This paper aims to provide a review of the conceptual design and theoretical framework of
the main control schemes proposed in the literature for unmanned underwater vehicles …

A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …

This research focuses on presenting new models based on classifiers that can be applied to
various problems. Adaboost is a type of ensemble learning machine that uses classifiers that …

Moth search (MS) is a nature-inspired metaheuristic optimization algorithm based on the
most representative characteristics of moths, Lévy flights and phototaxis. Phototaxis signifies …

Coefficient of consolidation (Cv) is an important parameter in the designing of civil
engineering structures founded on soil. Determination of the Cv in the laboratory is beset …

Reinforcement learning (RL) is a promising technique for designing a model-free controller
by interacting with the environment. Several researchers have applied RL to autonomous …

Lévy flight is a random walk mechanism which can make large jumps at local locations with
a high probability. The probability density distribution of Lévy flight was characterized by …

This manuscript proposes an efficient and novel method for the leader–follower formation
control of multiple autonomous underwater vehicles. The goal is to efficiently allow the …

The efficiency of tunnel boring machines (TBMs) in underground projects has great
significance for the mining and tunneling industries, demanding a reliable estimation of the …

Purpose To solve the path planning problem of the intelligent driving vehicular, this paper
designs a hybrid path planning algorithm based on optimized reinforcement learning (RL) …