Structural changes were the main focus of many studies in recent years. Changes which alter the socio-economic status of a nation from deprived and traditional nature to a developed and modern one. The main hypothesis of this study is that, the economic development does not occur through a regular flow of life (linear fashion), and without resilience, but it certainly needs to pass through a mo...

Quantum electrodynamics predicts that the quantum vacuum is birefringent, but due to very small cross-section this yet be confirmed by experiment. Vacuum birefringence arises as elastic part of photon-photon scattering; inelastic Breit-Wheeler pair-production. We outline how measurements photon-polarised nonlinear process can used infer a measurement birefringence. As an example scenario, we ca...

Multivariate reward processes with reward functions of constant rates, defined on a semi-Markov process, first were studied by Masuda and Sumita, 1991. Reward processes with nonlinear reward functions were introduced in Soltani, 1996. In this work we study a multivariate process , , where are reward processes with nonlinear reward functions respectively. The Laplace transform of the covar...

This article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (MPC) of a chemical plant. A combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (MIMO) process with time delays.  An optimization procedure for a neural MPC algorithm based on this model is then developed. T...

Model-based predictive control (MPC) is one of the most efficient techniques that is widely used in industrial applications. In such controllers, increasing the prediction horizon results in better selection of the optimal control signal sequence. On the other hand, increasing the prediction horizon increase the computational time of the optimization process which make it impossible to be imple...

in this paper, we present a capable algorithm for solving a class of nonlinear optimal control problems (ocp's). the approach rest mainly on the differential transform method (dtm) which is one of the approximate methods. the dtm is a powerful and efficient technique for finding solutions of nonlinear equations without the need of a linearization process. utilizing this approach, the optim...