In addition, with intelligent algorithm, the boundary values of operating parameters are determined. The genetic algorithm (GA) and particle swarm optimization (PSO) are combined into a GA-PSO hybrid algorithm. Subsequently, the hybrid algorithm is integrated with the machine learning model to ...
Moreover, we extend the PCA-based hybrid precoding to DS, where a shared agglomerative hierarchical clustering (AHC) algorithm developed from machine learning is proposed to group the DS for improved spectral efficiency (SE). Finally, we investigate the energy efficiency (EE) of the proposed ...
algorithm, we used the Extra Trees Regressor in the scikit-learn Python programming package40. Table2indicates the corresponding parameter setting. The number of trees was set to 1,000 because of the performance limit of the machine server we used. The maximum depth of the tree, the minimum ...
In this study, we present an approach that combines machine learning (ML) and mechanistic modeling (MM) to improve the performance of constraint-based modeling (CBM) on genome-scale metabolic models (GEMs). Our hybrid MM-ML models are applied to common tasks in systems biology and metabolic e...
[6] S. L. Gay, “The fast affine projection algorithm,” in Acoustic signal processing for telecommunication, pp. 23–45. Springer, 2000. [7] A. Mader, H. Puder, and G. U. Schmidt, “Step-size control for acoustic echo cancellation filters–an overview,” Signal Processing, vol. 80...
The k learning algorithms with the highest evaluation value are included in the pruned ensemble, whereas the other algorithms are eliminated. In clustering based pruning methods, a clustering algorithm (such as k-means) is utilized to group the classification algorithms within the ensemble into ...
(HML) algorithm utilized a similar method; However, it firstly has a reduced-order (but fast enough) numerical submodel that can give a rough estimate of the results, and secondly a machine learning submodel within this hybrid implementation improves the accuracy of the low-fidelity results to...
Intelligent scheduling controller for shop floor control systems: a hybrid genetic algorithm/decision tree learning approach This work develops an intelligent scheduling controller (ISC) to support a shop floor control system (SFCS) to make real-time decisions, robust to various ... CT Su,YR Shiue...
features from raw data that align with a machine learning algorithm. DL methods, such as CNNs and Long Short-Term Memory Neural Networks (LSTMs), have demonstrated their effectiveness by automatically learning relevant features from raw sensory input, thereby achieving state-of-the-art performance...
Machine learning-based approaches have shown promise in detecting botnets by analyzing network traffic patterns8,9. However, a single machine-learning algorithm may not be sufficient to detect all types of botnets effectively10. The quality of a single model can also decrease over time due to the...