toolbox gui 2.0  (MathWorks Inc)

Journal: Human Brain Mapping

Article Title: The Influence of Structural Brain Changes on Cognition in the Context of Healthy Aging: Exploring Mediation Effects Through gBAT —The Graphical Brain Association Tool

doi: 10.1002/hbm.70038

Figure Lengend Snippet: (A) Path diagram showing the mediation analyses that were performed to understand the influence of age on cognition through reductions in brain volume. Age was used as the predictor, either total MoCA score or one of six subscores were used as the outcome variable, and regional brain volume across 189 regions was used as the mediator in a robust ordinary least squares mediation model. Path a assesses the effect of age on brain volume. Path b assesses the effect of ROI‐wise brain volume on MoCA scores after controlling for age. Path c assesses the direct effect of age on MoCA. Path c' assesses the effect of age on MoCA after controlling for the mediator. Path ab assesses the indirect effect of age on MoCA through brain volume. (B) Graphical User Interface (GUI) is displayed which enables user‐friendly way of performing ROI‐based whole‐brain mediation analysis by entering behavioral data and preprocessed brain scans. As illustrated on the right, the results can be automatically visualized on brain figures by adjusting the GUI settings accordingly.

Article Snippet: The GUI leverages MATLAB's Image Processing Toolbox for efficient loading and processing of neuroimaging data.

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Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: ANFIS controller structure with two inputs .

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

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Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: ANFIS controller's input and output.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

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Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: IFOC speed control of induction motor using ANFIS control strategy.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

Techniques: Control

Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: Proposed ANFIS controller's architecture.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

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Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: ANFIS testing using checking data.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

Techniques:

Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: Details of the proposed ANFIS.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

Techniques:

Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: FPI, IPI, and ANFIS controller responses without load torque.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

Techniques:

Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: Performance comparisons of controllers without load torque.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

Techniques: Comparison

Journal: Heliyon

Article Title: Integer PI, fractional PI and fractional PI data trained ANFIS speed controllers for indirect field oriented control of induction motor

doi: 10.1016/j.heliyon.2024.e37822

Figure Lengend Snippet: Controllers response for rotor resistance variation (a) ANFIS, (b) FPI, (c) IPI.

Article Snippet: Then the first step is to import the training and checking data pairs into the MATLAB toolbox's anfis GUI, the second stage is to determine the number and type of input and output membership functions as well as the amount of epoch numbers (initialization).

Techniques: