human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "feeder topology identification"):
  Abstract: Advanced control of distributed energy resources at the consumer level requires full situational awareness of the the distribution system. One important problem is that of feeder topology identification, due to changing switch configurations, given a sparse number of measurements. We formulate the problem for residential feeders as a spanning tree identification problem over a general graph. Given a set of power flow measurements and load pseudo measurements, we show that the underlying graph structure is crucial in defining identifiability of the correct spanning tree on the graph. First we solve the deterministic case of known true loads and measured power flow. We show that the placement of sensors on the network alone determine whether the set of spanning trees can be correctly identified. In the stochastic case where loads are in the form of noisy forecasts, we present a locally optimal sensor placement algorithm.

Includes members:
  Member "topology detection in microgrids with micro synchrophasors":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on state estimation techniques and challenges in smart distribution systems")
  Member "optimal inverter var control in distribution systems with high pv penetration":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a tractable ellipsoidal approximation for voltage regulation problems")

Question: Please tell me which class the source paper 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)