Relevance: 6/10 This paper is more close to control engineering than to main AI topics. The neural network is used, but not in way like deep learning or reinforcement learning. It is not clear if this work is interesting for many AI researchers. If author can compare with more AI method, it will help. Significance: 8/10 The idea of self-organizing RBF network with spiking neuron mechanism is interesting. I think this is good for control system which is nonlinear and changing. The example of wastewater plant is practical and realistic. It show the method is working. But it is only one example. No test in other systems. Also, the paper not say if the method can be used for more fast or real-time system. Originality: 7/10 Author combine many known idea like RBF, recurrent NN, Lyapunov and spiking to make one model. The growing and pruning of hidden neuron is done with new idea. This part I think is creative. But I not understand why this growing method is better than others. Why us...
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