AIMC Topic: Temperature

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Improving multiple model ensemble predictions of daily precipitation and temperature through machine learning techniques.

Scientific reports Mar 18, 2022
Multi-Model Ensembles (MMEs) are used for improving the performance of GCM simulations. This study evaluates the performance of MMEs of precipitation, maximum temperature and minimum temperature over a tropical river basin in India developed by vario...
Machine Learning Temperature Support Vector Machine Rivers Linear Models
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Microfluidic manipulation by spiral hollow-fibre actuators.

Nature communications Mar 14, 2022
A microfluidic manipulation system that can sense a liquid and control its flow is highly desirable. However, conventional sensors and motors have difficulty fitting the limited space in microfluidic devices; moreover, fast sensing and actuation are ...
Temperature Robotics Microfluidics Lab-On-A-Chip Devices
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Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning: Average climate versus extremes.

Global change biology Feb 24, 2022
The global distribution of vegetation is largely determined by climatic conditions and feeds back into the climate system. To predict future vegetation changes in response to climate change, it is crucial to identify and understand key patterns and p...
Machine Learning Forecasting Temperature Climate Change
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Light-Induced Topological Patterning toward 3D Shape-Reconfigurable Origami.

Small (Weinheim an der Bergstrasse, Germany) Feb 20, 2022
Shape-reconfigurable materials are crucial in many engineering applications. However, because of their isotropic deformability, they often require complex molding equipment for shaping. A polymeric origami structure that follows predetermined deforme...
Temperature Robotics Polymers
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Modeling Soil Temperature for Different Days Using Novel Quadruplet Loss-Guided LSTM.

Computational intelligence and neuroscience Feb 17, 2022
Soil temperature ( ), a key variable in geosciences study, has generated growing interest among researchers. There are many factors affecting the spatiotemporal variation of , which poses immense challenges for the estimation. To enrich processi...
Neural Networks, Computer Temperature Soil Wind
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Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer.

Analytical chemistry Feb 15, 2022
Biofluids such as synovial fluid, blood plasma, and saliva contain several proteins which impart non-Newtonian properties to the biofluids. The concentration of such protein macromolecules in biofluids is regarded as an important biomarker for the di...
Machine Learning Temperature Microfluidics Rheology Viscosity Solutions
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Attention-Based Deep Recurrent Neural Network to Forecast the Temperature Behavior of an Electric Arc Furnace Side-Wall.

Sensors (Basel, Switzerland) Feb 12, 2022
Structural health monitoring (SHM) in an electric arc furnace is performed in several ways. It depends on the kind of element or variable to monitor. For instance, the lining of these furnaces is made of refractory materials that can be worn out over...
Neural Networks, Computer Forecasting Temperature Electricity Time
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Investigation of Three-Dimensional Condensation Film Problem over an Inclined Rotating Disk Using a Nonlinear Autoregressive Exogenous Model.

Computational intelligence and neuroscience Feb 10, 2022
This paper analyzed the three-dimensional (3D) condensation film problem over an inclined rotating disk. The mathematical model of the problem is governed by nonlinear partial differential equations (NPDE's), which are reduced to the system of nonlin...
Neural Networks, Computer Algorithms Temperature Models, Theoretical
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Deep learning-based optimization of a microfluidic membraneless fuel cell for maximum power density via data-driven three-dimensional multiphysics simulation.

Bioresource technology Feb 8, 2022
A deep learning-based method for optimizing a membraneless microfluidic fuel cell (MMFC)performance by combining the artificial neural network (ANN) and genetic algorithm (GA) was for the first time introduced. A three-dimensional multiphysics model ...
Neural Networks, Computer Computer Simulation Temperature Deep Learning Microfluidics
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Interpretable Short-Term Electrical Load Forecasting Scheme Using Cubist.

Computational intelligence and neuroscience Feb 8, 2022
Daily peak load forecasting (DPLF) and total daily load forecasting (TDLF) are essential for optimal power system operation from one day to one week later. This study develops a Cubist-based incremental learning model to perform accurate and interpre...
Neural Networks, Computer Forecasting Temperature Electricity
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