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Standard <t>ANFIS</t> 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 <t>MATLAB</t> 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.
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MathWorks Inc anfis function genfis1
Standard <t>ANFIS</t> 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 <t>MATLAB</t> 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.
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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.

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