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: "coordinating truck platooning by clustering pairwise fuel optimal plans"
  Abstract: We consider the fuel-optimal coordination of trucks into platoons. Truck platooning is a promising technology that enables trucks to save significant amounts of fuel by driving close together and thus reducing air drag. We study how fuel-optimal speed profiles for platooning can be computed. A first-order fuel model is considered and pairwise optimal plans are derived. We formulate an optimization problem that combines these pairwise plans into an overall plan for a large number of trucks. The problem resembles a medoids clustering problem. We propose an approximation algorithm similar to the partitioning around medoids algorithm and discuss its convergence. The method is evaluated with Monte Carlo simulations. We demonstrate that the proposed algorithm can compute a plan for thousands of trucks and that significant fuel savings can be achieved.

Connected through hyperedge HE-1 (induced by source paper "control of connected and automated vehicles state of the art and future challenges"):
  with members:
    - "trajectory planning under vehicle dimension constraints using sequential linear programming"
    - "a survey of motion planning and control techniques for self driving urban vehicles"
    - "least costly energy management for series hybrid electric vehicles"
    - "fuel optimal centralized coordination of truck platooning based on shortest paths"
    - "computing feasible vehicle platooning opportunities for transport assignments"
    - "cooperative look ahead control for fuel efficient and safe heavy duty vehicle platooning"

Connected through hyperedge HE-2 (induced by source paper "fuel efficient en route formation of truck platoons"):
  with members:
    - "fuel optimal centralized coordination of truck platooning based on shortest paths"
    - "cyber physical control of road freight transport"

Connected through hyperedge HE-3 (induced by source paper "efficient dynamic programming solution to a platoon coordination merge problem with stochastic travel times"):
  with members:
    - "travel time estimation for urban road networks using low frequency probe vehicle data"

Connected through hyperedge HE-4 (induced by source paper "computing feasible vehicle platooning opportunities for transport assignments"):
  with members:
    - "fuel optimal centralized coordination of truck platooning based on shortest paths"

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)