Comparison between ILSTM and machine learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

Comparison between ILSTM and deep learning-based algorithms in binary classification. by Asmaa Ahmed Awad (16726315)

MSE for ILSTM algorithm in binary classification. by Asmaa Ahmed Awad (16726315)

“…In this paper, a novel, and improved version of the Long Short-Term Memory (ILSTM) algorithm was proposed. The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …”

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

Subjects:

DE algorithm flow. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Test results of different algorithms. by Ling Zhao (111365)

“…<div><p>To solve the problems of insufficient global optimization ability and easy loss of population diversity in building interior layout design, this study proposes a novel layout optimization model integrating interactive genetic algorithm and improved differential evolutionary algorithm to improve the global optimization ability and maintain population diversity in building layout design. …”

Routing policy based on path satisfaction. by Yang Yu (4292)

“…<div><p>In the operational planning of electric power communication networks, a well-structured service scheduling scheme based on the established network topology can significantly enhance the risk prevention capabilities of these networks. Since routing policies directly influence data transmission paths, routing optimization serves as an effective strategy for improving network performance by mitigating transmission risks and threats. …”

The AD-PSO-Guided WOA LSTM algorithm RMSE is based on the objective function compared to different algorithms. by Ahmed M. Elshewey (21463867)

Iterative optimization convergence curve of each algorithm. by Guangwei Liu (181992)

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

“…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 optimization results of each algorithm for the 8 benchmark functions. by Guangwei Liu (181992)

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

“…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)

“…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. …”

Optimal results of the different algorithms on the speed design reducer problem. by Guangwei Liu (181992)

Optimal results of the different algorithms on the pressure vessel design problem. by Guangwei Liu (181992)

Optimal results of the different algorithms on the gear train design problem. by Guangwei Liu (181992)

The optimization results of each algorithm for the CEC2019 benchmark functions. by Guangwei Liu (181992)

Optimal results of the different algorithms on the tension/compression spring design problem. by Guangwei Liu (181992)

Homomorphic binary tree. by Jianhua He (341366)

Best optimizer results of Lightbgm. by Balraj Preet Kaur (20370832)

“…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. …”