We also propose specific algorithms for adaptation of the Lyapunov functions to specific initial conditions and demonstrate the effectiveness of the approach on a number of IEEE test cases.

Connected through hyperedge HE-1 (induced by source paper "region of attraction for power systems using gaussian process and converse lyapunov function part i theoretical framework and off line study"):
  with members:
    - "high fidelity model order reduction for microgrids stability assessment"
    - "bayesian optimization with safety constraints safe and automatic parameter tuning in robotics"
    - "probabilistic power flow computation via low rank and sparse tensor recovery"
    - "robust stability assessment in the presence of load dynamics uncertainty"
    - "information theoretic regret bounds for gaussian process optimization in the bandit setting"
    - "a tutorial on bayesian optimization of expensive cost functions with application to active user modeling and hierarchical reinforcement learning"

Connected through hyperedge HE-2 (induced by source paper "a framework for robust assessment of power grid stability and resiliency"):
  with members:
    - "efficient synchronization stability metrics for fault clearing"
    - "geometry based estimation of stability region for a class of structure preserving power grids"
    - "design and stability of load side primary frequency control in power systems"

Connected through hyperedge HE-3 (induced by source paper "structural emergency control paradigm"):
  with members:
    - "a framework for robust assessment of power grid stability and resiliency"
    - "toward simulation free estimation of critical clearing time"
    - "design and stability of load side primary frequency control in power systems"

Connected through hyperedge HE-4 (induced by source paper "stability and control of ad hoc dc microgrids"):
  with members:
    - "a framework for robust assessment of power grid stability and resiliency"

Connected through hyperedge HE-5 (induced by source paper "a hierarchical approach to stability assessment of large scale interconnected networks"):
  with members:
    - "a framework for robust assessment of power grid stability and resiliency"

Connected through hyperedge HE-6 (induced by source paper "towards electronics based emergency control in power grids with high renewable penetration"):
  with members:
    - "a framework for robust assessment of power grid stability and resiliency"
    - "toward simulation free estimation of critical clearing time"

Connected through hyperedge HE-7 (induced by source paper "smart transmission network emergency control"):
  with members:
    - "a framework for robust assessment of power grid stability and resiliency"

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)