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The problem of optimization of the rolling dynamics model is considered. That providing safe movement at high frequency when interacting with the railway. Moreover, allowing to evaluate the dynamic parameters when designing new and modernizing existing locomotives. The object of this research is a rail transport dynamic system model. The articles purpose is to increase the efficiency of the digital hardware in the rolling stock loop model by optimizing the organization of the computing process. The mathematical model analysis of the object made it possible to attribute it to the class of hard real-time systems. The computation of the model phase variables with different frequencies is necessary to optimize the simulation time of the train movements and is performed by splitting the original algorithm into parallel threads. The developed planning algorithm and the cyclic schedule implementation for the model of a dynamic real-time object consider microarchitecture solutions of symmetric multiprocessor systems with shared memory and methods for optimizing software tools. The experiments confirmed the operability of the optimized model. Also, allow us to recommend it for practical use in studying objects and determine the dynamic force of trolley structural elements during operation. Analysis of the optimized model simulation results, using cyclic schedules shows the correspondence of the obtained simulation results to the standard. The main advantage of the model is the increase in productivity when performing data processing by reducing the processor time. The optimized cyclic schedule algorithm of the semi-natural modeling platform is used for the subsequent development of the control system in real and accelerated time scales.
This paper summarises a successful application of functional programming within a commercial environment. We report on experience at Accentures Financial Services Solution Centre in London with simulating an object-oriented financial system in order
Recently, there has been increasing interest in transparency and interpretability in Deep Reinforcement Learning (DRL) systems. Verbal explanations, as the most natural way of communication in our daily life, deserve more attention, since they allow
Linear models are regularly used for mapping cores to tiles in a chip. System-on-Chip (SoC) design requires integration of functional units with varying sizes, but conventional models only account for identical-sized cores. Linear models cannot calcu
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The effectiveness of rapid rail transit system is analyzed using tools of complex network for the first time. We evaluated the effectiveness of the system in Beijing quantitatively from different perspectives, including descriptive statistics analysi