Ion criterion (BIC) is applied to quantify the magnitude of ond, the Bayesian information and facts criterion (BIC) is applied towards the coefficients within the estimated input utput neurons inside the Bismuth subcitrate (potassium) Anti-infection hidden layer, which impacts quantify the magnitude of neurons in the hidden layer, which impacts the coefficientscase study are presented to verify equations. equations. Finally, the results in the inside the estimated input utput the effectiveness of Ultimately, the results from the caseNN-based presented to verify the effectiveness with the proposed the proposed study are estimation approach compared with the LSM-based RSM. The graphical overview from the proposed NN-based estimation process overview NN-based estimation method compared using the LSM-based RSM. The graphicalis demonstrated in Figure 1. on the proposed NN-based estimation approach is demonstrated in Figure 1.Figure 1. Proposed feed-forward NN-based estimation Figure 1. Proposed feed-forward NN-based estimation procedure. process.The remainderThethe study is of your study follows: Section follows: Section two introduces the of remainder organized as is organized as two introduces the convenconventional LSM-based RSM. the functional-link-NN-based dual-response dualtional LSM-based RSM. Section three describes Section three describes the functional-link-NN-based response estimation model. Section four explains the estimation model. Section 4 explains the outputs generatedoutputs generated by the proposed NNby the proposed NN-based primarily based estimation strategy and analyzes the LSM-based RSM determined by the outcomes of your estimation system and analyzes the LSM-based RSM according to the outcomes in the case study. case study. Finally, Section 5 concludes the study and describes additional studies. Finally, Section five concludes the study and describes further studies. two. Traditional LSM-Based RSM2. Traditional LSM-Based RSM The RSM was very first introduced by Box and Wilson [35] and is made use of to model empiricalThe RSM was very first introduced by output and input variables. Myers [36] empirical Box and Wilson [35] and is utilised to model and Khuri and relationships involving relationships among output and input variables. Myers [36] and Khuri and MukhopadMukhopadhyay [37] present insightful commentaries around the diverse improvement hyay [37] present insightful commentariesthe the various improvement phases of difficult or is phases with the RSM. When on exact functional relationship is extremely the RSM. When the exactPhenmedipham Purity & Documentation unknown, the traditional LSM is employed to estimate the input esponse functional functional partnership is extremely difficult or is unknown, the traditional LSM is used torelationships in the output [38,39]. Generally, the estimated output [38,39]. estimate the input esponse functional relationships with the second-order response Normally, the surface functions are applied to analyze RD difficulties. The utilised to analyze RD estimated second-order response surface functions are estimated process mean and challenges. Thestandard deviation functionsand common deviation functions proposed by follows: estimated method mean proposed by Vining and Myers [8] may be defined as Vining and Myers [8] may be defined as follows: ^ ^ ^ 2 ^ LSM (x) = 0 + i xi + i xi +i =1 i =1 p p^ ij xi x j i=1 ijp j =pp(1)^ ^ ^ 2 ^ LSM (x) = 0 + i xi + i xi +i =1 i =pp^ ij xi x j i=1 ijj =p(2)Appl. Sci. 2021, 11, x FOR PEER REVIEW4 ofAppl. Sci. 2021, 11,four of() = +++(1)^ ^ where x = x1 , . . . , xi , . . . , x j , . . . , x p can be a vector of input variables, and and will be the () = m.
