Results 141 to 150 of about 4,805,610 (298)

Exploiting Edge Semantics in Job Shop Scheduling Problem With Heterogeneous Graph Transformers

Advanced Intelligent Systems, EarlyView.
A heterogeneous graph transformer (HGT) is introduced for reinforcement learning‐based job shop scheduling by explicitly distinguishing precedence and machine‐contention relations through edge‐type‐specific attention. The proposed framework learns richer scheduling representations, improves decision quality over homogeneous graph models, and highlights
Bulent Soykan, Fatih Kasimoglu
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks

BMC Bioinformatics
Background Long non-coding RNAs (lncRNAs) can prevent, diagnose, and treat a variety of complex human diseases, and it is crucial to establish a method to efficiently predict lncRNA-disease associations.
Bing Zhang, Haoyu Wang, Chao Ma, Hai Huang, Zhou Fang, Jiaxing Qu   +5 more
doaj   +1 more source

Advancing single-cell RNA-seq data analysis through the fusion of multi-layer perceptron and graph neural network. [PDF]

Brief Bioinform, 2023
Feng X, Xiu YH, Long HX, Wang ZT, Bilal A, Yang LM.   +5 more
europepmc   +1 more source

Resilient Multimodal Fusion for Robust Vulnerability Exploitability Prediction Under Data Degradation

Advanced Intelligent Systems, EarlyView.
Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati, Seyedeh Leili Mirtaheri, Reza Shahbazian, Andrea Pugliese   +3 more
wiley   +1 more source

Research on Diaphragm Pump Fault Diagnosis Method Based on Res‐DCB‐Net

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Nonstationary pressure pulsation signals of diaphragm pumps contain strong background noise and coupled characteristics. This makes it challenging to extract incipient fault features and to decouple faults with similar physical mechanisms. To address these limitations, this paper proposes a spatiotemporal fault diagnosis model named Res‐DCB ...
Jiahui Wang, Kaili Zhang, Yongxing Song, Zhaoxin Ma, Sitong Guan, Rongwang Chai, Kexiang Ceng, Jingting Liu   +7 more
wiley   +1 more source

Immune subtype identification and multi-layer perceptron classifier construction for breast cancer. [PDF]

Front Oncol, 2022
Yang X, Zheng Y, Xing X, Sui X, Jia W, Pan H.   +5 more
europepmc   +1 more source

Integrating machine learning, deep learning, and image analysis for seed species classification

Applications in Plant Sciences, EarlyView.
Abstract Premise The growing demand for wildflower seeds in ecological restoration requires reliable species identification, yet current market products often contain heterogeneous species. As seed identification is labor‐intensive and requires advanced botanical knowledge, we evaluated multiple segmentation and classification approaches to determine ...
Jonathan Ashworth, Eloise Barrett, Rebonto Haque, Ben Wildey, Anthony Hall, Felix Shaw, Jose J. De Vega   +6 more
wiley   +1 more source

Multi-Layer Perceptron Classifier with the Proposed Combined Feature Vector of 3D CNN Features and Lung Radiomics Features for COPD Stage Classification. [PDF]

J Healthc Eng, 2023
Yang Y, Zeng N, Chen Z, Li W, Guo Y, Wang S, Duan W, Liu Y, Chen R, Kang Y.   +9 more
europepmc   +1 more source

Artificial Intelligence–Driven and Digital Practices for Circular Business and Finance: Insights for Advancing Hubs for Circularity

Business Strategy and the Environment, EarlyView.
ABSTRACT The emerging concept of Hubs for Circularity (H4Cs) presents an opportunity to create collaborative, self‐sustaining regional industrial ecosystems that drive circular economy transitions at scale. However, the operationalisation of H4Cs faces financial, organisational and data‐driven challenges.
Aditya Tripathi, Marcos R. Machado, Laura Spierdijk, Devrim Murat Yazan   +3 more
wiley   +1 more source