Reduced Gradient Method and its Generalization via Stochastic Perturbation

Study of Boundary Layer Convective Heat Transfer with Low Pressure Gradient Over a Flat Plate Via He’s Homotopy Perturbation Method

Semantic Noise Modeling for Better Representation Learning

Latent representation learned from multi-layered neural networks via hierarchical feature abstraction enables recent success of deep learning. Under the deep learning framework, generalization performance highly depends on the learned latent representation which is obtained from an appropriate training scenario with a taskspecific objective on a designed network model. In this work, we propose ...

Simulation Optimization of Traffic Light Signal Timings via Perturbation Analysis

In this paper, we develop a simulation optimization algorithm for determining the traffic light signal timings for an intersection of two one-way street traffic flows modeled as single-server queues. The system performance is estimated via stochastic discreteevent simulation, and gradient-based search based on stochastic approximation is applied. In particular, we use smoothed perturbation anal...

Perturbation Analysis

Perturbation analysis (PA) is a sample path technique for analyzing changes in the performance of stochastic systems due to changes in system parameters. In terms of stochastic simulation | the main setting for the application of PA | the objective is to estimate sensitivities of the performance measures of interest with respect to system parameters while obtaining estimates of performance itse...

Numerical Solution of Optimal Heating of Temperature Field in Uncertain Environment Modelled by the use of Boundary Control

‎In the present paper‎, ‎optimal heating of temperature field which is modelled as a boundary optimal control problem‎, ‎is investigated in the uncertain environments and then it is solved numerically‎. ‎In physical modelling‎, ‎a partial differential equation with stochastic input and stochastic parameter are applied as the constraint of the optimal control problem‎. ‎Controls are implemented ...