Results 91 to 100 of about 3,002,307 (310)
Neural Network Adaptive Control With Long Short‐Term Memory
International Journal of Adaptive Control and Signal Processing, EarlyView.ABSTRACT In this study, we propose a novel adaptive control architecture that provides dramatically better transient response performance compared to conventional adaptive control methods. This is accomplished by the synergistic employment of a traditional adaptive neural network (ANN) controller and a long short‐term memory (LSTM) network.
Emirhan Inanc +4 more
wiley +1 more source
ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems
, 2014 Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine towards accomplishing the task of interest.
Aparna Lakshmiratan +10 more
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Advanced Biology, EarlyView.In vitro cancer models are advantageous for studying important processes such as tumorigenesis, cancer growth, invasion, and metastasis. The complexity and biological relevance increase depending on the model structure, organization, and composition of materials and cells.
Kyndra S. Higgins +2 more
wiley +1 more source
IEEE AccessThe increasing demand for wind power requires more frequent inspections to identify defects in the Wind Turbine Blades (WTBs). These defects, if not detected, can compromise the structural integrity and safety of wind turbines.
Majid Memari +4 more
doaj +1 more source
Is it ethical to avoid error analysis?
, 2017 Machine learning algorithms tend to create more accurate models with the availability of large datasets. In some cases, highly accurate models can hide the presence of bias in the data.
García-Martín, Eva, Lavesson, Niklas
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Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics
Advanced Engineering Materials, EarlyView.Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani +2 more
wiley +1 more source
Climate data selection for multi-decadal wind power forecasts
Environmental Research LettersReliable wind speed data is crucial for applications such as estimating local (future) wind power. Global climate models (GCMs) and regional climate models (RCMs) provide forecasts over multi-decadal periods.
Sofia Morelli +3 more
doaj +1 more source
Deterministic Uncertainty Estimation for Multi-Modal Regression With Deep Neural Networks
IEEE AccessPrediction interval (PI) is a common method to represent predictive uncertainty in regression by deep neural networks. This paper proposes an extension of the prediction interval by using a union of disjoint intervals. Since previous PI methods assumed a
Jaehak Cho +3 more
doaj +1 more source
A Case‐Based Reasoning Approach to Model Manufacturing Constraints for Impact Extrusion
Advanced Engineering Materials, EarlyView.A hybrid modeling approach is presented that combines constraint‐based process modeling and case‐based reasoning. The model formalizes manufacturing constraints and integrates simulation data to model complex manufacturing processes. The approach supports manufacturability analysis during product design through an adaptive modeling environment.
Kevin Herrmann +5 more
wiley +1 more source