Results 141 to 150 of about 9,482,218 (334)

Estimation of the Groundwater Level by using Combined Geostatistics with Artificial Neural Networks (Case Study: Shahrekord Plain) [PDF]

علوم و مهندسی آبیاری, 2013
One of the most basical issues in groundwater resources management is the estimation of water table from observation well network data. The purpose of this study is estimate the groundwater level using the combination algorithm of the geostatistics and ...
Reza Zamaniahmadmahmoodi, Alimohamad Akhondali, Hossein Samadiborojeni, Heydar Zareei   +3 more
doaj  

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley   +1 more source

Cellular Material Network: A General Machine Learning Architecture for Predicting Mechanical Properties of Cellular Materials

Advanced Intelligent Systems, EarlyView.
This study introduces Cellular Material Network (CM‐Net), a pioneering machine learning architecture integrating physical information, to predict the mechanical properties of cellular materials. Comprehensive validation through simulations and experiments demonstrates its accuracy in predicting nonlinear behaviors, including initial peak compression ...
Sicong Zhou, Qiang Gao, Liuchao Jin, Guoquan Xie, Kang Zhang, Wei‐Hsin Liao   +5 more
wiley   +1 more source

A deep learning convolutional neural network and multi-layer perceptron hybrid fusion model for predicting the mechanical properties of carbon fiber

Materials & Design, 2023
Meng-Ze Li, Shuran Li, Yu Tian, Y. Fu, Y. Pei, Wei-Dong Zhu, Ying-Lin Ke   +6 more
semanticscholar   +1 more source

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

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

Modeling of Continuous Stirred Tank Reactor based on Artificial Neural Network

مجلة النهرين للعلوم الهندسية, 2017
This paper presents the dynamic model identification algorithm of the continuous stirred tank reactor (CSTR) using a multi-layer perceptron (MLP) neural network topology.
Ahmed Sabah Al-Araji
doaj