Bilal H. Abed-alguni

Orcid: 0000-0002-7481-4854

According to our database1, Bilal H. Abed-alguni authored at least 16 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Improved discrete salp swarm algorithm using exploration and exploitation techniques for feature selection in intrusion detection systems.
J. Supercomput., December, 2023

Binary improved white shark algorithm for intrusion detection systems.
Neural Comput. Appl., September, 2023

Opposition-based sine cosine optimizer utilizing refraction learning and variable neighborhood search for feature selection.
Appl. Intell., June, 2023

2022
Discrete hybrid cuckoo search and simulated annealing algorithm for solving the job shop scheduling problem.
J. Supercomput., 2022

Discrete Jaya with refraction learning and three mutation methods for the permutation flow shop scheduling problem.
J. Supercomput., 2022

Island-based Cuckoo Search with elite opposition-based learning and multiple mutation methods for solving optimization problems.
Soft Comput., 2022

Improved Salp swarm algorithm for solving single-objective continuous optimization problems.
Appl. Intell., 2022

2021
Exploratory cuckoo search for solving single-objective optimization problems.
Soft Comput., 2021

Distributed Grey Wolf Optimizer for scheduling of workflow applications in cloud environments.
Appl. Soft Comput., 2021

2020
Hybridizing the Cuckoo Search Algorithm with Different Mutation Operators for Numerical Optimization Problems.
J. Intell. Syst., 2020

Intelligent hybrid cuckoo search and <i>β</i>-hill climbing algorithm.
J. King Saud Univ. Comput. Inf. Sci., 2020

Hybrid whale optimisation and β-hill climbing algorithm for continuous optimisation problems.
Int. J. Comput. Sci. Math., 2020

2019
A Hybrid Cuckoo Search and Simulated Annealing Algorithm.
J. Intell. Syst., 2019

Island-based whale optimisation algorithm for continuous optimisation problems.
Int. J. Reason. based Intell. Syst., 2019

2015
Erratum to: A multi-agent cooperative reinforcement learning model using a hierarchy of consultants, tutors and workers.
Vietnam. J. Comput. Sci., 2015

A multi-agent cooperative reinforcement learning model using a hierarchy of consultants, tutors and workers.
Vietnam. J. Comput. Sci., 2015


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