Rough Set Based Affinity Propagation Model for Prediction of Future Gold Price in Indian Scenario
Rudra Kalyan Nayak1, N. Satya Teja2, Ramamani Tripathy3, G. Venkatesh4, I. Sai Ram5

1Dr. Rudra Kalyan Nayak*, Assoc. Professor of CSE, Koneru Lakshmaiah Education Foundation (Deemed to be University), AP, India.
2N. SatyaTeja Student of 4th Year B.Tech (CSE), Koneru Lakshmaiah Education Foundation (Deemed to be University), AP, India
3Dr. Ramamani Tripathy, Asst. Professor of MCA, United School of Business Manageent, Odisha, India.
4G. Venkatesh, Student of 4th Year B.Tech (CSE), Koneru Lakshmaiah Education Foundation (Deemed to be University), AP, India
5I. Sai Ram, Student of 4th Year B.Tech (CSE), Koneru Lakshmaiah Education Foundation (Deemed to be University), AP, India.

Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 2219-2224 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7584129219/2019©BEIESP | DOI: 10.35940/ijitee.B7584.129219
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In international market, trading of metals has played a vital role. Metal cost might affect the nation’s economy. There are so many base metals available which have been utilized in world trading for construction and manufacturing of goods. Among them gold, silver, platinum, palladium have been treated as precious metals which has economic values. Therefore today’s researchers have concentrated their investigation on metal prediction using diversified algorithms like Auto Regressive Integrated Moving Average (ARIMA), KNN (K-Nearest Neighbor),Artificial Neural Network (ANN) and Support Vector Machine (SVM) etc. In this paper our foremost objective is to predict gold price, so we put our research on this metal. In this work we have employed rough set based affinity propagation algorithm for predicting future gold price and we compared our proposed model with rough set and ARIMA model basing upon the performance measures such as root mean square error (RMSE) and mean absolute percentage error (MAPE). The experimental result shows that the proposed model outperforms rough set and ARIMA model. 
Keywords: Rough Set, Affinity Propagation, Prediction, Gold Price.
Scope of the Article: Regression and Prediction