Asghar Moeini

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In this paper, a new method is proposed to design a sliding mode controller with variable boundary layer for a nonlinear system. In this method, model predictive control (MPC) is used to predict the future boundary layer thickness. In order to predict the behavior of the nonlinear system, a neural network model is used as an internal model. The simulation(More)
In this paper, we present a new way to simulate Turing machines using a specific form of Petri nets such that the resulting nets are capable of thoroughly describing behavior of the input Turing machines. We model every element of a Turing machine’s tuple F) q0, δ, Σ, b, Γ, Q, (i.e., with an equivalent translation in Colored Petri net’s set of elements with(More)
Davoud Mougouei School of Computer Science, Engineering, and Mathematics Flinders University Adelaide, Australia davoud.mougouei@ƒinders.edu.au David M. W. Powers School of Computer Science, Engineering, and Mathematics Flinders University Adelaide, Australia david.powers@ƒinders.edu.au Asghar Moeini School of Computer Science, Engineering, and Mathematics(More)
Multi-objective optimisation problems normally have not one but a set of solutions, which are called Pareto-optimal solutions or non-dominated solutions. Once a Pareto-optimal set has been obtained, the decision-maker faces the challenge of analysing a potentially large set of solutions. Selecting one solution over others can be quite a challenging task(More)
The existing software release planning models aim to find a subset of software requirements with the highest value on the assumption that the value of a selected subset of requirements equals to the Accumulated Value (AV) of that subset. This assumption however, does not hold due to the Value-related Dependencies among software requirements. To address(More)
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