Journal: Journal of Electrical Engineering

Article Title: Comparison of Damping Performance of Conventional And Neuro–Fuzzy Based Power System Stabilizers Applied in Multi–Machine Power Systems

doi: 10.2478/jee-2013-0055

Figure Lengend Snippet: Fig. 3. Structure of proposed ANFPSS for the power system under study In MATLAB, the ANFIS editor graphics user inter- face is available in Fuzzy Logic Toolbox [15]. In the AN- FIS Editor, the fuzzy inference is generated using grid partitioning method. For grid partitioning, it uses the Fuzzy C-means clustering (FCM) data clustering tech- nique. FCM is a data clustering algorithm in which each

Article Snippet: In MATLAB, the ANFIS editor graphics user interface is available in Fuzzy Logic Toolbox [15].

Techniques: Generated

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: