AIMC Topic: Physical Phenomena

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Mechanism Analysis and Self-Adaptive RBFNN Based Hybrid Soft Sensor Model in Energy Production Process: A Case Study.

Sensors (Basel, Switzerland) Feb 10, 2022
Despite hard sensors can be easily used in various condition monitoring of energy production process, soft sensors are confined to some specific scenarios due to difficulty installation requirements and complex work conditions. However, industrial pr...
Physical Phenomena Algorithms Neural Networks, Computer
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Coverage Path Planning Methods Focusing on Energy Efficient and Cooperative Strategies for Unmanned Aerial Vehicles.

Sensors (Basel, Switzerland) Feb 6, 2022
The coverage path planning (CPP) algorithms aim to cover the total area of interest with minimum overlapping. The goal of the CPP algorithms is to minimize the total covering path and execution time. Significant research has been done in robotics, pa...
Algorithms Physical Phenomena Unmanned Aerial Devices Conservation of Energy Resources Robotics
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Neural Fourier Energy Disaggregation.

Sensors (Basel, Switzerland) Jan 9, 2022
Deploying energy disaggregation models in the real-world is a challenging task. These models are usually deep neural networks and can be costly when running on a server or prohibitive when the target device has limited resources. Deep learning models...
Neural Networks, Computer Physical Phenomena
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Command-filter-based adaptive neural tracking control for a class of nonlinear MIMO state-constrained systems with input delay and saturation.

Neural networks : the official journal of the International Neural Network Society Dec 21, 2021
This paper investigates the problem of adaptive tracking control for a class of nonlinear multi-input and multi-output (MIMO) state-constrained systems with input delay and saturation. During the process of the control scheme, neural network is emplo...
Uncertainty Physical Phenomena Computer Simulation Neural Networks, Computer Nonlinear Dynamics
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Integrative measurement analysis via machine learning descriptor selection for investigating physical properties of biopolymers in hairs.

Scientific reports Dec 21, 2021
Integrative measurement analysis of complex subjects, such as polymers is a major challenge to obtain comprehensive understanding of the properties. In this study, we describe analytical strategies to extract and selectively associate compositional i...
Keratins Physical Phenomena Magnetic Resonance Spectroscopy Biopolymers Spectroscopy, Fourier Transform Infrared Humans Hair Algorithms Cats Swine Machine Learning Cattle Animals
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A Novel Energy Compensation Scheme for Quality Enhancement in Time-Delayed Teleoperation With Multi-DoF Haptic Data Reduction and Communication.

IEEE transactions on haptics Dec 16, 2021
Efficient and low-delay exchange of hapticinformation plays a key role for the design of high-fidelity teleoperation systems that operate over real-world communication networks. In the presence of communication unreliabilities such as delay and packe...
Physical Phenomena User-Computer Interface Haptic Technology Humans Robotics
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A quasi-particle dictionary: exhaustive classification of energy band crossing in time-reversal-invariant systems.

Science bulletin Dec 14, 2021
Algorithms Physical Phenomena Machine Learning
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Artificial neural network-based adaptive control for a DFIG-based WECS.

ISA transactions Dec 10, 2021
This paper presents an artificial neural network-based adaptive control approach for a doubly-fed induction generator (DFIG) based wind energy conversion system (WECS). The control objectives are: (1) extraction of maximum available power from the wi...
Neural Networks, Computer Physical Phenomena Wind Computer Simulation Electric Power Supplies
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The LHC Olympics 2020 a community challenge for anomaly detection in high energy physics.

Reports on progress in physics. Physical Society (Great Britain) Dec 7, 2021
A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within ...
Humans Machine Learning Physics Physical Phenomena Supervised Machine Learning
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Automated Construction of Neural Network Potential Energy Surface: The Enhanced Self-Organizing Incremental Neural Network Deep Potential Method.

Journal of chemical information and modeling Nov 9, 2021
In recent years, the use of deep learning (neural network) potential energy surface (NNPES) in molecular dynamics simulation has experienced explosive growth as it can be as accurate as quantum chemistry methods while being as efficient as classical ...
Molecular Dynamics Simulation Physical Phenomena Neural Networks, Computer Humans
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