H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 30 Citations 4,707 157 World Ranking 8528 National Ranking 18

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Mathematical optimization

His primary areas of investigation include Artificial intelligence, Mathematical optimization, Metaheuristic, Harmony search and Optimization problem. His work focuses on many connections between Artificial intelligence and other disciplines, such as Genetic algorithm, that overlap with his field of interest in Pattern recognition. His Mathematical optimization research integrates issues from Algorithm and Natural selection, Selection.

His Metaheuristic research includes elements of Variety, Hill climbing, Local search and Cluster analysis. Mohammed Azmi Al-Betar focuses mostly in the field of Harmony search, narrowing it down to matters related to Particle swarm optimization and, in some cases, Memetic algorithm and Search algorithm. His research investigates the connection between Optimization problem and topics such as Swarm intelligence that intersect with issues in Combinatorial optimization.

His most cited work include:

  • A comprehensive review (354 citations)
  • Grey wolf optimizer: a review of recent variants and applications (187 citations)
  • A harmony search algorithm for university course timetabling (154 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Artificial intelligence, Mathematical optimization, Harmony search, Metaheuristic and Algorithm. Mohammed Azmi Al-Betar combines subjects such as Machine learning and Pattern recognition with his study of Artificial intelligence. The study incorporates disciplines such as Selection and Benchmark in addition to Mathematical optimization.

Mohammed Azmi Al-Betar has researched Harmony search in several fields, including Particle swarm optimization and Heuristics. His Metaheuristic research is multidisciplinary, incorporating perspectives in Variety and Continuous optimization. His work deals with themes such as Swarm behaviour, Feature selection and Support vector machine, which intersect with Algorithm.

He most often published in these fields:

  • Artificial intelligence (49.71%)
  • Mathematical optimization (48.55%)
  • Harmony search (36.99%)

What were the highlights of his more recent work (between 2019-2021)?

  • Algorithm (28.90%)
  • Metaheuristic (34.10%)
  • Optimization problem (20.23%)

In recent papers he was focusing on the following fields of study:

Algorithm, Metaheuristic, Optimization problem, Data mining and Artificial intelligence are his primary areas of study. Mohammed Azmi Al-Betar works mostly in the field of Algorithm, limiting it down to concerns involving Feature selection and, occasionally, Benchmark, Classifier and Optimization algorithm. His Optimization problem research focuses on Local search and how it relates to Computational intelligence.

His study on Artificial intelligence also encompasses disciplines like

  • Pattern recognition which is related to area like Noise reduction,
  • Machine learning, which have a strong connection to Herd immunity. His study looks at the intersection of Particle swarm optimization and topics like Harmony search with Heuristics. His research integrates issues of Natural selection and Selection in his study of Mathematical optimization.

Between 2019 and 2021, his most popular works were:

  • An improved Dragonfly Algorithm for feature selection (23 citations)
  • EEG Signals Denoising Using Optimal Wavelet Transform Hybridized With Efficient Metaheuristic Methods (20 citations)
  • Link-based multi-verse optimizer for text documents clustering (16 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Algorithm

His main research concerns Algorithm, Feature selection, Metaheuristic, Artificial intelligence and Benchmark. The Algorithm study combines topics in areas such as Time domain, Optimization algorithm, Classifier and Biometrics. His Feature selection study integrates concerns from other disciplines, such as Swarm behaviour, Dragonfly algorithm and Fitness function.

Mohammed Azmi Al-Betar interconnects Machine learning and Pattern recognition in the investigation of issues within Artificial intelligence. His biological study deals with issues like Noise reduction, which deal with fields such as Harmony search, Genetic algorithm and Particle swarm optimization. His Hill climbing research is within the category of Mathematical optimization.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

A comprehensive review

Asaju Laaro Bolaji;Mohammed Azmi Al-Betar;Mohammed A. Awadallah;Ahamad Tajudin Khader.
soft computing (2016)

609 Citations

Grey wolf optimizer: a review of recent variants and applications

Hossam Faris;Ibrahim Aljarah;Mohammed Azmi Al-Betar;Seyedali Mirjalili.
Neural Computing and Applications (2018)

256 Citations

A harmony search algorithm for university course timetabling

Mohammed Azmi Al-Betar;Ahamad Tajudin Khader.
Annals of Operations Research (2012)

244 Citations

A survey on applications and variants of the cuckoo search algorithm

Mohammad Shehab;Ahamad Tajudin Khader;Mohammed Azmi Al-Betar.
Applied Soft Computing (2017)

179 Citations

Text feature selection with a robust weight scheme and dynamic dimension reduction to text document clustering

Laith Mohammad Abualigah;Ahamad Tajudin Khader;Mohammed Azmi Al-Betar;Osama Ahmad Alomari.
Expert Systems With Applications (2017)

172 Citations

Artificial bee colony algorithm, its variants and applications: A survey.

Asaju La'aro Bolaji;Ahamad Tajudin Khader;Mohammed Azmi Al-Betar;Mohammed A. Awadallah.
(2013)

164 Citations

University Course Timetabling Using a Hybrid Harmony Search Metaheuristic Algorithm

M. A. Al-Betar;A. T. Khader;M. Zaman.
systems man and cybernetics (2012)

125 Citations

$$eta$$ β -Hill climbing: an exploratory local search

Mohammed Azmi Al-Betar.
Neural Computing and Applications (2017)

112 Citations

Novel selection schemes for harmony search

Mohammed Azmi Al-Betar;Mohammed Azmi Al-Betar;Iyad Abu Doush;Ahamad Tajudin Khader;Mohammed A. Awadallah.
Applied Mathematics and Computation (2012)

100 Citations

Tournament-based harmony search algorithm for non-convex economic load dispatch problem

Mohammed Azmi Al-Betar;Mohammed A. Awadallah;Ahamad Tajudin Khader;Asaju La'aro Bolaji.
soft computing (2016)

85 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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