Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

Process fault of Tennessee Eastman process. by Faizan e Mustafa (18004325)

“…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …”

Hybrid feature selection algorithm of CSCO-ROA. by Afnan M. Alhassan (18349378)

“…Consequently, the prediction of BrC depends critically on the quick and precise processing of imaging data. The primary reason deep learning models are used in breast cancer detection is that they can produce findings more quickly and accurately than current machine learning-based techniques. …”

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

FEP Augmentation as a Means to Solve Data Paucity Problems for Machine Learning in Chemical Biology by Pieter B. Burger (4172578)

Subjects:

Construction process of RF. by Xini Fang (20861990)

“…<div><p>To enhance the accuracy and response speed of the risk early warning system, this study develops a novel early warning system that combines the Fuzzy C-Means (FCM) clustering algorithm and the Random Forest (RF) model. Firstly, based on operational risk theory, market risk, research and development risk, financial risk, and human resource risk are selected as the primary indicators for enterprise risk assessment. …”

Quantitative analysis of ACSA for TEP process. by Faizan e Mustafa (18004325)

“…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …”

The flowchart of the proposed algorithm. by Muhammad Ayyaz Sheikh (18610943)

“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”

Schematic representation of univariate ensemble-based feature selection. by Nanavath Kiran Singh Nayak (22184565)

Subjects:

ACSA pseudo code for proposed control process. by Faizan e Mustafa (18004325)

“…This algorithm possesses the capability to adapt its search behavior in response to the changing dynamics of the optimization process. …”

DataSheet1_Optimal capacity configuration of the wind-storage combined frequency regulation system considering secondary frequency drop.docx by Dongdong Li (123985)

Models’ performance without optimization. by Muhammad Usman Tariq (11022141)

“…The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. …”

Fig 9 - by Mouncef El Marghichi (17328361)

“…To achieve this, we propose a novel method that utilizes the gradient-based optimizer (GBO) to evaluate the SOH of lithium batteries. …”

Predictive performance indicators. by Mouncef El Marghichi (17328361)

“…To achieve this, we propose a novel method that utilizes the gradient-based optimizer (GBO) to evaluate the SOH of lithium batteries. …”

Fig 8 - by Mouncef El Marghichi (17328361)

“…To achieve this, we propose a novel method that utilizes the gradient-based optimizer (GBO) to evaluate the SOH of lithium batteries. …”