Artificial Neural Network Based Efficiency Prediction and Its Impact on Dye Synthesized Solar Cell
S. K. Kharade1, R. K. Kamat2, K. G. Kharade3, R. S. Kamath4, S. A. Shinde5
1S. K. Kharade*, Department of Mathematics, Shivaji University, Kolhapur, India.
2R. K. Kamat, Department of Computer Science, Shivaji University, Kolhapur, India.
3K. G. Kharade, Department of Computer Science, Shivaji University, Kolhapur, India.
4R. S. Kamath, Department of Computer Studies, Chatrapati Shahu Institute of Business Education and Research, Kolhapur, India.
5S. A. Shinde, Department of Electronics, Shivaji University, Kolhapur, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 2696-2699 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6309018520/2020©BEIESP | DOI: 10.35940/ijrte.E6309.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Alongside numerous different parameters, the general proficiency of pv element relies upon temperature of cell, which, depends on different ecological variables. Natural conditions, for instance, speed of wind solar irradiance, and wind course and in particular, the temperature around the cell influences cells exhibition. Also the climate forecast and meteorology is an exceptionally perplexing and loose science, ongoing exploration exercises with counterfeit neural system (ANN) have indicated that it has ground-breaking design arrangement and example acknowledgment capacities and that can be utilized as a device to obtain a sensible precise expectation of climate designs. This paper focuses on an application of Artificial Neural Network (ANN) to estimate the efficiency of Dye Synthesized solar cell. During writing of this research paper, development last ten years has been considered. An Artificial Neural Network model based on Multilayer Perceptron concept has been developed and trained using Levenberg-Marquardt feed-forward algorithm for prediction. The model was tested and trained using ten years of efficiency data of Dye synthesized solar cell. The exactness of the model was determined on premise of Mean Square Error. The result shows that Neural Network can be used for efficiency prediction successfully.
Keywords: ANN, Dye Synthesized Solar Cell, Efficiency Prediction.
Scope of the Article: Artificial Intelligence.