In this section, we will discuss the dynamical behavior through bifurcation and sensitivity.
Bifurcation analysis
From (18), we can write as
$$\begin{aligned} F^{”}=\frac{\alpha _1\kappa ^2+\alpha _4\kappa -\kappa \omega }{\alpha…
Category: 7. Maths
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Improved railway track faults detection using Mel-frequency cepstral coefficient and constant-Q transform features
This section discusses dataset collection and strategy, feature extraction techniques, machine learning methods for classification, and the recommended approach.
Dataset collection
The dataset holds crucial importance in the automated…
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Fractional differential quadrature method for modeling composite halide perovskite solar cells
Firstly, Discrete singular convolution differential quadrature (DQ) method combined with the technique of block-marching to analyze the halide perovskite CH3NH3GeI3 layer inserted between two layers (Electron transport layer- Hole transport…
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Mixed effect gradient boosting for high-dimensional longitudinal data
Mixed Effect Gradient Boosting (MEGB) is a hybrid statistical and machine learning technique that integrates the strengths of gradient boosting with mixed-effects modelling, addressing the unique challenges of longitudinal or hierarchical data….
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Medical triage as an AI ethics benchmark
In this work, we demonstrated the ability of LLMs to solve ethical dilemmas in the medical context. All models, except Mistral, consistently outperformed random guessing on the TRIAGE benchmark. This indicates that models do indeed have a good…
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Adaptive robust control of tea-picking-manipulator’s position tracking based on dead zone compensation with modified RBF
This section will setup the neural network model to establish the compensator model for the dead zone. Also, the control system stability will be analyzed.
GL matrix and GL multiplication operator
Define symbol “{·}” as GL matrix and “·”…
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Automated detection of Parkinson’s disease using improved linknet-ghostnet model based on handwriting images
Simulation procedure
The ILN-GNet model developed for PD detection was implemented using Python. Additionally, to run the simulation, we employed a system that had a 11th Gen Intel(R) Core (TM) i5-1135g7 CPU operating at 2.40 GHz and 2.42 GHz…
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Optimization and predictive performance of fly ash-based sustainable concrete using integrated multitask deep learning framework with interpretable machine learning techniques
It describes a design that makes an improved model for the prediction of concrete strength using Gradient Boosting and Deep Neural Networks, surpassing intrinsic low efficiency and high complexity issues in the existing models for the analysis of…
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A novel hesitant fuzzy tensor-based group decision-making approach with application to heterogeneous wireless network evaluation
In real-world scenarios, especially under uncertain and conflicting expert opinions, decision-makers often hesitate among several possible membership degrees when evaluating an element. This leads to the development of the hesitant fuzzy set…
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The optimization of low Earth orbit satellite constellation visibility with genetic algorithm for improved navigation potential
Configuration analysis of the single constellation
The mixed constellation analyzed in this study is composed of three main types: polar, Walker, and OCO constellations. The model construction places special emphasis on active compensation for…
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