The bearing health in the traction motor is the prerequisite and guarantee for the safe
operation of high-speed trains. The vibration signals of the bearing in traction motor feature …

This paper solves the flow-shop scheduling problem (FSP) through the reinforcement
learning (RL), which approximates the value function with neural network (NN). Under the …

Sentiment analysis is an ongoing research field within the discipline of data mining. The
majority of academics employ deep learning models for sentiment analysis due to their …

The drive for smarter, greener, and more livable cities has led to research towards more
effective solar energy forecasting techniques and their integration into traditional power …

This paper uses the database as the data source, using bibliometrics and visual analysis
methods, to statistically analyze the relevant documents published in the field of text …

Hyperparameters and architecture greatly influence the performance of convolutional neural
networks (CNNs); therefore, their optimization is important to obtain the desired results. One …

The performance of a machine learning algorithm is highly dependent on its
hyperparameters. However, hyperparameter optimization is not a trivial task as it is problem …

This paper proposed a method for improving the XLNet model to address the shortcomings
of segmentation algorithm for processing Chinese language, such as long sub-word lengths …

One of the most time-consuming parts of an attorney's job is finding similar legal cases.
Categorization of legal documents by their subject matter can significantly increase the …

The primary aim of this study was to experiment and compare the empirical evidence of
evolutionary algorithms and their applications using the Genetic Algorithm (GA) and Particle …