Sensitivity Analysis and Strength Prediction of Fly Ash — Based Geopolymer Concrete with Polyethylene Terephtalate using Artificial Neural Network

Author:

Silva Dante L.,de Jesus Kevin Lawrence M.,Villaverde Bernard S.,Cahilig Crisialine Joy C.,Dela Cruz Jan Piola L.,Sario Jessa Maye S.

Publisher

IEEE

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Linear and Nonlinear Predictive Models for Manila City’s Condition and People Satisfaction;2023 IEEE 8th International Conference on Recent Advances and Innovations in Engineering (ICRAIE);2023-12-02

2. Deep learning based concrete compressive strength prediction model with hybrid meta-heuristic approach;Expert Systems with Applications;2023-12

3. Backpropagation Neural Network – Based Prediction of Crack Depth in Fly-Ash Geopolymer Concrete with Akaike and Bayesian Information Criterion;2023 6th International Conference on Computing and Big Data (ICCBD);2023-10-27

4. Performance Evaluation of Fiber Waste-Reinforced Polymer Using Backpropagation Neural Network Model and Finite Element Analysis;2023 IEEE 4th International Conference on Pattern Recognition and Machine Learning (PRML);2023-08-04

5. Hybrid Particle Swarm Optimization — Artificial Neural Network: Strength Prediction of Bambusa Blumeana Fiber and Recycled Coarse Aggregate for Multi-generation Recycled Aggregate Concrete;2023 IEEE 3rd International Conference on Software Engineering and Artificial Intelligence (SEAI);2023-06-16

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