33 citations · 48 across the 7 of their papers we have counts for
8 papers
Time Series Forecasting Using Fuzzy Cognitive Maps: A Survey
Omid Orang, Petrônio Cândido de Lima e Silva, Frederico Gadelha Guimarães
Among various soft computing approaches for time series forecasting, Fuzzy Cognitive Maps (FCM) have shown remarkable results as a tool to model and analyze the dynamics of complex…
Introducing Randomized High Order Fuzzy Cognitive Maps as Reservoir Computing Models: A Case Study in Solar Energy and Load Forecasting
Omid Orang, Petrônio Cândido de Lima Silva, Frederico Gadelha Guimarães
Fuzzy Cognitive Maps (FCMs) have emerged as an interpretable signed weighted digraph method consisting of nodes (concepts) and weights which represent the dependencies among the co…
Combining Embeddings and Fuzzy Time Series for High-Dimensional Time Series Forecasting in Internet of Energy Applications
Hugo Vinicius Bitencourt, Luiz Augusto Facury de Souza, Matheus Cascalho dos Santos +2
The prediction of residential power usage is essential in assisting a smart grid to manage and preserve energy to ensure efficient use. An accurate energy forecasting at the custom…
High-dimensional Multivariate Time Series Forecasting in IoT Applications using Embedding Non-stationary Fuzzy Time Series
Hugo Vinicius Bitencourt, Frederico Gadelha Guimarães
In Internet of things (IoT), data is continuously recorded from different data sources and devices can suffer faults in their embedded electronics, thus leading to a high-dimension…
The Cone epsilon-Dominance: An Approach for Evolutionary Multiobjective Optimization
Lucas S. Batista, Felipe Campelo, Frederico G. Guimarães +1
We propose the cone epsilon-dominance approach to improve convergence and diversity in multiobjective evolutionary algorithms (MOEAs). A cone-eps-MOEA is presented and compared wit…
Applying Genetic Programming to Improve Interpretability in Machine Learning Models
Leonardo Augusto Ferreira, Frederico Gadelha Guimarães, Rodrigo Silva
Explainable Artificial Intelligence (or xAI) has become an important research topic in the fields of Machine Learning and Deep Learning. In this paper, we propose a Genetic Program…
Forecasting in Non-stationary Environments with Fuzzy Time Series
Petrônio Cândido de Lima e Silva, Carlos Alberto Severiano Junior, Marcos Antonio Alves +3
In this paper we introduce a Non-Stationary Fuzzy Time Series (NSFTS) method with time varying parameters adapted from the distribution of the data. In this approach, we employ Non…
Scalable and Customizable Benchmark Problems for Many-Objective Optimization
Ivan Reinaldo Meneghini, Marcos Antonio Alves, António Gaspar-Cunha +1
Solving many-objective problems (MaOPs) is still a significant challenge in the multi-objective optimization (MOO) field. One way to measure algorithm performance is through the us…