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: "an online rfid localization in the manufacturing shopfloor"
  Abstract: Radio Frequency Identification technology has gained popularity for cheap and easy deployment. In the realm of manufacturing shopfloor, it can be used to track the location of manufacturing objects to achieve better efficiency. The underlying challenge of localization lies in the nonstationary characteristics of manufacturing shopfloor which calls for an adaptive life-long learning strategy in order to arrive at accurate localization results. This paper presents an evolving model based on a novel evolving intelligent system, namely evolving Type-2 Quantum Fuzzy Neural Network (eT2QFNN), which features an interval type-2 quantum fuzzy set with uncertain jump positions. The quantum fuzzy set possesses a graded membership degree which enables better identification of overlaps between classes. The eT2QFNN works fully in the evolving mode, where all parameters including the number of rules are automatically adjusted and generated on the fly. The parameter adjustment scenario relies on decoupled extended Kalman filter method. Our numerical study shows that eT2QFNN is able to deliver comparable accuracy compared to state-of-the-art algorithms.

Connected through hyperedge HE-1 (induced by source paper "devdan deep evolving denoising autoencoder"):
  with members:
    - "online tool condition monitoring based on parsimonious ensemble"
    - "autonomous deep learning continual learning approach for dynamic environments"
    - "evolving ensemble fuzzy classifier"
    - "deep learning for iot big data and streaming analytics a survey"
    - "progressive neural networks"
    - "lifelong learning with dynamically expandable networks"
    - "stochastic configuration networks fundamentals and algorithms"
    - "online deep learning learning deep neural networks on the fly"

Connected through hyperedge HE-2 (induced by source paper "autonomous deep learning continual learning approach for dynamic environments"):
  with members:
    - "online tool condition monitoring based on parsimonious ensemble"
    - "autonomous deep learning incremental learning of denoising autoencoder for evolving data streams"
    - "an incremental construction of deep neuro fuzzy system for continual learning of non stationary data streams"
    - "evolving ensemble fuzzy classifier"
    - "progressive neural networks"
    - "lifelong learning with dynamically expandable networks"
    - "online deep learning learning deep neural networks on the fly"
    - "overcoming catastrophic forgetting in neural networks"

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.AI(Artificial Intelligence)