Using the cold bending of aluminum tubes as the application case, the ML model is evaluated with high reliability and efficiency in springback prediction and compensation strategy of springback.doi:10.1007/978-3-030-75381-8_13J. MaH. Li
Accurate prediction of compressional (P-wave) and shear (S-wave) velocity is vital for structural, geomechanical, and petrophysical analyses of subsurface formations. Since velocity is typically measured as its reciprocal, slowness is the standard parameter recorded in sonic logs and is the focus of...
learnMET: an R package to apply machine learning methods for genomic prediction using multi-environment trial data Cathy C. Westhues, Henner Simianer, Timothy M. Beissinger. G3. doi: https://doi.org/10.1093/g3journal/jkac226 Feedback We are glad about any new user testing learnMET! Pleas...
is defined as the duration from the time when raw packets are collected to the time when the detection result is given, it means that detection latency consists of two parts: the time for online feature extraction time and the time for model inference (i.e., prediction or classification). ...
The initial phase involves gathering relevant data to create a user profile or model for prediction tasks. The data may include such points as the user's attributes, behaviors, or content of the user accesses’ resources. Recommendation engines mostly rely on two types of data such as: explicit...
They ran coverage prediction experiments on two small RISC-V cores and a TPU. They look at points covered by10-90% of random tests to exclude trivial cases. The authors compare results against 3 methods: statistical frequency random patterns; a multi-layer perceptron (MLP) treating the design...
Among the different ML models examined, the RFC is found to be the most reliable prediction tool. However, individual ensemble models are prone to overfitting; hence, voting ensemble models are considered to improve prediction accuracy. Out of 62 possible combinations, a voting ensemble consisting ...
Automated systems for shipowners and shipping companies: FOS (Fuel Optimization System), Vessel Performance Monitoring, Fleet insight, Route planner, Catering, Port Call and other solutions for maritime logistics
Interpretable Battery Cycle Life Range Prediction Using Early Cell Degradation Data Battery cycle life prediction using early degradation data has many potential applications throughout the battery product life cycle. For that reason, vari... Z Huang,S Yang,ATW Gros - 《IEEE Transactions on Transporta...
Prediction datasets。表1显示了我们的数据集与相关预测数据集之间的比较。Argoverse Motion Forecasting[6]是第一个大规模预测数据集。它拥有320小时的驾驶数据,规模前所未有,并提供带有中心线和可行驶区域注释的简单语义地图。然而,由于当时目标检测领域的状态以及人工标注训练数据量不足(113个场景),数据集中的自动标记...