Hybrid DeepXAI Fusion Network for Interpretable Big Data Analytics and Secure Cloud Decision-Making Systems

Big data analytics supports modern intelligent systems, but model complexity and limited transparency can undermine interpretability, trust, and security in decision-making. This paper presents the Hybrid DeepXAI Fusion Network, a deep learning framework that integrates temporal, relational, and contextual features with explainable artificial intelligence (XAI) mechanisms. The architecture combines one-dimensional convolutional neural networks (1D-CNNs) for temporal feature extraction, Transformer encoders for contextual modeling, and graph neural networks (GNNs) for inter-feature dependency a

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