Results 231 to 240 of about 8,140,064 (302)

Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering. [PDF]

Sci Rep
Wang S.
europepmc   +1 more source

Conditionally Significant eQTL and TWAS Analyses Identify MsRD26 as a Major Candidate Positive Regulator of Salt Tolerance in Medicago sativa L

Advanced Science, EarlyView.
Salt stress significantly impacts plant growth. Through population transcriptome, eQTL and TWAS analyses, we identified several candidate genes potentially associated with salt stress response. Functional assays suggested that some of these genes may contribute to salt tolerance.
Lin Chen, Yuqi Zhang, Xinyue Ma, Jinpeng Bi, Fei He, Li Zhao, Haiyue Lei, Zhengqin Xiao, Xue Wang, Tiejun Zhang, Ruicai Long, Junmei Kang, Qingchuan Yang   +12 more
wiley   +1 more source

Enhanced extreme learning machine via competitive learning SSA (CL-SSA) for load capacity factor prediction. [PDF]

Heliyon
Tahir S Luoka N, Khalifa WMS.
europepmc   +1 more source

Fusing Direct and Indirect Measurements Through Multi‐Fidelity Learning For Accelerated Electrocaloric Materials Discovery

Advanced Science, EarlyView.
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang, Pengfei Dang, Yuan Tian, Zhengwang He, Wei Gu, Lixue Zhang, Turab Lookman, Yumei Zhou, Dezhen Xue   +8 more
wiley   +1 more source

Intelligent identification and warning method of disc cutter abnormal wear in TBM construction based on extreme learning machine. [PDF]

Sci Rep
Li Q, Du L, Yang Y, Ni Z, Zhao X.
europepmc   +1 more source

Deep Learning‐Driven Discovery and Engineering of an Efficient PETase for Depolymerization and Detoxification of PET Microplastics Under Physiological Conditions

Advanced Science, EarlyView.
A deep learning–driven pipeline mining 246 million protein sequences uncovers AhPETase, an evolutionarily distinct PET hydrolase. Engineered variant AhPETaseM1 degrades post‐consumer PET microplastics under physiological conditions and reverses microplasticinduced cytotoxicity in human lung and colon cells, establishing enzymatic microplastic ...
Yuxuan Wang, Shijie He, Yuheng Chang, Sheng Mao, Jianan Canal Li, Binbin Chen, Hongxun Gao, Mingchun Xu, Chenxu Liu, Yajie Wang   +9 more
wiley   +1 more source

Development of a novel modeling framework based on weighted kernel extreme learning machine and ridge regression for streamflow forecasting. [PDF]

Sci Rep
Samadi-Koucheksaraee A, Chu X.
europepmc   +1 more source

Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes

Advanced Science, EarlyView.
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley   +1 more source

Integrated metaheuristic algorithms with extreme learning machine models for river streamflow prediction. [PDF]

Sci Rep
Van Thieu N, Nguyen NH, Nguyen NH, Sherif M, El-Shafie A, Ahmed AN.   +5 more
europepmc   +1 more source

Optimal extreme learning machine for diagnosing brain tumor based on modified sailfish optimizer. [PDF]

Heliyon
Ali Amin S, Alqudah MKS, Ateeq Almutairi S, Almajed R, Rustom Al Nasar M, Ali Alkhazaleh H.   +5 more
europepmc   +1 more source