AIMC Topic: Uncertainty

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Nonlinear control of a class of non-affine variable-speed variable-pitch wind turbines with radial-basis function neural networks.

ISA transactions May 12, 2022
Due to complicated dynamics, wind turbines' governing equations are subject to uncertainties and unknown disturbance sources. Despite uncertainties and disturbance sources, the paper's focus is to design an adaptive controller that enables trajectory...
Nonlinear Dynamics Uncertainty Torque Computer Simulation Neural Networks, Computer
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Guaranteed cost-based feedback control design for fractional-order neutral systems with input-delayed and nonlinear perturbations.

ISA transactions May 9, 2022
Time delay in actuators is mainly caused by electrical and mechanical components. The effect is visible in the system response particularly when changing in the input command. Therefore, input delay is a problem in the control system design that must...
Algorithms Feedback Neural Networks, Computer Uncertainty Records Nonlinear Dynamics
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Investigating a Dual-Channel Network in a Sustainable Closed-Loop Supply Chain Considering Energy Sources and Consumption Tax.

Sensors (Basel, Switzerland) May 6, 2022
This paper proposes a dual-channel network of a sustainable Closed-Loop Supply Chain (CLSC) for rice considering energy sources and consumption tax. A Mixed Integer Linear Programming (MILP) model is formulated for optimizing the total cost, the amou...
Renewable Energy Uncertainty Algorithms Iran Fuzzy Logic
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The research for PLTS normalization method based on minimum entropy change and its application in MAGDM problem.

PloS one May 6, 2022
In the problem of multiple attributes group decision making (MAGDM), the probabilistic linguistic term sets (PLTSs) is an useful tool which can be more flexible and accurate to express the evaluation information of decision makers (DMs). However, due...
Linguistics Uncertainty Decision Making Fuzzy Logic Entropy
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Deep learning with self-supervision and uncertainty regularization to count fish in underwater images.

PloS one May 4, 2022
Effective conservation actions require effective population monitoring. However, accurately counting animals in the wild to inform conservation decision-making is difficult. Monitoring populations through image sampling has made data collection cheap...
Deep Learning Fishes Animals Ecosystem Uncertainty
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Asymptotic Tracking Control for Uncertain MIMO Systems: A Biologically Inspired ESN Approach.

IEEE transactions on neural networks and learning systems May 2, 2022
In this study, a biologically inspired echo state network (ESN)-based method is established for the asymptotic tracking control of a class of uncertain multi-input multi-output (MIMO) systems. By mimicking the characters of real biological systems, a...
Neural Networks, Computer Nonlinear Dynamics Uncertainty Feedback Computer Simulation
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Cloud-based neuro-fuzzy hydro-climatic model for water quality assessment under uncertainty and sensitivity.

Environmental science and pollution research international Apr 29, 2022
River water quality is a function of various bio-physicochemical parameters which can be aggregated for calculating the Water Quality Index (WQI). However, it is challenging to model the nonlinearity and uncertain behavior of these parameters. When d...
Rivers Water Quality Uncertainty Cloud Computing Fuzzy Logic Oxygen
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A novel belief rule base expert system with interval-valued references.

Scientific reports Apr 26, 2022
As an essential parameter in the belief rule base (BRB), referential values refer to evaluation criteria for describing attributes using quantitative data or linguistic terms, the rationality and preciseness of which are important to the modeling acc...
Biological Evolution Expert Systems Uncertainty Algorithms
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Optimistic reinforcement learning by forward Kullback-Leibler divergence optimization.

Neural networks : the official journal of the International Neural Network Society Apr 21, 2022
This paper addresses a new interpretation of the traditional optimization method in reinforcement learning (RL) as optimization problems using reverse Kullback-Leibler (KL) divergence, and derives a new optimization method using forward KL divergence...
Reinforcement, Psychology Uncertainty Robotics Algorithms Computer Simulation
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Semi-supervised medical image segmentation via a tripled-uncertainty guided mean teacher model with contrastive learning.

Medical image analysis Apr 8, 2022
Due to the difficulty in accessing a large amount of labeled data, semi-supervised learning is becoming an attractive solution in medical image segmentation. To make use of unlabeled data, current popular semi-supervised methods (e.g., temporal ensem...
Humans Supervised Machine Learning Image Processing, Computer-Assisted Uncertainty
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