Demonstration of a nonlinear dynamic model of traffic flow planning in intelligent transport systems

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 621, P. 03015 - 03015

Published: Jan. 1, 2025

The significant relevance of the problems traffic flow planning in intelligent transport systems is pointed out, with a critical analysis previous scientific studies on this issue. proposed nonlinear dynamic model was characterised. Mathematical modelling methods, methods correlation and regression analysis, expert assessments were used. A demonstration carried an example data developed, corresponding optimisation problem formulated solved. separate matrix prepared for each group constraints. written format Portfolio Safeguard package. To solve problem, Solver VANGRB chosen, which uses Gurobi contained 1,280 variables C k sr y each, as well approximately 50,000 x jsrkt . matrices about 1,280, 30,000, 18,000, 1,176 rows optimal values found pairs AB, AC, AD, AE, BA, CA all types agreements.

Language: Английский

Modelling the delivery of special cargo categories as a mandatory component of an intelligent transport system

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 621, P. 03008 - 03008

Published: Jan. 1, 2025

The intelligentisation of the global economy continues to grow, and this process is only going deepen expand in future. Modelling delivery becoming one priority components transport. methodological basis study provisions theories transport processes systems, logistics, management concept sustainable development. Mathematical modelling methods were applied relevant models with discrete continuous variables nonlinear functions designed. proposes a mathematical toolkit for special categories cargo, which allows logistics operator optimise using principles intelligence. proposed implemented as result forming scheme cargo air-road connection justifying its components, clarifying subtask delivering consignment by road, well creating equations number samples perishable goods destination, their weight, volume, packages types destinations, determining urgency shipments characteristics. meets modern requirements trends, scientifically substantiated appropriately tested.

Language: Английский

Multi-agent deep reinforcement learning based multiple access for underwater cognitive acoustic sensor networks

Computers & Electrical Engineering, Journal Year: 2024, Volume and Issue: 120, P. 109819 - 109819

Published: Nov. 6, 2024

Language: Английский