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Enhancing a Multi-population Optimisation Approach with a Dynamic Transformation Scheme
The adaptive multi-population optimisation (AMPO) algorithm is an intelligent meta-heuristic search method utilising multiple search groups to...
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Firefly Algorithm and Deep Neural Network Approach for Intrusion Detection
Metaheuristic optimization has grown in popularity as a way for solving complex issues that are difficult to solve using traditional methods. With...
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A survey, taxonomy and progress evaluation of three decades of swarm optimisation
While the concept of swarm intelligence was introduced in 1980s, the first swarm optimisation algorithm was introduced a decade later, in 1992. In...
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The Analysis of Hybrid Brain Storm Optimisation Approaches in Feature Selection
The volume of data available has risen significantly in recent years due to advancements in data gathering techniques in different fields. The...
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A brick-up model for recombining metaheuristic optimisation algorithm using analytic hierarchy process
Most swarm intelligence algorithms are stochastic metaheuristic algorithms in nature, and thus they may not solve all optimisation problems...
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An Analysis on Hybrid Brain Storm Optimisation Algorithms
Optimisation can be described as the process of finding optimal values for the variables of a given problem in order to minimise or maximise one or...
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A novel hybrid genetic algorithm-based firefly mating algorithm for solving Sudoku
Sudoku is an NP-complete-based mathematical puzzle, which has enormous applications in the domains of steganography, visual cryptography, DNA...
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
In this paper, we consider the problem of learning from imbalanced data. This is one of the main challenges faced by machine learning and...
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A novel enhanced exploration firefly algorithm for global continuous optimization problems
In the global optimization process of the firefly algorithm (FA), there is a need to provide a fast convergence rate and to explore the search space...
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A novel technique based on the improved firefly algorithm coupled with extreme learning machine (ELM-IFF) for predicting the thermal conductivity of soil
Thermal conductivity is a specific thermal property of soil which controls the exchange of thermal energy. If predicted accurately, the thermal...
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A novel software defect prediction model using two-phase grey wolf optimisation for feature selection
The process of accurately predicting software defects is highly crucial during the early period of software development before testing activities...
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Allocating energy-objective aware workflow in distributed edge micro data centres
A workflow is sent from the internet of things (IoT) in the real world to a distributed edge micro data centre (EMDC), which is assigned to various...
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S-LSTM-ATT: a hybrid deep learning approach with optimized features for emotion recognition in electroencephalogram
PurposeHuman emotion recognition using electroencephalograms (EEG) is a critical area of research in human–machine interfaces. Furthermore, EEG data...
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Harris Hawks Optimisation: Using of an Archive
This paper proposes an enhanced variant of the novel and popular Harris Hawks Optimisation (HHO) method. The original HHO algorithm was studied in...
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A metaheuristic approach based on coronavirus herd immunity optimiser for breast cancer diagnosis
As one of the important concepts in epidemiology, herd immunity was recommended to control the COVID-19 pandemic. Inspired by this technique, the...
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Phototropic algorithm for global optimisation problems
Problem solving and decision-making have a vital role to play in both technical and non-technical fields. Some decisions are simple while others...
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Task Scheduling Based Optimized Based Algorithm for Minimization of Energy Consumption in Cloud Computing Environment
Allocating virtual machineries in the cloud optimally for workloads is difficult. In the cloud, finding the best way to schedule tasks is an NP-hard...
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Chaotic Quasi-Oppositional Moth Flame Optimization for Solving Multi-objective Optimal DG Emplacement Problem in Radial Distribution Network
Many scientists are still concerned about power quality and minimising system losses. By lowering distribution losses, distributed generation (DG)...
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A Novel Grey Wolf Optimisation based CNN Classifier for Hyperspectral Image classification
Hyperspectral image (HI) analysis is becoming popular in remote sensing applications due to its high spectral resolution along with high spatial...
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Disease Diagnosis in Grapevines – A Hybrid Resnet-Jaya Approach
Different diseases in grapevines have different kinds of effects on the various parts of the plant, the most drastic of such abnormalities easily...