Results 31 to 40 of about 7,680 (217)

Forecasting the Financial Efficiency of Russian Cinema Using a Multifactor Ensemble Machine Learning Model Trained on Historical Data

Финансы: теория и практика
The object of the study is data on the distribution of Russian cinema films from July 2022 to September 2023. Specifically, it analyzes 185 films that were released during this period.
A. V. Dozhdikov
doaj   +1 more source

Advancing the Design of High‐Efficiency Printable Hole‐Conductor‐Free Mesoscopic Perovskite Solar Cells Through Machine Learning

Advanced Science, EarlyView.
Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng, Jingzi Zhang, Xu Zhu, Yuelin Wang, Antai Yang, Kailong Hu, Chengquan Zhong, Jiakai Liu, Menghan Dun, Xi Lin   +9 more
wiley   +1 more source

Enhancing Hate Speech and Offensive Language Detection using CatBoost with RoBERTa-based Contextual Embeddings

Sistemasi: Jurnal Sistem Informasi
The widespread dissemination of hate speech and offensive content on social media platforms has become a critical societal issue, highlighting the need for reliable automated detection systems.
Muhammad Elfarizi, Surya Agustian, Fitra Kurnia, Suwanto Sanjaya, Fitri Insani   +4 more
doaj   +1 more source

Machine‐Learning Framework for Designing Stable Interfaces in All‐Solid‐State Lithium‐Ion Batteries

Advanced Science, EarlyView.
A data‐driven strategy is developed to discover coating materials for all‐solid‐state lithium batteries. Using calculations of interfacial reactivity, unsupervised pattern recognition, and machine‐learning prediction, the study identifies low‐reactivity compositional patterns and screens new lithium‐based oxide and polyanion candidates, extending ...
Sehyeok Park, Myeongcho Jang, Hun‐Gi Jung, Kyung Yoon Chung, Seungho Yu   +4 more
wiley   +1 more source

Automatic identification of forest species using machine learning methods based on satellite image processing [PDF]

Известия Саратовского университета. Новая серия: Серия Науки о Земле
Monitoring of the condition and species diversity of tree species plays a significant role in the forest resource management. The emergence of high-quality multispectral satellite images opens up opportunities for using information about vegetation in a ...
Ogneva, Marina V., Shlapak, Pavel Aleksandrovich, Vasilyev, Alexander A., Moiseev, Denis S.   +3 more
doaj   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Feature selection and load identification method for air conditioning load recognition based on mutual information and Catboost

Diance yu yibiao
Air conditioning load identification is an important basis for the participation of massive air conditioning loads on the user side in demand response regulation.
YI Shuhui, LIU Junjie, FANG Tian, HUANG Yingqi, WEN He   +4 more
doaj   +1 more source

Analytical Determination of Interwell Connectivity Based on Interwell Influence

Tsinghua Science and Technology, 2021
Interwell connectivity, an important element in reservoir characterization, especially for water flooding, is used to make decisions for better oil production.
Jiangru Yuan, Xingjie Zeng, Haiyun Wu, Weishan Zhang, Jiehan Zhou, Bingyang Chen   +5 more
doaj   +1 more source

Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults

Annals of Gastroenterological Surgery, EarlyView.
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males, Marko Kumric, Zvonimir Boban, Josip Vrdoljak, Dario Pecenkovic, Matej Ivanda, Marko Grahovac, Zenon Pogorelic, Josko Bozic   +8 more
wiley   +1 more source

Islanding detection method for microgrids based on CatBoost

Frontiers in Energy Research, 2023
The occurrence of unintentional islanding will seriously threaten the stable operation of a microgrid (MG). Therefore, detecting the islanding of an microgrid timely is an important premise to ensure the microgrid operates safely and stably. However, the problem of dead zone exists in the traditional islanding detection process because the threshold of
Ran Chen, Li Zhou, Chuanyu Xiong, Hanping Xu, Zhaoyang Zhang, Xuhui He, Xuhui He, Qingguo Dong, Qingguo Dong, Can Wang, Can Wang   +10 more
openaire   +2 more sources