In this paper, we introduce a hybrid approach based on neural network and optimization teqnique to solve ordinary differential equation. In proposed model we use heyperbolic secont transformation function in hiden layer of neural network part and bfgs teqnique in optimization part. In comparison with existing similar neural networks proposed model provides solutions with high accuracy. Numerica...

A Reliability-Based Design Optimization (RBDO) framework is presented that accounts for stochastic variations in structural parameters and operating conditions. The reliability index calculation is itself an iterative process, potentially employing an optimization technique to find the shortest distance from the origin to the limit-state boundary in a standard normal space. Monte Carlo simulati...

This study concerns numerical simulation, modeling and optimization of aerodynamic stall control using a synthetic jet actuator. Thenumerical simulation was carried out by a large-eddy simulation that employs a RNG-based model as the subgrid-scale model. The flow around a NACA0015 airfoil, including a synthetic jet located at 10 % of the chord, is studied under Reynolds number Re = 12.7 × 106 a...

A quantile is a popular performance measure for stochastic system to evaluate its variability and risk. To reduce the risk, selecting actions that minimize tail quantiles of some loss distributions typically interest decision makers. When distribution observed via simulations, evaluating optimizing can be challenging, especially when simulations are expensive as it may cost large number simulat...

always allocate man - machine is considered as one of the main concerns of operation planners. utilize an appropriate using of workforce in situations that the operation is dependent on the capabilities of the workforce, can lead to improve the systems efficiency and productivity indicators. since these issues, categories in np-hard problems, so optimization and solving the mathematical model o...