Intrusion detection method based on Bayesian and decision tree
Gong-kuang zidonghua, 2013 In view of problems of low detection rate and high false detection rate in intrusion detection method based on Bayesian or decision tree, the paper proposed an intrusion detection method based on Bayesian and decision tree. Firstly, Naive Bayesian method
CHI Jing, YANG Zhen-yu, ZHANG Ting
doaj
Bayesian method application: Integrating mathematical modeling into clinical pharmacy through vancomycin therapeutic monitoring. [PDF]
Pharmacol Res Perspect, 2022 Chen A, Gupta A, Do DH, Nazer LH.
europepmc +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
A Bayesian method for identifying associations between response variables and bacterial community composition. [PDF]
PLoS Comput Biol, 2022 Verster A +4 more
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Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers
Advanced Science, EarlyView.FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao +9 more
wiley +1 more source
An Efficient Bayesian Method for Estimating the Degree of the Skewness of X Chromosome Inactivation Based on the Mixture of General Pedigrees and Unrelated Females. [PDF]
Biomolecules, 2023 Kong YF +6 more
europepmc +1 more source
Sustainable Materials Design With Multi‐Modal Artificial Intelligence
Advanced Science, EarlyView.Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu +8 more
wiley +1 more source
A calibrated Bayesian method for the stratified proportional hazards model with missing covariates. [PDF]
Lifetime Data Anal, 2022 Kim S, Kim JK, Ahn KW.
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Advanced Science, EarlyView.By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
Bayesian and Non-Bayesian Approaches to Scientific Modeling and Inference in Economics and Econometrics [PDF]
After brief remarks on the history of modeling and inference techniques in economics and econometrics , attention is focused on the emergence of economic science in the 20th century. First, the broad objectives of science and the Pearson-Jeffreys' "unity
Arnold Zellner
core