Muneef Abdulkareem Farea Ahmed

NFGA-LINEAR: An Explainable Neuro-Fuzzy Genetic Framework for Forecasting Anomaly-Affected Data-Scarce Time Series

NFGA-LINEAR is developed, an interpretable Takagi–Sugeno–Kang neurofuzzy framework in which a genetic algorithm jointly determines the number of rules and optimizes Gaussian antecedents and rule-specific linear consequents and confirms that neither its forecasting nor detection performance is uniformly superior across...