Author

El Farissi Ilhame

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Conference Open access 2026

Evaluating Deep Learning Architectures for Multivariate Time Series Forecasting: Accuracy, Efficiency, and the Learning Efficiency Score

Deep neural network architectures are extensively utilized in the processing of complex multivariate datasets, which may have nonlinear interdependencies, sequential dependencies, and high dimensionalities. Examples of commonly adopted models include MLPs, CNNs, RNNs, LSTMs, GRUs, and Transformer models. Although previ...

Zrouri Amira, El Farissi Ilhame · EPJ Web of Conferences · 0 citations

Review Open access Sep 2026

Optimization of Deep Neural Networks for Multivariate Data: Systematic Review and Critical Analysis of Methods, Hyperparameters, and Performance (2015–2026)

Optimizing deep neural networks for multivariate data remains difficult: features are high-dimensional, correlated, and heterogeneous, and no existing review connects optimization strategy, hyperparameter choice, and data type into a single picture. We address this gap through a Systematic Mapping Study of 107 articles...

Zrouri Amira, El Farissi Ilhame · Artificial Intelligence and... · 0 citations