comparative performance
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Desalination ◽  
2022 ◽  
Vol 525 ◽  
pp. 115474
Sebastian A. Romo ◽  
Nicholas Mattise ◽  
Jelena Srebric

2022 ◽  
Vol 48 ◽  
pp. 103871
Priyanka Lamba ◽  
Parul Singh ◽  
Pankaj Singh ◽  
Pushpa Singh ◽  
Bharti ◽  

Radouane Majdoul ◽  
Abdelwahed Touati ◽  
Abderrahmane Ouchatti ◽  
Abderrahim Taouni ◽  
Elhassane Abdelmounim

<p><span>In the present paper, an efficient and performant nonlinear regulator is designed for the control of the pulse width modulation (PWM) voltage inverter that can be used in a standalone photovoltaic microgrid. The main objective of our control is to produce a sinusoidal voltage output signal with amplitude and frequency that are fixed by the reference signal for different loads including linear or nonlinear types. A comparative performance study of controllers based on linear and non-linear techniques such as backstepping, sliding mode, and proportional integral derivative (PID) is developed to ensure the best choice among these three types of controllers. The performance of the system is investigated and compared under various operating conditions by simulations in the MATLAB/Simulink environment to demonstrate the effectiveness of the control methods. Our investigation shows that the backstepping controller can give better performance than the sliding mode and PID controllers. The accuracy and efficiency of the proposed backstepping controller are verified experimentally in terms of tracking objectives.</span></p>

S Raja Rajeswari ◽  
Dr. A. John Sanjeev Kumar

Opinion mining has become a major part in today's economy. People would want to know more about a product and the customers opinion before buying it. Companies would also want to know the opinions of the customers. Therefore, analyzing the customer’s opinion is important. A new customer would consider a product as good by analyzing the opinions of other customers. The opinions are collected from various areas, which include blogs, web forums, and product review sites. Classifying these large set of opinions requires a good classifier. In view of this, a comparative study of three classification techniques - Naive Bayes classifier with Kernel Density Estimation (KDE), Support Vector Machine (SVM), Decision Tree and KNN was made. To evaluate the classifier accuracy, precision, recall and F-measure techniques are used. Experimental results show that the Naive Bayes with Kernel Density Estimation (KDE) classifier achieved higher accuracy among others.

2022 ◽  
Vol 21 (1) ◽  
Corine Ngufor ◽  
Josias Fagbohoun ◽  
Abel Agbevo ◽  
Hanafy Ismail ◽  
Joseph D. Challenger ◽  

Abstract Background Pyrethroid-PBO nets were conditionally recommended for control of malaria transmitted by mosquitoes with oxidase-based pyrethroid-resistance based on epidemiological evidence of additional protective effect with Olyset Plus compared to a pyrethroid-only net (Olyset Net). Entomological studies can be used to assess the comparative performance of other brands of pyrethroid-PBO ITNs to Olyset Plus. Methods An experimental hut trial was performed in Cové, Benin to compare PermaNet 3.0 (deltamethrin plus PBO on roof panel only) to Olyset Plus (permethrin plus PBO on all panels) against wild pyrethroid-resistant Anopheles gambiae sensu lato (s.l.) following World Health Organization (WHO) guidelines. Both nets were tested unwashed and after 20 standardized washes compared to Olyset Net. Laboratory bioassays were also performed to help explain findings in the experimental huts. Results With unwashed nets, mosquito mortality was higher in huts with PermaNet 3.0 compared to Olyset Plus (41% vs. 28%, P < 0.001). After 20 washes, mortality declined significantly with PermaNet 3.0 (41% unwashed vs. 17% after washing P < 0.001), but not with Olyset Plus (28% unwashed vs. 24% after washing P = 0.433); Olyset Plus induced significantly higher mortality than PermaNet 3.0 and Olyset Net after 20 washes. PermaNet 3.0 showed a higher wash retention of PBO compared to Olyset Plus. A non-inferiority analysis performed with data from unwashed and washed nets together using a margin recommended by the WHO, showed that PermaNet 3.0 was non-inferior to Olyset Plus in terms of mosquito mortality (25% with Olyset Plus vs. 27% with PermaNet 3.0, OR = 1.528, 95%CI = 1.02–2.29) but not in reducing mosquito feeding (25% with Olyset Plus vs. 30% with PermaNet 3.0, OR = 1.192, 95%CI = 0.77–1.84). Both pyrethroid-PBO nets were superior to Olyset Net. Conclusion Olyset Plus outperformed PermaNet 3.0 in terms of its ability to cause greater margins of improved mosquito mortality compared to a standard pyrethroid net, after multiple standardized washes. However, using a margin of non-inferiority defined by the WHO, PermaNet 3.0 was non-inferior to Olyset Plus in inducing mosquito mortality. Considering the low levels of mortality observed and increasing pyrethroid-resistance in West Africa, it is unclear whether either of these nets would demonstrate the same epidemiological impact observed in community trials in East Africa.

2022 ◽  
Vol 9 (12) ◽  
pp. 222-241
G. A Eriyeva ◽  
C.N. Okoli

This paper focused on comparative performance of GARCH models, ascertaining the best model fit, estimating the parameters and making prediction from optimal model. The study used UBA daily stock exchange prices sourced from the official websites of,on the daily basis of the Nigeria stock exchange rate over a period of ten years from 06/06/2012 – 04/06/2021. Five GARCH models (SGARCH, GJRGARCH or TGARCH, EGARCH, APGARCH and IGARCH) were fitted to the secondary data set of the Nigerian Stock exchange market for the period of June 2012- June 2021 and the results of the findings were obtained. The AIC results were SGARCH (1,1) (-6.1784), GJRGARCH (1,1) (-6.1778), EGARCH (1,1) (-6.1714) , APGARCH (1,1) (-6.1245) and IGARCH(1,1)  with the value of AIC -6.1793. The EGARCH (1, 1) was found to be the optimal model with AIC value of -6.1714.   The further findings indicated volatility clustering and leverage effect. The result of the analysis equally showed parameter estimates of the EGARCH (1,1) model and all the parameters were significant including mean and alpha. Prediction using the optimal model was made with an initial out of sample of 200 and n ahead of 200 with predicted values within the 95% confidence interval resulting there is no sign of volatility and clustering.  Based on the findings of the study, other time series packages should be compared with GARCH models, data should be making available for easy access and investors should be encouraged to invest in United Bank for Africa (UBA, Nigeria).

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