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Institution

Vignan University

EducationGuntur, Andhra Pradesh, India
About: Vignan University is a education organization based out in Guntur, Andhra Pradesh, India. It is known for research contribution in the topics: Control theory & CMOS. The organization has 1138 authors who have published 1381 publications receiving 7798 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the application of generalized wavelet neural network (GWNN) models corresponding to the FAO-56 Penman Monteith (FAO56 PM), Turc, and Hargreaves (HG) methods for estimating daily reference evapotranspiration (ETo) was studied.
Abstract: This study focuses on the application of generalized wavelet neural network (GWNN) models corresponding to the FAO-56 Penman Monteith (FAO-56 PM), Turc, and Hargreaves (HG) methods for estimating daily reference evapotranspiration (ETo). The daily pooled climate data from 15 different locations under 4 different agro-ecological regions (AERs: semi-arid, arid, sub-humid, and humid) in India are used as an input to GWNN models. The inputs include three combinations of climate data (minimum and maximum air temperatures, minimum and maximum relative humidity, wind speed, and solar radiation) and the target consists of the FAO-56 PM estimated ETo. Further, the GWNN models were applied to 15 individual model development locations and 10 different model testing locations to test the generalizing capability. Comparison of developed GWNN models was made with the classic generalized artificial neural network (GANN), generalized linear regression (GLR), generalized wavelet regression (GWR), and corresponding...

13 citations

Journal ArticleDOI
29 Jun 2017
TL;DR: This study clearly shows that both RSM and ANN models provided desired predictions, however, compared with RSM, the ANN model gave a better prediction for the production of lactase.
Abstract: Modeling and optimization were performed to enhance production of lactase through submerged fermentation by Bacillus subtilis VUVD001 using artificial neural networks (ANN) and response surface methodology (RSM). The effect of process parameters namely temperature (°C), pH, and incubation time (h) and their combinational interactions on production was studied in shake flask culture by Box–Behnken design. The model was validated by conducting an experiment at optimized process variables which gave the maximum lactase activity of 91.32 U/ml. Compared to traditional activity, 3.48-folds improved production was obtained after RSM optimization. This study clearly shows that both RSM and ANN models provided desired predictions. However, compared with RSM (R 2 = 0.9496), the ANN model (R 2 = 0.99456) gave a better prediction for the production of lactase.

13 citations

Proceedings ArticleDOI
14 Nov 2014
TL;DR: The total influence of all the weather parameters was significant on thrips and while it was non-significant on jassid, aphids and whitefly, the regression equations were developed for cotton pest using multiple linear regression models.
Abstract: The research work is focused to study the influence of weather parameters on the incidence of pests on cotton from the period 2006 to 2010 at Acharya N. G. Ranga Agricultural University, Lam farm, Guntur. Multiple Linear Regression (REG) and Generalized Linear Model (GLM) techniques are used to analyze the pooled pest's data statistically along with weather parameters by SAS (Statistical Analysis System). The regression equations were developed for cotton pest using multiple linear regression models. The comparative study has been made for identifying the coefficient of determination (R2) which remains same for all kinds of pests when both REG procedure and GLM procedure models were fitted. The total influence of all the weather parameters was significant on thrips and while it was non-significant on jassid, aphids and whitefly.

13 citations

Book ChapterDOI
20 Sep 2019
TL;DR: The result of review work indicates that the TOPSIS method can be applied to solve multi objective optimization problems and are also applicable to solve process parameter optimization of any machining process.
Abstract: Optimum process parameters in a machining process leads to better machining performance. These optimum process parameters can be selected from a number of alternatives with the help of Multi Criteria Decision Making (MCDM) methods. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of the MCDM methods, which is used to select optimum combination of process parameters using relative closeness value to the ideal solution. In this study, complete review is done on TOPSIS method for the purpose of optimization of process parameters in manufacturing environment. The result of review work indicates that the TOPSIS method can be applied to solve multi objective optimization problems and are also applicable to solve process parameter optimization of any machining process.

13 citations

Journal ArticleDOI
TL;DR: In this article, a stability-indicating method has been developed to determine the impurities in sacubitril (SCB) and valsartan (VLS) tablet dosage forms and perform robustness studies using the design of experiments approach.
Abstract: According to current regulatory guidelines, a stability-indicating method has been developed to determine the impurities in sacubitril (SCB) and valsartan (VLS) tablet dosage forms and perform robustness studies using the design of experiments approach. The present study was initiated to understand quality target product profile, analytical target profile, and risk assessment for method variables that affect the method response. A reversed-phase-HPLC system was equipped with a Phenomenex Gemini-NX C18 column (150 × 4.6 mm, 3 μm) and a photo diode array detector. A gradient mobile phase was used in this research work. The detection was performed at 254 nm; the flow rate was 1.5 mL/min, and the column temperature was maintained at 30°C. The proposed method was validated per the International Council for Harmonisation Q2 (R1) guidelines. The coefficient of correlation was >0.999 for all impurities. The limits of detection and quantification were evaluated for SCB, VLS, and all impurities. The precision and accuracy were obtained for SCB, VLS, and their related impurities. Intra- and inter-day relative standard deviation values were less than 10.0%, and the recoveries of impurities varied between 90.0 and 115.0%. Based on the validation results, the proposed DoE method can estimate SCB and VLS impurities in the finished dosage form.

13 citations


Authors
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202322
202231
2021352
2020254
2019250
2018159