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: "big data analytics for dynamic energy management in smart grids"
  Abstract: The smart electricity grid enables a two-way flow of power and data between suppliers and consumers in order to facilitate the power flow optimization in terms of economic efficiency, reliability and sustainability. This infrastructure permits the consumers and the micro-energy producers to take a more active role in the electricity market and the dynamic energy management (DEM). The most important challenge in a smart grid (SG) is how to take advantage of the users' participation in order to reduce the cost of power. However, effective DEM depends critically on load and renewable production forecasting. This calls for intelligent methods and solutions for the real-time exploitation of large volumes of data generated by the vast amount of smart meters. Hence, robust data analytics, high performance computing, efficient data network management, and cloud computing techniques are critical towards the optimized operation of SGs. This research aims to highlight the big data issues and challenges faced by the DEM employed in SG networks. It also provides a brief description of the most commonly used data processing methods in the literature, and proposes a promising direction for future research in the field.

Connected through hyperedge HE-1 (induced by source paper "bmi a behavior measurement indicator for fuel poverty using aggregated load readings from smart meters"):
  with members:
    - "detecting activities of daily living and routine behaviours in dementia patients living alone using smart meter load disaggregation"
    - "learning to exploit invariances in clinical time series data using sequence transformer networks"

Connected through hyperedge HE-2 (induced by source paper "homogeneous and mixed energy communities discovery with spatial temporal net energy"):
  with members:
    - "preserving both privacy and utility in network trace anonymization"
    - "privacy preserving and collusion resistant energy sharing"
    - "smart microgrids overview and outlook"
    - "community detection in networks with node attributes"
    - "a classification for community discovery methods in complex networks"

Connected through hyperedge HE-3 (induced by source paper "fog computing in iot aided smart grid transition requirements prospects status quos and challenges"):
  with members:
    - "charging and discharging of plug in electric vehicles pevs in vehicle to grid v2g systems a cyber insurance based model"
    - "fog assisted operational cost reduction for cloud data centers"

Connected through hyperedge HE-4 (induced by source paper "real time load prediction with high velocity smart home data stream"):
  with members:
    - "mllib machine learning in apache spark"
    - "household electricity demand forecasting benchmarking state of the art methods"

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.DB(Databases)