Fog/edge computing-based IoT (FECIoT): Architecture, applications, and research issues
The Internet-of-Things (IoT) is the future of the Internet, where everything will be connected.
Studies have revealed that fog/edge computing-based services will play a major role in …
Studies have revealed that fog/edge computing-based services will play a major role in …
Combinatorial optimization problems and metaheuristics: Review, challenges, design, and development
F Peres, M Castelli - Applied Sciences, 2021 - mdpi.com
In the past few decades, metaheuristics have demonstrated their suitability in addressing
complex problems over different domains. This success drives the scientific community …
complex problems over different domains. This success drives the scientific community …
Trajectory tracking control of an autonomous underwater vehicle using Lyapunov-based model predictive control
This paper studies the trajectory tracking control problem of an autonomous underwater
vehicle (AUV). We develop a novel Lyapunov-based model predictive control (LMPC) …
vehicle (AUV). We develop a novel Lyapunov-based model predictive control (LMPC) …
A self-adaptive Harris Hawks optimization algorithm with opposition-based learning and chaotic local search strategy for global optimization and feature selection
AG Hussien, M Amin - International Journal of Machine Learning and …, 2022 - Springer
Abstract Harris Hawks Optimization is a recently proposed algorithm inspired by the
cooperative manner and chasing behavior of harris. However, from the experimental results …
cooperative manner and chasing behavior of harris. However, from the experimental results …
Joint reflecting and precoding designs for SER minimization in reconfigurable intelligent surfaces assisted MIMO systems
This paper investigates the use of a reconfigurable intelligent surface (RIS) to aid point-to-
point multi-data-stream multiple-input multiple-output (MIMO) wireless communications. With …
point multi-data-stream multiple-input multiple-output (MIMO) wireless communications. With …
Quality and diversity optimization: A unifying modular framework
The optimization of functions to find the best solution according to one or several objectives
has a central role in many engineering and research fields. Recently, a new family of …
has a central role in many engineering and research fields. Recently, a new family of …
A real-time nonlinear model predictive controller for yaw motion optimization of distributed drive electric vehicles
This paper proposes a real-time nonlinear model predictive control (NMPC) strategy for
direct yaw moment control (DYC) of distributed drive electric vehicles (DDEVs). The NMPC …
direct yaw moment control (DYC) of distributed drive electric vehicles (DDEVs). The NMPC …
[图书][B] Introduction to algorithms for data mining and machine learning
XS Yang - 2019 - books.google.com
Introduction to Algorithms for Data Mining and Machine Learning introduces the essential
ideas behind all key algorithms and techniques for data mining and machine learning, along …
ideas behind all key algorithms and techniques for data mining and machine learning, along …
Chaotic opposition-based grey-wolf optimization algorithm based on differential evolution and disruption operator for global optimization
In this paper, an improved version of the Grey Wolf Optimizer (GWO) is proposed to improve
the exploration and the exploitation ability of the GWO algorithm. This improvement is …
the exploration and the exploitation ability of the GWO algorithm. This improvement is …
Integrated path planning and tracking control of an AUV: A unified receding horizon optimization approach
This paper attempts to develop a unified receding horizon optimization (RHO) scheme for
the integrated path planning and tracking control of an autonomous underwater vehicle …
the integrated path planning and tracking control of an autonomous underwater vehicle …