Improved monarch butterfly optimization for unconstrained global search and neural network training
This work is a seminal attempt to address the drawbacks of the recently proposed monarch
butterfly optimization (MBO) algorithm. This algorithm suffers from premature convergence …
butterfly optimization (MBO) algorithm. This algorithm suffers from premature convergence …
Sentiment analysis for Arabic language: A brief survey of approaches and techniques
With the emergence of Web 2.0 technology and the expansion of on-line social networks,
current Internet users have the ability to add their reviews, ratings and opinions on social …
current Internet users have the ability to add their reviews, ratings and opinions on social …
Automatic selection of hidden neurons and weights in neural networks using grey wolf optimizer based on a hybrid encoding scheme
In neural networks, finding optimal values for the number of hidden neurons and connection
weights simultaneously is considered a challenging task. This is because altering the …
weights simultaneously is considered a challenging task. This is because altering the …
Ant colony optimization for Cuckoo Search algorithm for permutation flow shop scheduling problem
Y Zhang, Y Yu, S Zhang, Y Luo… - Systems Science & …, 2019 - Taylor & Francis
ABSTRACT A Cuckoo Search (CS) algorithm based on ant colony algorithm is proposed for
scheduling problem in permutation flow shop scheduling problem (PFSP). When the raised …
scheduling problem in permutation flow shop scheduling problem (PFSP). When the raised …
A hybrid multi-gene genetic programming with capuchin search algorithm for modeling a nonlinear challenge problem: Modeling industrial winding process, case …
M Braik - Neural Processing Letters, 2021 - Springer
Motivated by the increasing complexity and operational productivity of industrial processes,
the need for efficient modeling schemes for industrial systems is highly demanded. This …
the need for efficient modeling schemes for industrial systems is highly demanded. This …
Nature-inspired metaheuristics search algorithms for solving the economic load dispatch problem of power system: a comparison study
This work proposes a new approach in addressing Economic Load Dispatch (ELD)
optimization problem in power unit systems using nature-inspired metaheuristics search …
optimization problem in power unit systems using nature-inspired metaheuristics search …
Mathematical model for approximating shield tunneling-induced surface settlement via multi-gene genetic programming
Obtaining an accurate estimation of surface settlement during tunnel excavation is
challenging due to the many factors that influence settlement. This study developed a …
challenging due to the many factors that influence settlement. This study developed a …
Enhanced cuckoo search algorithm for industrial winding process modeling
Modeling of nonlinear industrial systems embraces two key stages: selection of a model
structure with a compact parameter list, and selection of an algorithm to estimate the …
structure with a compact parameter list, and selection of an algorithm to estimate the …
Bidirectional reservoir networks trained using SVM privileged information for manufacturing process modeling
In the last decade, a wide range of machine learning approaches were proposed and
experimented to model highly nonlinear manufacturing processes. However, improving the …
experimented to model highly nonlinear manufacturing processes. However, improving the …
A novel hybrid meta-heuristic algorithm for optimization problems
W Gai, C Qu, J Liu, J Zhang - Systems Science & Control …, 2018 - Taylor & Francis
This paper presents a novel hybrid meta-heuristic algorithm called HMGSG to solve the
optimization problems. In the proposed HMGSG algorithm, a spiral-shaped path for grey wolf …
optimization problems. In the proposed HMGSG algorithm, a spiral-shaped path for grey wolf …