Journal: Scientific Reports

Article Title: Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete

doi: 10.1038/s41598-024-77144-9

Figure Lengend Snippet: The fundamental configuration of ANFIS.

Article Snippet: The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid intelligent system that blends neural network and fuzzy logic functionalities to perform adaptive and accurate inference, especially in modeling complex and nonlinear systems .

Techniques:

Journal: Scientific Reports

Article Title: Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete

doi: 10.1038/s41598-024-77144-9

Figure Lengend Snippet: ANFIS model variables interactions.

Article Snippet: The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid intelligent system that blends neural network and fuzzy logic functionalities to perform adaptive and accurate inference, especially in modeling complex and nonlinear systems .

Techniques:

Journal: Scientific Reports

Article Title: Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete

doi: 10.1038/s41598-024-77144-9

Figure Lengend Snippet: ANFIS processing settings.

Article Snippet: The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid intelligent system that blends neural network and fuzzy logic functionalities to perform adaptive and accurate inference, especially in modeling complex and nonlinear systems .

Techniques: Generated

Journal: Scientific Reports

Article Title: Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete

doi: 10.1038/s41598-024-77144-9

Figure Lengend Snippet: Graphical plot of ANFIS model training sets.

Article Snippet: The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid intelligent system that blends neural network and fuzzy logic functionalities to perform adaptive and accurate inference, especially in modeling complex and nonlinear systems .

Techniques:

Journal: Scientific Reports

Article Title: Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete

doi: 10.1038/s41598-024-77144-9

Figure Lengend Snippet: Graphical plot of ANFIS model testing sets.

Article Snippet: The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid intelligent system that blends neural network and fuzzy logic functionalities to perform adaptive and accurate inference, especially in modeling complex and nonlinear systems .

Techniques:

Journal: Scientific Reports

Article Title: Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete

doi: 10.1038/s41598-024-77144-9

Figure Lengend Snippet: ANFIS Membership function plots.

Article Snippet: The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid intelligent system that blends neural network and fuzzy logic functionalities to perform adaptive and accurate inference, especially in modeling complex and nonlinear systems .

Techniques:

Journal: Scientific Reports

Article Title: Artificial intelligence prediction of the mechanical properties of banana peel-ash and bagasse blended geopolymer concrete

doi: 10.1038/s41598-024-77144-9

Figure Lengend Snippet: Statisical computations to evaluate the performance of the developed model.

Article Snippet: The Adaptive Neuro-Fuzzy Inference System (ANFIS) is a hybrid intelligent system that blends neural network and fuzzy logic functionalities to perform adaptive and accurate inference, especially in modeling complex and nonlinear systems .

Techniques:

Journal: Scientific Reports

Article Title: Evaluation of sisal fiber and aluminum waste concrete blend for sustainable construction using adaptive neuro-fuzzy inference system

doi: 10.1038/s41598-023-30008-0

Figure Lengend Snippet: ANFIS model structure generated from MATLAB R2020a.

Article Snippet: The ANFIS computation toolbox in MATLAB software was adopted for the model simulation, testing, training and validation of the response function using hybrid method of optimization and grid partition method of FIS at 100 Epochs.

Techniques: Generated