Combining traditional and spiking neural networks for energy-efficient detection of Eimeria parasites
Analysis of the Performance of a Semantic Interpretability-Based Tuning and Rule Selection of Fuzzy Rule-Based Systems by Means of a Multi-Objective Evolutionary Algorithm
A Multi-objective Evolutionary Algorithm for Tuning Fuzzy Rule-Based Systems with Measures for Preserving Interpretability
Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary Algorithm
A genetic-programming-based approach for the learning of compact fuzzy rule-based classification systems
Comparison and design of interpretable linguistic vs. scatter FRBSs: GM3M generalization and new rule meaning index for global assessment and local pseudo-linguistic representation
