Results 61 to 70 of about 5,416,756 (285)

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Supervised Score-Based Modeling by Gradient Boosting

Score-based generative models can effectively learn the distribution of data by estimating the gradient of the distribution. Due to the multi-step denoising characteristic, researchers have recently considered combining score-based generative models with
Zhao, Changyuan, Du, Hongyang, Liu, Guangyuan, Niyato, Dusit   +3 more
core   +2 more sources

Gradient boosting [PDF]

, 2021
Tässä tutkielmassa käsitellään Gradient boosting algoritmia. Algoritmi käsittelee ohjatun oppimisen menetelmin läpi dataa ja pyrkii tekemään tämän avulla luotettavia ennusteita.
Polviander, Oona
core  

Radiative Thermal Management for Extreme Environments: Mechanisms and Design Strategies

Advanced Materials, EarlyView.
In this review, we discuss the fundamental mechanisms of radiative cooling and solar heating, material and structural design strategies, hybrid approaches integrating additional heat transfer pathways, and durability‐oriented designs addressing environmental stresses.
Hyung Rae Kim, Haeseong Kim, Joo Hwan Ko, Gil Ju Lee, Dae‐Hyeong Kim, Young Min Song   +5 more
wiley   +1 more source

Experimental assessment with data-driven machine learning-based prediction of compressive strength of waste natural fiber-reinforced sustainable concrete

Scientific Reports
This study presents a hybrid approach combining experimental evaluation and machine learning modeling for the compressive strength (CS) estimation of natural fiber-reinforced concrete (NFRC), which utilizes jute, coir, and bamboo fibers. A dataset of 444
Prince Paul, Md. Kawsarul Islam Kabbo, Rajarshi Das Gupta, Md. Habibur Rahman Sobuz, Prosanjit Baral, Mohammed Jameel, Sani Aliyu Abubakar   +6 more
doaj   +1 more source

Data-driven natural frequency tuning in cantilever structures through strategic perforation patterns

Applications in Engineering Science
The objective of this study is to investigate the dynamic behavior of a cantilever rectangular beam by tuning its natural frequency through a novel perforation technique.
Amir Hossein Rabiee, Parsa Shafiei, Alireza Farhadi   +2 more
doaj   +1 more source

ada: An R Package for Stochastic Boosting [PDF]

Boosting is an iterative algorithm that combines simple classification rules with "mediocre" performance in terms of misclassification error rate to produce a highly accurate classification rule. Stochastic gradient boosting provides an enhancement which
George Michailides, Kjell Johnson, Mark Culp   +2 more
core  

Phase‐Engineered MoS2 Quantum Monolayer Catalysts

Advanced Materials, EarlyView.
A new type of catalyst model—phase‐engineered MoS2 quantum‐monolayer catalyst (∼0.8 nm thick, < 6 nm in the lateral size; switchable freely among metallic 1T, semiconducting 2H, and a hybrid phase of metallic‐semiconducting 1T‐2H)—is reported. It can efficiently and stably drive photochemical H2, syngas and ammonia synthesis as a catalyst or co ...
Ruijie Yang, Yingying Fan, Lillian Pernitsky, Mojtaba Ebrahimian Mashhadi, Ningxin Chen, Md. Mehadi Hassan, Zheng Li, Heng Zhao, Liang Mei, Zhiyuan Zeng, Zhangxing Chen, Jinguang Hu, Qingye Lu   +12 more
wiley   +1 more source

Hedonic price models and indices based on boosting applied to the Dutch housing market [PDF]

We create a hedonic price model for house prices for six geographical submarkets in the Netherlands. Our model is based on a recent data mining technique called boosting.
Kagie, M., Wezel, M.C. van
core