Algorithm performance in different operational phases. by Dongqing Zhang (423941)

FFT feature extraction. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Fig 2 - Single image de-raining by multi-scale Fourier Transform network by Chaobing Zheng (20896579)

Data Sheet 1_Comparison of multiple machine learning models for predicting prognosis of pancreatic ductal adenocarcinoma based on contrast-enhanced CT radiomics and clinical featur... by Yue Huang (285485)

“…Objective<p>The aim of this study was to evaluate the prognostic potential of combining clinical features and radiomics with multiple machine learning (ML) algorithms in pancreatic ductal adenocarcinoma (PDAC).…”

BiLSTM model structure diagram [30]. by Yuye Zou (22806476)

“…The model employs a sophisticated three-phase methodology: (1) decomposition through Variational Mode Decomposition (VMD) to extract multiple intrinsic mode functions (IMFs) from the original time series, effectively capturing its nonlinear and complex patterns; (2) optimization using a Chaotic Particle Swarm Optimization (CPSO) algorithm to fine-tune the Bi-directional Long Short-Term Memory (BiLSTM) network parameters, thereby improving both predictive accuracy and model stability; and (3) integration of predictions from both high-frequency and low-frequency components to generate comprehensive final forecasts. …”

VMD-CPSO-BiLSTM network structure. by Yuye Zou (22806476)

“…The model employs a sophisticated three-phase methodology: (1) decomposition through Variational Mode Decomposition (VMD) to extract multiple intrinsic mode functions (IMFs) from the original time series, effectively capturing its nonlinear and complex patterns; (2) optimization using a Chaotic Particle Swarm Optimization (CPSO) algorithm to fine-tune the Bi-directional Long Short-Term Memory (BiLSTM) network parameters, thereby improving both predictive accuracy and model stability; and (3) integration of predictions from both high-frequency and low-frequency components to generate comprehensive final forecasts. …”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…Five types of features were considered: (1) percentage of pixels of the different colour categories defined by hue angle, (2) average values of each channel, (3) average and median channel value of each colour category region, (4) threshold parameters based on reddish region descriptors and (5) total number of leaf pixels (<a href="#sup1" target="_blank">Supplementary Data S4</a>). The described extracted features were used to predict leaf betalain content (µg per FW) using multiple machine learning regression algorithms (Linear regression, Ridge regression, Gradient boosting, Decision tree, Random forest and Support vector machine) using the <i>Scikit-learn</i> 1.2.1 library in Python (v.3.10.1) (list of hyperparameters used is given in <a href="#sup1" target="_blank">Supplementary Data S5</a>). …”

Raw dataset. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Classification report of XGBoost. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Confusion matrix of RF. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Distribution of faults types. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Classification report of KNN. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Confusion matrix of XGBoost. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Confusion matrix of KNN. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Distribution of fault currents. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Confusion matrix of DT. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

KNN model working [80]. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Line plots current over fault type. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Classification report of decision tree. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”

Classification report of random forest. by Zawar Ahmed Khan (22574556)

“…<div><p>This study explores the design of an effective fault classification algorithm for 3 phase induction motor, an integral unit in many industrial systems. …”