Journal: Scientific Reports

Article Title: An efficient ANFIS-EEBAT approach to estimate effort of Scrum projects

doi: 10.1038/s41598-022-11565-2

Figure Lengend Snippet: Standard ANFIS architecture. Number of Story Points and Project Velocity are given as inputs. These inputs have been derived from 21 projects dataset (dataset sample given in Table ). ANFIS based exhaustive search MATLAB functionality has been used to decide the inputs. Different inputs (as feature pairs) tested against Actual Time. The feature pair with minimum error has been chosen in input layer.

Article Snippet: ANFIS based exhaustive search MATLAB functionality has been used to decide the inputs.

Techniques: Derivative Assay

Journal: Heliyon

Article Title: Optimization of adaptive neuro–fuzzy inference system (ANFIS) parameters via Box-Behnken experimental design approach: The prediction of chromium adsorption

doi: 10.1016/j.heliyon.2024.e25813

Figure Lengend Snippet: RMSE values obtained from ANFIS via BBD approach.

Article Snippet: Adaptive Neuro-Fuzzy Inference System (ANFIS), an artificial neural network based on the Takagi-Sugano fuzzy inference system, is a MATLAB application to make estimations depending on functions prepared by training fuzzy logic with a given data set.

Techniques:

Journal: Heliyon

Article Title: Optimization of adaptive neuro–fuzzy inference system (ANFIS) parameters via Box-Behnken experimental design approach: The prediction of chromium adsorption

doi: 10.1016/j.heliyon.2024.e25813

Figure Lengend Snippet: RMSE values obtained via Regression model and ANFIS prediction at optimum conditions.

Article Snippet: Adaptive Neuro-Fuzzy Inference System (ANFIS), an artificial neural network based on the Takagi-Sugano fuzzy inference system, is a MATLAB application to make estimations depending on functions prepared by training fuzzy logic with a given data set.

Techniques:

Journal: Heliyon

Article Title: Optimization of adaptive neuro–fuzzy inference system (ANFIS) parameters via Box-Behnken experimental design approach: The prediction of chromium adsorption

doi: 10.1016/j.heliyon.2024.e25813

Figure Lengend Snippet: Train and test data vs FIS output obtained with optimum ANFIS model (trimf 6-6-3).

Article Snippet: Adaptive Neuro-Fuzzy Inference System (ANFIS), an artificial neural network based on the Takagi-Sugano fuzzy inference system, is a MATLAB application to make estimations depending on functions prepared by training fuzzy logic with a given data set.

Techniques:

Journal: Heliyon

Article Title: Optimization of adaptive neuro–fuzzy inference system (ANFIS) parameters via Box-Behnken experimental design approach: The prediction of chromium adsorption

doi: 10.1016/j.heliyon.2024.e25813

Figure Lengend Snippet: Predicted data obtained with optimum ANFIS model vs. experimental data.

Article Snippet: Adaptive Neuro-Fuzzy Inference System (ANFIS), an artificial neural network based on the Takagi-Sugano fuzzy inference system, is a MATLAB application to make estimations depending on functions prepared by training fuzzy logic with a given data set.

Techniques:

Journal: Heliyon

Article Title: Optimization of adaptive neuro–fuzzy inference system (ANFIS) parameters via Box-Behnken experimental design approach: The prediction of chromium adsorption

doi: 10.1016/j.heliyon.2024.e25813

Figure Lengend Snippet: The comparison of other ANFIS modeling studies on Cr(VI) adsorption.

Article Snippet: Adaptive Neuro-Fuzzy Inference System (ANFIS), an artificial neural network based on the Takagi-Sugano fuzzy inference system, is a MATLAB application to make estimations depending on functions prepared by training fuzzy logic with a given data set.

Techniques: Comparison, Adsorption, Modification, Concentration Assay

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: