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Model fitting results showing the comparison between the predicted TB incidence (solid curve) and the normalized observed data (dots). The model was calibrated by minimizing the sum of squared errors (SSE) between the model output and the data using a least-squares approach. The system of ordinary differential equations was solved using MATLAB's ode45 solver, and parameter optimization was carried out using MATLAB's <t>fminsearch</t> function based on the Nelder–Mead simplex method.
Fminsearch Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/fminsearch function/product/MathWorks Inc
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fminsearch function - by Bioz Stars, 2026-03
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matlab function fminsearch  (MathWorks Inc)
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Model fitting results showing the comparison between the predicted TB incidence (solid curve) and the normalized observed data (dots). The model was calibrated by minimizing the sum of squared errors (SSE) between the model output and the data using a least-squares approach. The system of ordinary differential equations was solved using MATLAB's ode45 solver, and parameter optimization was carried out using MATLAB's <t>fminsearch</t> function based on the Nelder–Mead simplex method.
Matlab Function Fminsearch, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab function fminsearch/product/MathWorks Inc
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matlab function fminsearch - by Bioz Stars, 2026-03
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bounded fminsearch function  (MathWorks Inc)
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Model fitting results showing the comparison between the predicted TB incidence (solid curve) and the normalized observed data (dots). The model was calibrated by minimizing the sum of squared errors (SSE) between the model output and the data using a least-squares approach. The system of ordinary differential equations was solved using MATLAB's ode45 solver, and parameter optimization was carried out using MATLAB's <t>fminsearch</t> function based on the Nelder–Mead simplex method.
Bounded Fminsearch Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/bounded fminsearch function/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
bounded fminsearch function - by Bioz Stars, 2026-03
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non-linear optimization function fminsearch  (MathWorks Inc)
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MathWorks Inc non-linear optimization function fminsearch
Model fitting results showing the comparison between the predicted TB incidence (solid curve) and the normalized observed data (dots). The model was calibrated by minimizing the sum of squared errors (SSE) between the model output and the data using a least-squares approach. The system of ordinary differential equations was solved using MATLAB's ode45 solver, and parameter optimization was carried out using MATLAB's <t>fminsearch</t> function based on the Nelder–Mead simplex method.
Non Linear Optimization Function Fminsearch, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/non-linear optimization function fminsearch/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
non-linear optimization function fminsearch - by Bioz Stars, 2026-03
90/100 stars
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Model fitting results showing the comparison between the predicted TB incidence (solid curve) and the normalized observed data (dots). The model was calibrated by minimizing the sum of squared errors (SSE) between the model output and the data using a least-squares approach. The system of ordinary differential equations was solved using MATLAB's ode45 solver, and parameter optimization was carried out using MATLAB's fminsearch function based on the Nelder–Mead simplex method.

Journal: Infectious Disease Modelling

Article Title: Modelling the potential impact of TB-funded prevention programs on the transmission dynamics of TB

doi: 10.1016/j.idm.2025.05.010

Figure Lengend Snippet: Model fitting results showing the comparison between the predicted TB incidence (solid curve) and the normalized observed data (dots). The model was calibrated by minimizing the sum of squared errors (SSE) between the model output and the data using a least-squares approach. The system of ordinary differential equations was solved using MATLAB's ode45 solver, and parameter optimization was carried out using MATLAB's fminsearch function based on the Nelder–Mead simplex method.

Article Snippet: The system of ordinary differential equations was solved using MATLAB's ode45 solver, and parameter optimization was carried out using MATLAB's fminsearch function based on the Nelder–Mead simplex method.

Techniques: Comparison