日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

A review of applications of machine learning in quantum dots research

机器学习在量子点研究中的应用综述

Malashin, Ivan; Martysyuk, Dmitry; Nelyub, Vladimir; Borodulin, Aleksei; Gantimurov, Andrei; Tynchenko, Vadim

Multi-objective optimization of a regional biogas supply chain using organic waste

利用有机废料对区域沼气供应链进行多目标优化

Malashin, Ivan P; Martysyuk, Dmitry; Nelyub, Vladimir; Borodulin, Aleksei; Gantimurov, Andrei; Tynchenko, Vadim

Support Vector Machines in Polymer Science: A Review

支持向量机在聚合物科学中的应用:综述

Malashin, Ivan; Tynchenko, Vadim; Gantimurov, Andrei; Nelyub, Vladimir; Borodulin, Aleksei

Physics-Informed Neural Networks in Polymers: A Review

聚合物中的物理信息神经网络:综述

Malashin, Ivan; Tynchenko, Vadim; Gantimurov, Andrei; Nelyub, Vladimir; Borodulin, Aleksei

Machine Learning in Polymeric Technical Textiles: A Review

机器学习在聚合物技术纺织品中的应用:综述

Malashin, Ivan; Martysyuk, Dmitry; Tynchenko, Vadim; Gantimurov, Andrei; Nelyub, Vladimir; Borodulin, Aleksei; Galinovsky, Andrey

Data-Driven Optimization of Discontinuous and Continuous Fiber Composite Processes Using Machine Learning: A Review

基于机器学习的不连续和连续纤维复合材料工艺数据驱动优化:综述

Malashin, Ivan; Martysyuk, Dmitry; Tynchenko, Vadim; Gantimurov, Andrei; Nelyub, Vladimir; Borodulin, Aleksei

Boosting-Based Machine Learning Applications in Polymer Science: A Review

基于提升算法的机器学习在聚合物科学中的应用:综述

Malashin, Ivan; Tynchenko, Vadim; Gantimurov, Andrei; Nelyub, Vladimir; Borodulin, Aleksei

Minimizing unnecessary tax audits using multi-objective hyperparameter tuning of XGBoost with focal loss

利用 XGBoost 和焦点损失函数进行多目标超参数调优,最大限度地减少不必要的税务审计。

Malashin, Ivan P; Masich, Igor S; Tynchenko, Vadim S; Gantimurov, Andrei P; Nelyub, Vladimir A; Borodulin, Aleksei S

A Multi-Objective Optimization of Neural Networks for Predicting the Physical Properties of Textile Polymer Composite Materials

基于神经网络的多目标优化方法预测纺织聚合物复合材料的物理性能

Malashin, Ivan; Tynchenko, Vadim; Gantimurov, Andrei; Nelyub, Vladimir; Borodulin, Aleksei

Mechanical Testing of Selective-Laser-Sintered Polyamide PA2200 Details: Analysis of Tensile Properties via Finite Element Method and Machine Learning Approaches

选择性激光烧结聚酰胺PA2200力学性能测试详情:基于有限元法和机器学习方法的拉伸性能分析

Malashin, Ivan; Martysyuk, Dmitriy; Tynchenko, Vadim; Nelyub, Vladimir; Borodulin, Aleksei; Galinovsky, Andrey