21 citations · 24 across the 19 of their papers we have counts for
10 papers · 1 filter
A Primer on Evolutionary Optimization Frameworks for Near-Field Multi-Source Localization
Seyed Jalaleddin Mousavirad, Parisa Ramezani, Mattias O'Nils +1
This paper introduces evolutionary optimization as a grid-free training-free continuous-domain search mechanism for near-field multi-source localization, addressing the major limit…
Robust Energy Consumption Prediction with a Missing Value-Resilient Metaheuristic-based Neural Network in Mobile App Development
Seyed Jalaleddin Mousavirad, Luís A. Alexandre
Energy consumption is a fundamental concern in mobile application development, bearing substantial significance for both developers and end-users. Main objective of this research i…
A Metaheuristic-based Machine Learning Approach for Energy Prediction in Mobile App Development
Seyed Jalaleddin Mousavirad, Luís A. Alexandre
Energy consumption plays a vital role in mobile App development for developers and end-users, and it is considered one of the most crucial factors for purchasing a smartphone. In a…
A Cluster-Based Opposition Differential Evolution Algorithm Boosted by a Local Search for ECG Signal Classification
Mehran Pourvahab, Seyed Jalaleddin Mousavirad, Virginie Felizardo +6
Electrocardiogram (ECG) signals, which capture the heart's electrical activity, are used to diagnose and monitor cardiac problems. The accurate classification of ECG signals, parti…
Metaheuristic-based Energy-aware Image Compression for Mobile App Development
Seyed Jalaleddin Mousavirad, Luís A Alexandre
The JPEG standard is widely used in different image processing applications. One of the main components of the JPEG standard is the quantisation table (QT) since it plays a vital r…
HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space
Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin +3
The human mental search (HMS) algorithm is a relatively recent population-based metaheuristic algorithm, which has shown competitive performance in solving complex optimisation pro…
MCS-HMS: A Multi-Cluster Selection Strategy for the Human Mental Search Algorithm
Ehsan Bojnordi, Seyed Jalaleddin Mousavirad, Gerald Schaefer +1
Population-based metaheuristic algorithms have received significant attention in global optimisation. Human Mental Search (HMS) is a relatively recent population-based metaheuristi…
An Enhanced Differential Evolution Algorithm Using a Novel Clustering-based Mutation Operator
Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin +3
Differential evolution (DE) is an effective population-based metaheuristic algorithm for solving complex optimisation problems. However, the performance of DE is sensitive to the m…
Differential Evolution-based Neural Network Training Incorporating a Centroid-based Strategy and Dynamic Opposition-based Learning
Seyed Jalaleddin Mousavirad, Diego Oliva, Salvador Hinojosa +1
Training multi-layer neural networks (MLNNs), a challenging task, involves finding appropriate weights and biases. MLNN training is important since the performance of MLNNs is main…
Towards Solving Large-scale Expensive Optimization Problems Efficiently Using Coordinate Descent Algorithm
Shahryar Rahnamayan, Seyed Jalaleddin Mousavirad
Many real-world problems are categorized as large-scale problems, and metaheuristic algorithms as an alternative method to solve large-scale problem; they need the evaluation of ma…