The article shows the possibility of describing complex objects with parallel functioning components in the form of structures built on the basis of neural networks. The neural network is represented by an operator matrix, that is, a formal description that gives a universal way to solve many non-standard control problems. Matrix apparatus is shown to significantly improve the efficiency of the method compared to previously known. It is concluded that the representation of the neural network by the operator matrix provides a universal way to solve the problems of transport and information flows management; neuron-like systems based on such representation of the neuron are able to catch complex nonlinear relationships, self-improvement, learning in the process of use. Their use provides ample opportunities for finding and implementing effective solutions to the problems of management and control of flows
Keywords: graph, parallelism, transport and information flow, neural network, synaptic weight, predicate, activation function, operator matrix, neuron, complex systems