Results 161 to 170 of about 5,089,183 (236)

Enhanced Pure Pursuit Path Tracking Algorithm for Mobile Robots Optimized by NSGA-II with High-Precision GNSS Navigation. [PDF]

Sensors (Basel)
Jiang X, Kuroiwa T, Cao Y, Sun L, Zhang H, Kawaguchi T, Hashimoto S.   +6 more
europepmc   +1 more source

Optimized Design of a Triangular Shear Piezoelectric Sensor Using Non-Dominated Sorting Genetic Algorithm-II(NSGA-II). [PDF]

Sensors (Basel)
Shi Y, Dai J.
europepmc   +1 more source

Multi-Objective Optimization of Injection Molding Process Parameters for Junction Boxes Based on BP Neural Network and NSGA-II Algorithm. [PDF]

Materials (Basel)
Hong T, Huang D, Ding F, Zhang L, Dong F, Chen L.   +5 more
europepmc   +1 more source

Multi-Objective NSGA-II Optimization of Single- and Dual-Fluid ORC-VCC Systems Using Butane and Isobutane. [PDF]

Materials (Basel)
Witanowski Ł.
europepmc   +1 more source

Resonant MEMS Accelerometer with Low Cross-Axis Sensitivity-Optimized Based on BP and NSGA-II Algorithms. [PDF]

Micromachines (Basel)
Miao J, Li P, Lv M, Nie S, Liu Y, Liang R, Ma W, Zhuang X.   +7 more
europepmc   +1 more source

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Sustainable multi-objective process planning in reconfigurable manufacturing environment: adapted new dynamic NSGA-II vs New NSGA-III

International Journal of Production Research, 2022
The highly competitive and volatile market puts companies in a tough position. While cost and time efficiency are important to stay competitive, environmental awareness is more and more critical.
Lyes Benyoucef, Mohamed Amine Boutiche
exaly   +2 more sources

A comprehensive survey on NSGA-II for multi-objective optimization and applications

Artificial Intelligence Review, 2023
Haiping Ma, Ma Haiping
exaly   +2 more sources

A feature selection approach based on NSGA-II with ReliefF

Applied Soft Computing, 2023
In this paper, a hybrid feature selection algorithm based on a multi-objective algorithm with ReliefF (MOFS-RFGA) is proposed. Combining the advantages of filter and wrapper methods, the two types of algorithms are hybridized to improve the capability when solving feature selection problems.
Yu Xue, Hao Zhu, Ferrante Neri
semanticscholar   +3 more sources

Multi-objective classification based on NSGA-II

International Journal of Computing Science and Mathematics, 2018
Yu Xue, T H Ma
exaly   +2 more sources

Multi-objective optimization for materials design with improved NSGA-II

Materials Today Communications, 2021
Quan Qian
exaly   +2 more sources