Search Results for author: Diego Oliva

Found 8 papers, 1 papers with code

A Novel Plagiarism Detection Approach Combining BERT-based Word Embedding, Attention-based LSTMs and an Improved Differential Evolution Algorithm

no code implementations3 May 2023 Seyed Vahid Moravvej, Seyed Jalaleddin Mousavirad, Diego Oliva, Fardin Mohammadi

In this article, we propose a novel method for detecting plagiarism that is based on attention mechanism-based long short-term memory (LSTM) and bidirectional encoder representations from transformers (BERT) word embedding, enhanced with optimized differential evolution (DE) method for pre-training and a focal loss function for training.

A new Hyper-heuristic based on Adaptive Simulated Annealing and Reinforcement Learning for the Capacitated Electric Vehicle Routing Problem

no code implementations7 Jun 2022 Erick Rodríguez-Esparza, Antonio D Masegosa, Diego Oliva, Enrique Onieva

Electric vehicles (EVs) have been adopted in urban areas to reduce environmental pollution and global warming as a result of the increasing number of freight vehicles.

HMS-OS: Improving the Human Mental Search Optimisation Algorithm by Grouping in both Search and Objective Space

no code implementations19 Nov 2021 Seyed Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin, Diego Oliva, Mahshid Helali Moghadam, Mehrdad Saadatmand

The human mental search (HMS) algorithm is a relatively recent population-based metaheuristic algorithm, which has shown competitive performance in solving complex optimisation problems.

Clustering

Differential Evolution-based Neural Network Training Incorporating a Centroid-based Strategy and Dynamic Opposition-based Learning

no code implementations29 Jun 2021 Seyed Jalaleddin Mousavirad, Diego Oliva, Salvador Hinojosa, Gerald Schaefer

This improves exploitation since the new member is obtained based on the best individuals, while the employed DOBL strategy, which uses the opposite of an individual, leads to enhanced exploration.

A multilevel thresholding algorithm using Electromagnetism Optimization

no code implementations24 Jun 2014 Diego Oliva, Erik Cuevas, Gonzalo Pajares, Daniel Zaldivar, Valentin Osuna

Such samples build each particle in the EMO context whereas its quality is evaluated considering the objective that is function employed by the Otsu or Kapur method.

Image Segmentation Segmentation +1

Circle detection using electro-magnetism optimization

no code implementations30 May 2014 Erik Cuevas, Diego Oliva, Daniel Zaldivar, Marco Perez-Cisneros, Humberto Sossa

The EMO algorithm is used to find the circle candidate that is better related with the real circle present in the image according to the objective function.

Opposition Based ElectromagnetismLike for Global Optimization

no code implementations20 May 2014 Erik Cuevas, Diego Oliva, Daniel Zaldivar, Marco Perez, Gonzalo Pajares

Electromagnetismlike Optimization (EMO) is a global optimization algorithm, particularly well suited to solve problems featuring nonlinear and multimodal cost functions.

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