This paper presents a novel adaptive cuckoo search (ACS) algorithm for optimization. The
step size is made adaptive from the knowledge of its fitness function value and its current …

In this paper, we introduced a practical version of golden section search algorithm to
optimize multi/uni-modal objective functions. Accordingly, this study presented a novel …

The identification of a module's fault-proneness is very important for minimizing cost and
improving the effectiveness of the software development process. How to obtain the …

In recent, the development of the automotive semi-active suspension (SAS) system with the
nonlinear hydraulic adjustable damper (HAD) has attracted widely attention due to its …

This paper studies the parameter estimation problem of Hammerstein output error
autoregressive (OEAR) systems. According to the maximum likelihood principle and the …

Memetic Algorithm (MA) is a combination of Evolutionary Algorithms (EAs) and Local Search
(LS) operators known as hybrid algorithms. In this paper, an efficient MA with a novel LS …

An enhanced scatter search (eSS) with combined opposition-based learning algorithm is
proposed to solve large-scale parameter estimation in kinetic models of biochemical …

The basic challenge associated with the design of vehicle suspension system is the
attainment of an optimal trade-off between the various design objectives. This study presents …

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

Many studies have been conducted by researchers globally in the recent past on the control
schemes to enhance the performance of rotary single inverted pendulum (RSIP). The …