Improved Multilayer Perceptron Neural Networks Weights and Biases Based on The Grasshopper optimization Algorithm to Predict Student Performance on Ambient Learning

Exploring foci of: doi.org Improved Multilayer Perceptron Neural Networks Weights and Biases Based on The Grasshopper optimization Algorithm to Predict Student Performance on Ambient Learning January 2023 • Mercy K. Michira, Richard Rimiru, Waweru Mwangi The classification accuracy of a multi-layer Perceptron Neural Networks depends on the selection of its parameters such the connection weights and biases. Generating an optimal value of these parameters requires a suitable algorithm to train the multilayer perceptron neural networks. This paper presents swam based Grasshopper optimization algorithm that optimizes the connection weights and biases of Multilayer Perceptron Neural Network. Grasshopper optimization algorithm is a swarm-based metaheuristic algorithm ap… Open Article Page

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