DMTD algorithm. by Yunhu Huang (21402795)

“…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”

Optimization parameters for the three treatment plans performed for the homogeneous and heterogeneous phantoms. by Masashi Yagi (3186909)

Subjects:

The <i>D</i>_<i>98</i> in the CTV and the for the nominal scenario optimized using the WC algorithm in homogeneous and heterogeneous phantom. by Masashi Yagi (3186909)

Subjects:

The <i>D</i>_<i>98</i> in the CTV and the for the nominal scenario optimized using the SC algorithm in homogeneous and heterogeneous phantoms. by Masashi Yagi (3186909)

Subjects:

Improved LMedS-based for sag measurement accuracy of transmission lines via PSO method by Xingzhi Ren (21400870)

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

Algorithm for generating hyperparameter. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

The variation of the DVHs of dose distributions in the patient case reassessed for 28 different perturbations of beam ranges and positions in the CTV (orange) and OAR (light blue)... by Masashi Yagi (3186909)

Subjects:

Results of machine learning algorithm. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

ROC comparison of machine learning algorithm. by Balraj Preet Kaur (20370832)

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”

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. …”

Table2_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

Table1_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

Table3_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

Table4_Identification of Pan-Cancer Biomarkers Based on the Gene Expression Profiles of Cancer Cell Lines.XLSX by ShiJian Ding (11764646)

EITO_P with flexible trip time. by Yunhu Huang (21402795)

“…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”

Energy consumption in the PPO process. by Yunhu Huang (21402795)

“…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”

Speed limits. by Yunhu Huang (21402795)

“…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”

Running time in the PPO process. by Yunhu Huang (21402795)

“…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”

Speed limits and gradients from RJ to WYJ. by Yunhu Huang (21402795)

“…Finally, we conducted comparative tests of the manual driving, intelligent driving algorithm (ITOR, STON), and the algorithms proposed in this paper, EITO, using real line data from the Yizhuang Line of Beijing Metro (YLBS). …”