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 distributed privacy preserving incremental update algorithm for probability distribution of wind power forecast error"
  Abstract: Establishing the conditional probability distribution (PD) of wind power forecast error (WFE) is a prerequisite for many stochastic analysis considering wind power integration. However, with the increasingly emergence of new data, the update burden of the conditional PD is getting heavier as the size of training data set grows rapidly. Meanwhile, the centralized training manner of the conditional PD may reveals the data privacy of wind farms (WFs) belonging to different stakeholders. To solve these problems, we propose a distributed privacy-preserving (DPP) incremental update algorithm (DPP-IUA) for updating each WF's conditional PD of WFE considering their correlation. This algorithm consists of two original methods: (1) a DPP incremental Gaussian-mixture-model algorithm (DPP-IGA) for updating the joint PD of the correlated WFs; and (2) a DPP mechanism for deriving each WF's conditional PD of WFE under a given forecast vector. The DPP-IUA keeps each WF's conditional PD of WFE up to date with extremely low update burden. Meanwhile, this algorithm is also fully distributed and strictly protects the data privacy of different WFs. The effectiveness, correctness and efficiency of the proposed DPP-IUA is empirically verified using historical data.

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)