Advances in Soft Computing

.- Intelligent Systems.
.- Speeding up the Multi-Objective NAS Through Incremental Learning.
.- Tax Underreporting Detection using an Unsupervised Learning Approach.
.- Unsupervised anomaly detection algorithms unveil relevant temporal and spatial patterns in the SARS COV2 codon usage in M´exico.
.- Spatial intelligent estimation of energy consumption.
.- Exploring Classificational Cellular Automaton Hyper-heuristics for Solving the Knapsack Problem.
.- Enhancing Reptile Search Algorithm Performance for the Knapsack Problem with Integration of Chaotic Map.
.- Optimal Fuzzy-Genetic Self-Tuning for Tracking Photovoltaic Peak Power.
.- Novel Approaches to the Minimum Identifying Code Problem Using Enhanced Genetic Algorithms.
.- Bioinformatics and Medical Applications.
.- Emotion recognition Method based on EEG Signal Processing, Simplified Inception Network and Discrete Model.
.- Enhancing User Authentication Through EEG based P300 Speller Response.
.- Detecting Alzheimer's Disease through the Use of Language Impairment Features.
.- From EEG Signal Acquisition and Classification to Mobile Integration: A Comprehensive Framework.
.- Leveraging Pre-trained Models for Robust Federated Learning for Kidney Stone Type Recognition.
.- Natural Language Processing.
.- Automatic Text Summarization based on Transportation Network and Word Mover's Distances embeddings: a toy experiment.
.- Identification of Fake Users in Mobile Communication Using Sentiment Analysis Techniques.
.- RESTful API for intent recognition based on RASA.
.- Predicting the 2024 Mexican Presidential Election with Social Media.
.- Multilevel Analyses of Russian Texts with RuLingva: a case study.
.- Attention + LSTM Aspect-based Sentiment Analysis for multi-label classification.