An adaptive method for the performance evaluation of a concentrating solar power system using NN and CS Online publication date: Tue, 23-May-2017
by Venbakkam Sendamaraikannan Srinivasan; S.Srinivasa Rao Madane
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 12, No. 2, 2017
Abstract: In this paper, the proposed adaptive technique is used for improving the performance of the concentrating solar power (CSP) system. Initially, the neural network (NN) generated the dataset based on the reference signal and the normal signal. Then the cuckoo search (CS) algorithm improved the effectiveness of the proposed algorithm and the weight and the biases can optimised. The novelty of this paper is to evaluate the performance of the CSP system and improve the effectiveness also of gathered maximum energy. Thereafter, to support the accuracy and efficiency of the system, parameters such as regression coefficient, root mean square error (RMSE) value and error variation are estimated. The proposed optimisation process is implemented in MATLAB/Simulink platform and also the result is estimated and analysed based on the error parameters of the CSP system. Based on these, the proposed optimisation process is evaluated and compared with other traditional methods.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook