Results 81 to 90 of about 95,729 (269)

Real Estate Appraisal Performance Improvement by Adapting a Hybrid Model: Geographically Weighted Regression and Extreme Gradient Boosting in Al Bireh, Palestine

International Journal of Technology
Real estate appraisal functions as a decision support system in pivotal financial, economic, and business processes, encompassing buying and selling houses, property tax, bank lending, and insurance companies.
Jamal A.A. Numan, Izham Mohamad Yusoff
doaj   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information. [PDF]

, 2019
The manual brain tumor annotation process is time consuming and resource consuming, therefore, an automated and accurate brain tumor segmentation tool is greatly in demand. In this paper, we introduce a novel method to integrate location information with
Chen, Jefferson W, Jiang, Jiaxiang, Kao, Po-Yu, Khan, Amil, Manjunath, BS, Shailja, Shailja, Zhang, Angela   +6 more
core  

Machine‐Learning‐Guided Design of Incommensurate Antiferroelectrics via Field‐Driven Phase Engineering

Advanced Science, EarlyView.
The key to enhancing the energy storage performance of antiferroelectrics lies in regulating the phase transition and reverse phase transition. A phase‐field‐machine learning framework is employed to predict the energy storage performance of Pb‐based incommensurate antiferroelectrics with multi‐scale regulation strategy, thereby revealing the dynamic ...
Ke Xu, Xiaoming Shi, Zhaochen Xi, Shouzhe Dong, Changqing Guo, Rongzhen Gao, Letao Yang, Jing Wang, Di Zhou, Houbing Huang   +9 more
wiley   +1 more source

Discharge estimation in compound channels with converging and diverging floodplains using an optimised Gradient Boosting Algorithm

Journal of Hydroinformatics
River discharge estimation is vital for effective flood management and infrastructure planning. River systems consist of a main channel and floodplains, collectively forming a compound channel, posing challenges in discharge calculation, particularly ...
Shashank Shekhar Sandilya, Bhabani Shankar Das, Sébastien Proust, Divyanshu Shekhar   +3 more
doaj   +1 more source

Prompt Engineering Accelerates the Data‐Driven Discovery of Photocatalysts via an LLM‐Based Model Ensemble Strategy

Advanced Science, EarlyView.
This work establishes a pipeline that transforms fragmented literature into a structured database for graphitic carbon nitride photocatalyst discovery. A prompt‐engineered, cross‐model large language model ensemble automates high‐fidelity extraction, enabling interpretable machine learning to identify dominant performance descriptors. These data‐driven
Dianyuan Li, Xichen Sun, Shaohua Sun, Runzhou Wang, Miaomiao Zhang, Meng Xiao, Yue Wang, Yuezhou Zhang   +7 more
wiley   +1 more source

GWO-XGBoost prediction algorithm for industrial wastewater quality key data

Gongye shui chuli
In order to solve the complex adjustment of XGBoost model parameters and further improve the accuracy of water quality data prediction，a predictin algorithm based on Gray Wolf Optimization（GWO） to optimize XGBoost.
NIU Jinghui
doaj   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

Assessment of seasonal variations in the air quality index (2019–2022) in Al-Jahra city, Kuwait

Kuwait Journal of Science
The daily air quality indices (AQIs) for pollutants, including particulate matter (PM10 and PM2.5), carbon monoxide (CO), nitrogen oxides (NO2), ozone (O3), and sulfur dioxide (SO2), were evaluated for the period of 2019–2022 in Al-Jahra City, Kuwait ...
Alsowaidan S., Al-Hurban A., Alsaber A.
doaj   +1 more source

Machine Learning for Designing Perovskites and Perovskite‐Inspired Solar Materials: Emerging Opportunities and Challenges

Advanced Science, EarlyView.
This review offers a comprehensive comparison between perovskites and perovskite‐inspired materials (PIMs), focusing on their crystal structures, electronic properties, and chemical compositions. It evaluates the applicability of machine learning (ML) descriptors and models across both material classes.
Yangfan Zhang, Yiming Xia, Ali Shakiba, Hongrui Zhang, Xiaojing Hao, Priyank V. Kumar, Mahesh P. Suryawanshi   +6 more
wiley   +1 more source