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

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

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)

Datasets and their properties. by Olaide N. Oyelade (14047002)

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

Subjects:

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

S1 Data - by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Curve of step response signal of 6 algorithms. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Data Sheet 1_AI-driven optimization of dynamic vibration absorbers with hydraulic amplifier and mechanical inerter integration.pdf by Ahmed Shamseldin (19759437)

Wilcoxon’s rank sum test results. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Flowchart of MSHHOTSA. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Tension/compression spring design problem. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Speed reducer design problem. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Flowchart of TSA [43]. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Pressure vessel design problem. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”

Gear train design problem. by Guangwei Liu (181992)

“…The primary objective of MSHHOTSA is to address the limitations of the tunicate swarm algorithm, which include slow optimization speed, low accuracy, and premature convergence when dealing with complex problems. …”