Applications of Computational Intelligence in Concrete Technology

Applications of Computational Intelligence in Concrete Technology

Gupta, Sakshi; Thakur, Mohindra Singh; Sihag, Parveen; Kose, Utku

Taylor & Francis Ltd

06/2022

306

Dura

Inglês

9781032013022

15 a 20 dias

453

Descrição não disponível.
1. Usage of Computational Intelligence Techniques in Concrete Technology, 2. Developing Random Forest Random Tree and Linear Regression Model to Predict Compressive Strength of Concrete Using Glass Fiber, 3. Prediction of Compressive Strength at Elevated Temperatures Using Machine Learning Methods, 4. Implementation of Machine Learning Approaches to Evaluate Flexural Strength of Concrete With Glass Fiber, 5. A Comparative Study Using ANFIS and ANN for Determining the Compressive Strength of Concrete, 6. Prediction of Concrete Mix Compressive Strength Using Waste Marble Powder: A Comparison of ANN, RF, RT, and LR models, 7. Using GA to Predict the Compressive Strength of Concrete Containing Nano-Silica, 8. Evaluation of Models by Soft Computing Techniques for the Prediction of Compressive Strength of Concrete Using Steel Fibre, 9. Using Regression Model to Estimate the Splitting Tensile Strength for the Concrete With Basalt Fiber Reinforced Concrete, 10. Prediction of Compressive Strength of Self-Compacting Concrete Containing Silica's Using Soft Computing Techniques, 11. Using Soft Computing Techniques to Predict the Values of Compressive Strength of Concrete with Basalt Fiber Reinforced Concrete, 12. Soft Computing-Based Prediction of Compressive Strength of High Strength Concrete, 13. Forecasting Compressive Strength of Concrete Containing Nano-Silica Using Particle Swarm Optimization Algorithm and Genetic Algorithm, 14. Prediction of Ultrasonic Pulse Velocity of Concrete, 15. Evaluation of ANN and Tree-Based Techniques for Predicting the Compressive Strength of Granite Powder Reinforced Concrete, 16. Predicting Recycled Aggregates Compressive Strength in High-Performance Concrete Using Artificial Neural Networks, 17. Compressive Strength Prediction and Analysis of Concrete Using Hybrid Artificial Neural Networks
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artificial neural network;fuzzy system;prediction model;gaussian process;gene expression;programming tree;forest algorithm;Compressive Strength;Soft Computing Techniques;RF;Ann Model;Adaptive Neuro Fuzzy Inference Systems;RF Model;Soft Computing;Agreement Plot;Glass Fiber Reinforced Concrete;M5P Tree;SVM;ANFIS Model;Ann GA Model;Out-of Bag Error;Testing Data Sets;Coarse Aggregate;Self-compacting Concrete;BF;MLR;Membership Function;Fiber Reinforced Concrete;BPNN Model;Weka Software;GPR Model;Glass Fiber