过去一年中添加的文章，按日期排序
[HTML][HTML] An analysis on classification models for customer churn prediction
KC Mouli, CV Raghavendran, VY Bharadwaj… - Cogent …, 2024 - Taylor & Francis
2 天前 - … Cyber defense in the age of artificial intelligence and machine learning for financial
fraud detection application. International Journal of Electrical and Electronics Research, 10(…
fraud detection application. International Journal of Electrical and Electronics Research, 10(…
[HTML][HTML] Development of a machine learning algorithm to predict the residual cognitive reserve index
BE Gavett, S Tomaszewski Farias… - … Communications, 2024 - academic.oup.com
2 天前 - … To address these limitations, this study sought to determine whether a machine
learning approach to combining standard clinical variables could (1) predict a residual-based …
learning approach to combining standard clinical variables could (1) predict a residual-based …
Diabetic Prediction based on Machine Learning Using PIMA Indian Dataset
MS Salih - Communications on Applied Nonlinear Analysis, 2024 - internationalpubls.com
2 天前 - … of data pre-processing are conducted on the Pima Diabetes dataset. The proposed
approach … Regarding the feature aspect, we used a method called principal component …
approach … Regarding the feature aspect, we used a method called principal component …
An Improved Information Retrieval System using Hybrid RNN LSTM for Multiple Search Engines
B Sangamithra - Communications on Applied Nonlinear …, 2024 - internationalpubls.com
2 天前 - … learning techniques for this … machine learning techniques such artificial neural
networks (ANNs). Improved results have been seen specifically using deep-learning techniques …
networks (ANNs). Improved results have been seen specifically using deep-learning techniques …
A Study on Customer Segmentation for Banking Sector Through Cluster Analysis: Ethical Implications
LK Kumar - Communications on Applied Nonlinear Analysis, 2024 - internationalpubls.com
2 天前 - … data. To ensure the accuracy and robustness of our segmentation methodology,
sophisticated machine learning techniques like the Elbow and Silhouette methods are …
sophisticated machine learning techniques like the Elbow and Silhouette methods are …
Enhancing IoT-Enabled Wireless Sensor Network Performance through Adaptive Congestion Control: Investigation of Hybrid Aggregation and Scheduling Techniques
SH Sutar - Communications on Applied Nonlinear Analysis, 2024 - internationalpubls.com
2 天前 - … , the effective management of data transmission and congestion control within …
data priority, network traffic, and energy constraints. Furthermore, machine learning techniques, …
data priority, network traffic, and energy constraints. Furthermore, machine learning techniques, …
ForestEyes: Citizen Scientists and Machine Learning-Assisting Rainforest Conservation
ÁL Fazenda, FA Faria - Communications of the ACM - dl.acm.org
2 天前 - … used as training data for machine learning techniques.Finally, different techniques
are … This methodology based on CS and ML techniques introduces a novel computational …
are … This methodology based on CS and ML techniques introduces a novel computational …
Deep learning based adaptive Ryu controller model for quality of experience issues in multimedia streaming for software defined vehicular networks
VP Sarvade, SA Kulkarni - Applied Intelligence, 2024 - Springer
2 天前 - … resilience by varying transmission rate and packet size. Our … by combining the
SDVN with machine learning algorithms to … further enhances the QoS/QoE of data transmission. …
SDVN with machine learning algorithms to … further enhances the QoS/QoE of data transmission. …
Federated Learning Survey: A Multi-Level Taxonomy of Aggregation Techniques, Experimental Insights, and Future Frontiers
2 天前 - … The emerging integration of IoT (Internet of Things) and AI (Artificial Intelligence)
has … local raw data, ensuring data privacy, network scalability, and minimal data transfer. One …
has … local raw data, ensuring data privacy, network scalability, and minimal data transfer. One …
Open Access Data and Deep Learning for Cardiac Device Identification on Standard DICOM and Smartphone-based Chest Radiographs
2 天前 - … Artificial intelligence (AI) algorithms, particularly convolutional neural networks (CNNs), …
, compatible with both Digital Imaging and Communications in Medicine (DICOM) and …
, compatible with both Digital Imaging and Communications in Medicine (DICOM) and …