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Optimized 8-Parameter Relay-Based Delayed Thermal Process Model Identification via Saturated Relay and Artificial Delay
This study aims at an extension and substantial improvement of the recently published relay-feedback parameter identification of an...
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CL-BPUWM: continuous learning with Bayesian parameter updating and weight memory
Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new...
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Exploring Artificial Neural Network for X-Parameter and S-Parameter Modelling of HEMT
In this research paper, we have explored the efficiency of artificial neural network (ANN) for the S-parameter and X-parameter modelling of high...
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Surface roughness prediction and process parameter optimization of Ti-6Al-4 V by magnetic abrasive finishing
In order to effectively predict the surface roughness Ra of Ti-6Al-4 V material after magnetic abrasive finishing (MAF) process, and optimize the...
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Enhancing damage prediction in bulk metal forming through machine learning-assisted parameter identification
The open-source parameter identification tool ADAPT (A diversely applicable parameter identification Tool) is integrated with a machine...
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In situ image processing for process parameter-build quality dependency of plasma transferred arc additive manufacturing
Plasma transferred arc additive manufacturing (PTA-AM) is a high volume and high speed directed energy deposition (DED) technique that uses metal...
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Guaranteed Parameter Estimation for Cooperative Models
The parameters of cooperative models are estimated in a boundederror context, i.e., all uncertain quantities are assumed to be bounded, with known...
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The significant impact of parameter tuning on blocking bug prediction
Software development projects are prone to bugs that can hinder the development process and delay software release. Among the most critical bugs are...
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Powder bed fusion of high-Mn-N Ni-free austenitic stainless steel: achieving low porosity and high mechanical strength through process parameter selection
The emergence of innovative high-performance stainless steels is essential at the forefront of material science. This research highlights the...
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Evaluation and Optimization of Process Parameter for Surface Roughness of 3D-Printed PETG Specimens Using Taguchi Method at Constant Printing Temperature
3D printing technology is also known as additive manufacturing technology where the products are manufactured layer by layer. In recent years, huge...
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A method for process parameter optimization of simultaneous double-sided friction stir welding using a heat transfer model
This paper presents a method for optimizing process parameters of simultaneous double-sided friction stir welding (SDS-FSW). Building upon the...
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Process parameter determination for small recycling plants for the production of filament for FFF printing using the Taguchi method
With the increasing use of the filament fabrication process, the in-house production of filament and the recycling of PLA waste is becoming more and...
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Parameter Investigation for the In-Situ Hybridization Process by Deep Drawing of Dry Fiber-Metal-Laminates
A newly developed in-situ-hybridization single-step process for the manufacturing of formed fiber-metal-laminates (FML) was introduced in previous...
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Monitoring variability in parameter estimates for lumped parameter models of the systemic circulation using longitudinal hemodynamic measurements
BackgroundPhysics-based cardiovascular models are only recently being considered for disease diagnosis or prognosis in clinical settings. These...
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Research on parameter identification of fracture model for titanium alloy under wide stress triaxiality based on machine learning
The abilities to describe the fracture behavior and calibrate the relevant parameters are essential factors in evaluating ductile fracture criteria...
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State Parameter Based Liquefaction Probability Evaluation
The relative density and effective stress of the soil influence the cyclic stress or liquefaction behaviour of granular soil significantly. The state...
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How to compute suitable vicinity parameter and sampling time of recurrence analysis
We show how the maximum of recurrence-microstates entropy configures a new way to properly compute appropriate recurrence vicinity parameter and time...
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Neural Network Modeling for Process Parameter Optimization During Machining of EN24 STEEL
In recent years, there has been a growing interest in tool wear prediction by machining characteristics such as interface temperature, friction, and...
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Learning search algorithm to solve real-world optimization problems and parameter extract of photovoltaic models
Solar energy is widely acknowledged as a promising and abundant source of clean electricity. Unfortunately, the efficiency of converting solar energy...
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FDM-3D printing parameter optimization using taguchi approach on surface roughness of thermoplastic polyurethane parts
FDM (Fused Deposition Modelling) 3D Printing requires the special review of process parameters with taguchi optimization for optimal print surface...
