26 citations · 241 across the 38 of their papers we have counts for
6 papers · 1 filter
Dynamic Multi Objective Particle Swarm Optimization based on a New Environment Change Detection Strategy
Ahlem Aboud, Raja Fdhila, Adel M. Alimi
The dynamic of real-world optimization problems raises new challenges to the traditional particle swarm optimization (PSO). Responding to these challenges, the dynamic optimization…
Multi Objective Particle Swarm Optimization based Cooperative Agents with Automated Negotiation
Najwa Kouka, Raja Fdhila, Adel M. Alimi
This paper investigates a new hybridization of multi-objective particle swarm optimization (MOPSO) and cooperative agents (MOPSO-CA) to handle the problem of stagnation encounters…
Taylor-based Optimized Recursive Extended Exponential Smoothed Neural Networks Forecasting Method
Emna Krichene, Wael Ouarda, Habib Chabchoub +1
A newly introduced method called Taylor-based Optimized Recursive Extended Exponential Smoothed Neural Networks Forecasting method is applied and extended in this study to forecast…
Hierarchical Bi-level Multi-Objective Evolution of Single- and Multi-layer Echo State Network Autoencoders for Data Representations
Naima Chouikhi, Boudour Ammar, Adel M. Alimi
Echo State Network (ESN) presents a distinguished kind of recurrent neural networks. It is built upon a sparse, random and large hidden infrastructure called reservoir. ESNs have s…
Genesis of Basic and Multi-Layer Echo State Network Recurrent Autoencoders for Efficient Data Representations
Naima Chouikhi, Boudour Ammar, Adel M. Alimi
It is a widely accepted fact that data representations intervene noticeably in machine learning tools. The more they are well defined the better the performance results are. Featur…
Hierarchical Learning Algorithm for the Beta Basis Function Neural Network
Habib Dhahri, Mohamed Adel Alimi
The paper presents a two-level learning method for the design of the Beta Basis Function Neural Network BBFNN. A Genetic Algorithm is employed at the upper level to construct BBFNN…