This paper presents a bi-objective algorithm that optimizes the error and the sum of the absolute weights of a Multi-Layer Perceptron neural network. The algori ...

Dynamic Multi-Objective Optimization Algorithm Guided by Recurrent Neural Network Abstract: In recent years, prediction-based algorithms have attracted much attention for solving dynamic ...

Multi-objective evolutionary optimization of polynomial neural networks for modelling and prediction of explosive cutting process. Engineering Applications of Artificial Intelligence, 22(4): 676-687.

References Abouhamze, M. and Shakeri, M. [2007] “ Multi-objective stacking sequence optimization of laminated cylindrical panels using a genetic algorithm and neural networks,” Compos. Struct. 81(2), ...

Neural network optimization differs from other optimization techniques due to the unique characteristics of neural networks: non-convex loss functions, high-dimensional parameter spaces, noisy ...

Multi-objective Simulated Annealing for Hyper-parameter Optimization in Convolutional Neural Networks ... and the MOSA trade-off fronts obtained for this dataset are compared to the fronts generated ...

Combining multi-objective genetic algorithm and neural network dynamically for the complex optimization problems in physics. These files save the raw data created by DNMOGA, NBMOGA and NSGA-II, and ...