AIMC Topic: Models, Theoretical

Clear Filters Showing 121 to 130 of 1953 articles

Construction of VAE-GRU-XGBoost intrusion detection model for network security.

PloS one
With the advent of the big data era, the threat of network security is becoming increasingly severe. In order to cope with complex network attacks and ensure network security, a network intrusion detection model is constructed relying on deep learnin...

Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism.

PloS one
Improving translation quality and efficiency is one of the key challenges in the field of Natural Language Processing (NLP). This study proposes an enhanced model based on Bidirectional Encoder Representations from Transformers (BERT), combined with ...

Data-driven prediction of daily Cryptosporidium river concentrations for water resource management: Use of catchment-averaged vs spatially distributed features in a Bagging-XGBoost model.

The Science of the total environment
Cryptosporidium is a waterborne pathogen which poses a major challenge to water utilities because of its resistance to chlorination and its infectivity at very low concentrations. The ability to make predictions of Cryptosporidium concentrations in r...

Large Language Model Architectures in Health Care: Scoping Review of Research Perspectives.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs) can support health care professionals in their daily work, for example, when writing and filing reports or communicating diagnoses. With the rise of LLMs, current research investigates how LLMs could be applie...

Research on the potential of the deep learning-based "decomposition-optimization-reconstruction" method in runoff prediction for typical climate- and human-regulated basins in northern China.

Journal of contaminant hydrology
River runoff may be affected mainly by the natural climate or human activities, and runoff series present complex characteristics, such as non-stationarity, which makes accurate prediction of runoff challenging. To address the problem that the predic...

Heat loss evaluation for heating building envelope based on relevance vector machine.

PloS one
Due to the influence of many factors, there is no reasonable evaluation method for the heat loss evaluation of the envelope, which leads to the deviation of the evaluation results of building energy consumption. By comparing different regression anal...

Circular saw blade wear status prediction based on generative adversarial network and CNN-LSTM model.

PloS one
Monitoring the status of circular saw blades is an effective measure to ensure the production efficiency and safety of spent fuel assembly cutting. However, the prediction of wear during the cutting of stainless steel shells of spent fuel assemblies ...

A model of mobile robots in networks with resolvability properties.

PloS one
A model for mobility of robots keeping the property of uniquely recognizing the vertices of a given network is considered in this work. This is made in order to detect failures or intruders, by means of dynamic vectors of distances to the set of mobi...

Forecasting monthly residential natural gas demand in two cities of Turkey using just-in-time-learning modeling.

PloS one
Natural gas (NG) is relatively a clean source of energy, particularly compared to fossil fuels, and worldwide consumption of NG has been increasing almost linearly in the last two decades. A similar trend can also be seen in Turkey, while another sim...

Enhanced pedestrian trajectory prediction via overlapping field-of-view domains and integrated Kolmogorov-Arnold networks.

PloS one
Accurate pedestrian trajectory prediction is crucial for applications such as autonomous driving and crowd surveillance. This paper proposes the OV-SKTGCNN model, an enhancement to the Social-STGCNN model, aimed at addressing its low prediction accur...