scholarly journals Using response surface design to determine the optimal parameters of genetic algorithm and a case study

2013 ◽  
Vol 51 (17) ◽  
pp. 5039-5054 ◽  
Author(s):  
Ibrahim Kucukkoc ◽  
Aslan Deniz Karaoglan ◽  
Ramazan Yaman
2022 ◽  
Author(s):  
M.I Ejimofor ◽  
I.G Ezemagu ◽  
M.C Menkiti ◽  
V.I Ugonabo ◽  
B.U Ejimofor

Abstract The potential of gastropod shell conchiolin (GSC) (a waste product of the deprotenization stage of chitosan production) as one of the alternatives to chemical coagulants has been explored for treatment of paint industrial wastewater (PW). The accuracy of response surface design (RSD) and the precision of artificial intelligence (AI) in predicting and optimizing the process conditions were harnessed in raising experimental design matrix and response optimization, respectively for the bench scale jar test coagulation experiment. PW was characterized using American public health association (APHA) standard methods. Extraction of conchiolin was done via alkaline extraction method. PW contains 2098mg/l total suspended solid (TSS) above discharge limit (1905mg/l). Fourier transform infrared (FTIR) spectrum of GSC revealed a broad N–H wagging band at 750 – 650 cm−1 indicating the presence of secondary amine linked to the presence of protein. Turbidity removal from PW via one factor at a time (OFAT) was found to be a function of pH, GSC dosage, temperature and time. Artificial neural network (ANN) response prediction shows 92% correlation with the response surface design (RSD) experimental result. The optimal conditions obtained via genetic algorithm (GA) for the response optimization at the best pH of 4 indicate optimal turbidity removal of 98% at GSC dosage, time and temperature of 4 g, 20 min and 45oC, respectively.


2021 ◽  
pp. 1-37
Author(s):  
Ana Gabriela Sierra-Sánchez ◽  
Verónica Martínez-Miranda ◽  
Elia Alejandra Teutli-Sequeira ◽  
Ivonne Linares-Hernández ◽  
Guadalupe Vázquez-Mejía ◽  
...  

2019 ◽  
Vol 62 (5) ◽  
pp. 1251-1258 ◽  
Author(s):  
Yu Liu ◽  
Chaoyuan Wang ◽  
Zhengxiang Shi ◽  
Baoming Li

Abstract. A wash cycle using an alkaline solution with a dissolved chemical detergent is a standard clean-in-place (CIP) process for cleaning milking systems. However, long-term chemical use may corrode equipment and create difficulties in wastewater treatment. This study investigated the potential for using alkaline electrolyzed oxidizing (EO) water as an alternative to alkaline chemical detergent for removal of microorganisms and adenosine triphosphate (ATP) on milking system materials. Laboratory trials were performed based on a Box-Behnken response surface design to assess the cleaning effect of alkaline EO water on three materials typically used in milking systems: stainless steel, rubber gasket, and polyvinyl chloride (PVC) hose. Results showed that alkaline EO water treatment was generally enhanced with increased treatment time, temperature, and pH, and their interaction effects were also observed in ATP removal. However, treatment time did not have a dominant role in cleaning PVC hose. Response surface models were developed to reliably predict detected microorganisms and relative light units (RLU) on the three materials after alkaline EO water treatment. Based on the response surface models, the three parameters for alkaline EO water cleaning were optimized as treatment time of 10.0 min, temperature of 61.8°C, and pH of 12, after which microorganisms and RLU were nearly undetectable. Alkaline EO water treatment with the optimized parameters had an equivalent or better cleaning ability compared to the commercial detergent, suggesting its potential as a cleaning and bacteria removal agent for milking systems. Keywords: Alkaline electrolyzed oxidizing water, Cleanliness, Milking system, Response surface model.


Sign in / Sign up

Export Citation Format

Share Document