The “curse of dimensionality” is one of the largest problems that influences the quality of the
optimization process in most data mining, pattern recognition, and machine learning tasks …

Nonlinear state space modeling of a nuclear reactor has been done for the purpose of
controlling its global power in load following mode. The nonlinear state space model has …

This paper puts forward computational intelligence-based sigmoidal type trajectory
scheduling for the control of nuclear research reactors. In order to calculate parameters of …

In this paper, a closed-loop fuzzy logic controller based on the particle swarm optimization
algorithm is proposed for controlling the power level of nuclear research reactors. The …

This paper proposes a nonlinear control approach using dynamic neural network-based
input–output feedback linearization to resolve the inherent conflicting performance criteria …

In this paper, the problem of the global dissipativity of high-order Hopfield bidirectional
associative memory neural networks with time-varying coefficients and distributed delays is …

Major factors of project success include using tools of performance measurements and
feedbacks. Earned value management (EVM) is a unique issue within megaprojects due to …

In this article, we investigate the problem of fixed-time stabilization (FXTSB) of delayed
neural networks (DNNs). Firstly, some new general conditions on the control law are …

Dynamic optimization has become an increasingly important aspect of chemical processes
in the past few decades. To solve such chemical dynamic optimization problems (DOPs) …

This work presents a new approach for solving classification and learning problems. The
Successive Geometric Segmentation technique is applied to encapsulate large datasets by …