Withthe continuous development of computer technology, machine translation methods have also experienced a long research process. In recent years, the research of artificial neural network has brought new solutions t...
详细信息
the proceedings contain 84 papers. the topics discussed include: YONA: an intelligence question-answering system based on artificial intelligence;a hybrid model based on GAT and TAGCN for node classification;SRGCN: so...
ISBN:
(纸本)9798350343113
the proceedings contain 84 papers. the topics discussed include: YONA: an intelligence question-answering system based on artificial intelligence;a hybrid model based on GAT and TAGCN for node classification;SRGCN: social relationship graph convolutional network-based social network user geolocation prediction;dense pedestrian detection method based on improved YOLOv5;opening the black box: interpretable machinelearning reveals the relationship between lexical diversity and writing quality;porting and optimization of electric power consumers anomaly behavior monitoring on ARM platform;short text similarity detection based on graph attention networks and knowledge augmentation;MSFF-Net: a multi-scale feature fusion network for hippocampus segmentation;research on path optimization of automated warehouse based on genetic algorithm;and modeling operational profile for ai systems: a case study on UAV systems.
this paper compares sentiment analysis of Chinese user comment text of mobile applications based on both sentiment dictionary and machinelearning/deep learning methods. the dataset is unique because of the inclusion ...
详细信息
In India, like in the rest of the world, cancer is a major killer. this research objective is to predict cancer mortality in India, using supervised machinelearning methods. Cancer mortality rates in India between 19...
详细信息
the increasing complexity of network traffic resulting from internet-based services and data exchanges presents formidable obstacles to real-time analysis and decision-making in the field of network security. A real-t...
详细信息
the proceedings contain 90 papers. the topics discussed include: severity stratification of brinjal leaf diseases: a federated learning CNNs approach;experimental analysis of malware detection and classification syste...
ISBN:
(纸本)9798350384628
the proceedings contain 90 papers. the topics discussed include: severity stratification of brinjal leaf diseases: a federated learning CNNs approach;experimental analysis of malware detection and classification system using intelligent deep learning methodology;exploring the thematic clusters of artificial intelligence applications in supply chains using topic modelling and text mining: a machinelearning insight;predicting quality of ground water using different deep learning models;BananaLeafNet: federated learning CNNs for multiclass disease identification in banana crops;the detection of adverse drug reactions in clinical text data using transformer models;energy consumption forecasting in buildings based on heating and cooling loads using regression models;towards sustainable ICT: a bibliometric review of green communications;leveraging machinelearning approach for large-scale unstructured satellite image analysis: a comprehensive review and future predictions;and the food preservation using a solar dryer monitoring system.
In order to quickly predict the life indicators of aircraft wires, a modeling and parameter estimation method based on different surrogate models is proposed for aircraft wires. the predicted values are used to predic...
详细信息
We investigate the benefits of using intraday realized volatility (RV) commonality, and propose a novel non-parametric framework for forecasting one-day ahead intraday RV (1D-ahead intraday RV). Specifically, we train...
详细信息
ISBN:
(纸本)9798400702402
We investigate the benefits of using intraday realized volatility (RV) commonality, and propose a novel non-parametric framework for forecasting one-day ahead intraday RV (1D-ahead intraday RV). Specifically, we train multiple models using machinelearning (ML) techniques under various training settings (single-asset, cluster-driven, and cross-asset), where commonality gradually enters model dynamics as training schemes become more complex. We conclude that models that leverage the cryptocurrency commonality outperform models that do not explicitly account for it, regardless of the market regime considered. the source code of this project is available at: ***/edjanga/crypto_volatility_commonality.
the neurological ailment Parkinson's disease affects millions of individuals globally. Contrarily, an early detection of the illness will aid in its efficient treatment. Withmachinelearning, which is still in it...
详细信息
Federated learning can utilize its distributed structure to protect data privacy security of clients and improve efficiency of machinelearning. However, its distributed framework also make itself be susceptible to sy...
详细信息
暂无评论