… determines the node degree using deep learning algorithm and particular hardware. Stampa
et al. [75] used deep reinforcement learning to optimize the routing performance with the …

… , although the intelligent generation method proposed in this paper uses topology optimization
calculations to build the dataset, the topology optimization calculations of this model do …

… In this study, a novel deep learning framework is proposed for landslide susceptibility
assessment using improved deep belief networks (LSCDBN) with intelligent optimization …

… creation of standard work procedures that assure production quantity and efficiency by
using ambient intelligence, optimization heuristics, and ML [48]. Luetkehoff et al. develop a self-…

… In this research, we propose an intelligent decision support … Swarm Optimization (PSO)
models for feature optimization. The … base model trained using each optimized feature subset. A …

… and intelligent optimization based two-stage deep learning … (mRMR), Gray Wolf Optimization
algorithm (GWO) and LSTM. First… Next, a two-stage intelligent optimization prediction model …

… Deep learning (DL) methods have a greater capability to address complex and heterogeneous
machinery signals, and identify faults more accurately. This paper presents a review of …

… This section presented the proposed intelligent deep learning and improved WOA for
object recognition. The main flow of the proposed framework is illustrated in Fig. 1. …

… Optimization (GJO) algorithm, and a hybrid deep learning … ) combined to build a hybrid
deep learning model CNN-LSTM-… The hyperparameters of the CLT are optimized using GJO to …

… We leverage the Caffe framework [44], a plain deep learning framework, to evaluate the
inference performance of models on both, so that can avoid interference of the optimizations …