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| Machine learning for renewable energy materials Gu, Geun Ho; Noh, Juhwan; Kim, Inkyung; Jung, Yousung, JOURNAL OF MATERIALS CHEMISTRY A, v.7, no.29, pp.17096 - 17117, 2019-08 |
| Machine learning identification of symmetrized base states of Rydberg atoms Chong, Daryl Ryan; Kim, Minhyuk; Ahn, Jaewook; Jeong, Heejeong, FRONTIERS OF PHYSICS, v.17, no.1, 2022-02 |
| Machine learning modeling to forecast uncertainty between capital sudden stop and boom Park, sangjin; Yang, Jae-Suk, EXPERT SYSTEMS WITH APPLICATIONS, v.237, 2024-03 |
| Machine learning models based on bubble analysis for Bitcoin market crash prediction Park, sangjin; Yang, Jae-Suk, ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, v.135, 2024-09 |
| Machine learning powered sketch aided design via topology optimization Zhang, Weisheng; Wang, Yue; Youn, Sung-Kie; Guo, Xu, COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, v.419, 2024-02 |
| Machine learning-assisted laser-induced breakdown spectroscopy for monitoring molten salt compositions of small modular reactor fuel under varying laser focus positions Lee, Yunu; Foster, Richard I.; Kim, Hyeongbin; Choi, Sungyeol, ANALYTICA CHIMICA ACTA, v.1241, 2023-02 |
| Machine learning-assisted optimization of TBBPA-bis-(2,3-dibromopropyl ether) extraction process from ABS polymer Wan, Yan; Zeng, Qiang; Shi, Pujiang; Yoon, Yong-Jin; Tay, Chor Yong; Lee, Jong-Min, CHEMOSPHERE, v.287, 2022-01 |
| Machine learning-based atom contribution method for the prediction of surface charge density profiles and solvent design Liu, Qilei; Zhang, Lei; Tang, Kun; Liu, Linlin; Du, Jian; Meng, Qingwei; Gani, Rafiqul, AICHE JOURNAL, v.67, no.2, pp.e17110, 2021-02 |
| Machine learning-based constitutive model for J2- plasticity Jang, DP; Fazily, Piemaan; Yoon, Jeong Whan, INTERNATIONAL JOURNAL OF PLASTICITY, v.138, pp.102919, 2021-03 |
Machine Learning-Based Dimension Optimization for Two-Stage Precoder in Massive MIMO Systems with Limited Feedback Kang, Jinho; Lee, Jung Hoon; Choi, Wan, APPLIED SCIENCES-BASEL, v.9, no.14, 2019-07 |
| Machine learning-based discovery of molecules, crystals, and composites: A perspective review Lee, Sangwon; Byun, Haeun; Cheon, Mujin; Kim, Jihan; Lee, Jay Hyung, KOREAN JOURNAL OF CHEMICAL ENGINEERING, v.38, no.10, pp.1971 - 1982, 2021-10 |
| Machine learning-based discrete event dynamic surrogate model of communication systems for simulating the command, control, and communication system of systems Kang, Bong Gu; Seo, Kyung-Min; Kim, Tag Gon, SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL, v.95, no.8, pp.673 - 691, 2019-08 |
| Machine learning-based inverse design methods considering data characteristics and design space size in materials design and manufacturing: a review Lee, Junhyeong; Park, Donggeun; Lee, Mingyu; Lee, Hugon; Park, Kundo; Lee, Ikjin; Ryu, Seunghwa, MATERIALS HORIZONS, v.10, no.12, pp.5436 - 5456, 2023-12 |
| Machine learning-based optimization of segmented thermoelectric power generators using temperature-dependent performance properties Demeke, Wabi; Ryu, Byungki; Ryu, Seunghwa, APPLIED ENERGY, v.355, 2024-02 |
| Machine learning-based self-powered acoustic sensor for speaker recognition Han, Jae Hyun; Bae, Kang Min; Hong, Seong Kwang; Park, Hyunsin; Kwak, Jun-Hyuk; Wang, Hee Seung; Joe, Daniel Juhyung; et al, NANO ENERGY, v.53, pp.658 - 665, 2018-11 |
| Machine learning-driven stress integration method for anisotropic plasticity in sheet metal forming Fazily, Piemaan; Yoon, Jeong Whan, INTERNATIONAL JOURNAL OF PLASTICITY, v.166, 2023-07 |
| Machine learning-enabled development of high performance gradient-index phononic crystals for energy focusing and harvesting Lee, Sangryun; Choi, Wonjae; Park, Jeong Won; Kim, Dae-Su; Nahm, Sahn; Jeon, Wonju; Gu, Grace X.; et al, NANO ENERGY, v.103, 2022-12 |
| Machine Learning-Enabled Exploration of the Electrochemical Stability of Real-Scale Metallic Nanoparticles Bang, Kihoon; Hong, Doosun; Park, Youngtae; Kim, Donghun; Han, Sang Soo; Lee, Hyuck-Mo, NATURE COMMUNICATIONS, v.14, no.1, 2023-05 |
| Machine learning-enabled textile-based graphene gas sensing with energy harvesting-assisted IoT application Zhu, Jianxiong; Cho, Minkyu; Li, Yutao; He, Tianyiyi; Ahn, Junseong; Park, Jaeho; Ren, Tian-Ling; et al, NANO ENERGY, v.86, 2021-08 |
| Machine Learning-Guided Etch Proximity Correction Shim, Seongbo; Shin, Youngsoo, IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, v.30, no.1, pp.1 - 7, 2017-02 |
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