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Uncertainty

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Robust Control Based on Adaptive Neural Network for the Process of Steady Formation of Continuous Contact Force in Unmanned Aerial Manipulator.

Sensors (Basel, Switzerland)
Contact force control for Unmanned Aerial Manipulators (UAMs) is a challenging issue today. This paper designs a new method to stabilize the UAM system during the formation of contact force with the target. Firstly, the dynamic model of the contact p...

Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities.

Environmental monitoring and assessment
In this article, the maximum and minimum daily temperature data for Indian cities were tested, together with the predicted diurnal temperature range (DTR) for monthly time horizons. RClimDex, a user interface for extreme computing indices, was used t...

A novel optimization method for belief rule base expert system with activation rate.

Scientific reports
Although the belief rule base (BRB) expert system has many advantages, such as the effective use of semi-quantitative information, objective description of uncertainty, and efficient nonlinear modeling capability, it is always limited by the problem ...

Model order reduction techniques to identify submarining risk in a simplified human body model.

Computer methods in biomechanics and biomedical engineering
This work investigates linear and non-linear parametric reduced order models (ROM) capable of replacing computationally expensive high-fidelity simulations of human body models (HBM) through a non-intrusive approach. Conventional crash simulation met...

Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction.

Environmental science and pollution research international
Precise wind speed prediction is crucial for the management of the wind power generation systems. However, the stochastic nature of the wind speed makes optimal interval prediction very complicated. In this paper, a hybrid approach consisting of impr...

Train-induced vibration attenuation measurements and prediction from ground soil to building column.

Environmental science and pollution research international
The investigation of the influence of soil-structure coupling on the vibration propagation pattern is the key to ensuring the reliability of the prediction of train-induced building vibration. This study selects different metro depots with over-track...

Tackling prediction uncertainty in machine learning for healthcare.

Nature biomedical engineering
Predictive machine-learning systems often do not convey the degree of confidence in the correctness of their outputs. To prevent unsafe prediction failures from machine-learning models, the users of the systems should be aware of the general accuracy...

Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction.

Nature communications
Unreliable predictions can occur when an artificial intelligence (AI) system is presented with data it has not been exposed to during training. We demonstrate the use of conformal prediction to detect unreliable predictions, using histopathological d...

Reinforcement Learning with Side Information for the Uncertainties.

Sensors (Basel, Switzerland)
Recently, there has been a growing interest in the consensus of a multi-agent system (MAS) with advances in artificial intelligence and distributed computing. Sliding mode control (SMC) is a well-known method that provides robust control in the prese...

Adaptive Interaction Control of Compliant Robots Using Impedance Learning.

Sensors (Basel, Switzerland)
This paper presents an impedance learning-based adaptive control strategy for series elastic actuator (SEA)-driven compliant robots without the measurement of the robot-environment interaction force. The adaptive controller is designed based on the c...