Simulation for response surface in the HPLC optimization method development using artificial intelligence models: A data-driven approach
In this paper, three different data-driven algorithms were employed including two nonlinear
models (Artificial neural network (ANN) and Adaptive neuro-fuzzy inference system (ANFIS))
and a classical linear model (Multilinear regression analysis (MLR)) for the simulation of
response surface for methyclothiazide (M) and amiloride (A) considered as (K'or k) modeling
in HPCL using pH and composition of mobile phase (methanol) as the corresponding input
variables. The experimental and simulated results were evaluated based on five different …
models (Artificial neural network (ANN) and Adaptive neuro-fuzzy inference system (ANFIS))
and a classical linear model (Multilinear regression analysis (MLR)) for the simulation of
response surface for methyclothiazide (M) and amiloride (A) considered as (K'or k) modeling
in HPCL using pH and composition of mobile phase (methanol) as the corresponding input
variables. The experimental and simulated results were evaluated based on five different …
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