Results 61 to 70 of about 36,988 (280)

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Pest and Disease Prediction and Management for Sugarcane Using a Hybrid Autoregressive Integrated Moving Average—A Long Short-Term Memory Model

Agriculture
This study introduces a hybrid AutoRegressive Integrated Moving Average (ARIMA)—Long Short-Term Memory (LSTM) model for predicting and managing sugarcane pests and diseases, leveraging big data for enhanced accuracy.
Minghui Wang, Tong Li
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

Correspondence On the Selection of Error Measures for Comparisons Among Forecasting Methods [PDF]

Clements and Hendry (1993) proposed the Generalized Forecast Error Second Moment (GFESM) as an improvement to the Mean Square Error in comparing forecasting performance across data series.
JS Armstrong, Robert Fildes
core  

PENGGUNAAN MEAN SQUARE ERROR (MSE) DALAM MENENTUKAN PENDUGA RASIO YANG EFISIEN PADA SAMPLING ACAK BERSTRATA [PDF]

, 2010
Penelitian ini akan membahas tentang penduga rasio yang effisien pada sampling acak berstrata. Dari beberapa penduga rasio pada sampling acak berstrata, penulis mengambil tiga penduga rasio yaitu penduga rasio gabungan, penduga rasio yang diajukan oleh ...
Yetti Murni
core  

Transferable Deep Reinforcement Learning With Edge‐Contour‐Depth Fusion for Autonomous Wireless Capsule Endoscopy Navigation

Advanced Science, EarlyView.
This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu, Haitao Gao, Qingyang Liu, Sishen Yuan, Haiyang Fang, Mingwu Su, Baijia Liang, Yongzun Yang, Long Bai, Wenzhen Dong, Dihong Xie, Shijian Su, Jiewen Lai, Shing Shin Cheng, Zhen Li, Xiuli Zuo, Hongliang Ren   +16 more
wiley   +1 more source

A Prediction System of Dengue Fever Using Monte Carlo Method

Emitter: International Journal of Engineering Technology, 2016
Dengue fever is an acute disease that clinically can cause death because there is no prediction system to estimate dengue fever cases so it resulted in the growing of dengue fever cases every year.
Mochammad Choirur Roziqin, Achmad Basuki, Tri Harsono   +2 more
doaj   +3 more sources

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source

Mean Squared Error (MSE) dan Penggunaannya

Jurnal Pemanfaatan Teknologi untuk Masyarakat: Jurnal Pengabdian Masyarakat
Mean Squared Error (MSE) adalah metrik evaluasi yang umum digunakan dalam statistik dan machine learning untuk mengukur seberapa akurat sebuah model regresi dalam memprediksi nilai numerik. MSE menghitung selisih antara nilai prediksi model dan nilai sebenarnya dari data, kemudian mengkuadratkan selisih tersebut agar tidak ada selisih yang bernilai ...
openaire   +1 more source

PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes

Advanced Science, EarlyView.
A plant genomic foundation model pre‐trained on 12 species enables both accurate gene prediction and de novo gene design. Through AI‐human knowledge screening, seven designed sequences showed transcriptional activity in plants, with two expressing stable proteins—demonstrating the first DNA‐RNA‐protein expression of LLM‐generated genes in plants and ...
Changhao Li, Qizhe Zhang, Hanchen Chen, Kepeng Lin, Chengfang Luo, Mengying Yang, Wei Xu, Fan Yao, Jianbing Yan, Qing‐Yong Yang, Xuehai Hu   +10 more
wiley   +1 more source