Abstract

Business plays a pivotal role for the development of human civilization as well as change of the status of the country in this whole universe. To compare and compute the export trend for any organization or a country is an indispensable for numerous intelligent systems to measure the national and international gain or loss for developing countries as well as for developed countries. The main purpose of this research is to develop a dynamic business prediction model for person, organization, Institute, Ministry of Commerce, Ministry of Finance ,Ministry of Economics, Prime Minister office and last but not least for whole world to predict the exact demand for exportable products and formulate export policy. Bangladesh Export Promotion Bureau (BEPB) helped us by providing the valuable data set and information. In this research activities we have had first classify the data by using Support Vector Machine (SVM), a latest data classification technique in the field of data processing. SVM reduce the redundant data from vast amount of data. After getting processed data we have used first-order logic (FL) to build a knowledgebase which will work as background knowledge for our computation. Finally Bayes’ Network (BN) has used to perform the proper prediction by using the knowledge base information. Based on the result of BN, we have made a list of emerging products those have major impact on the prosperity of the country or organization.

How to Cite
KAMAL, SONIA FARHANA NIMMY, MOHD. KAMAL UDDIN, Md.Sarwar. Automated Listing for Exportable Products. Global Journal of Computer Science and Technology, [S.l.], may 2012. ISSN 0975-4172. Available at: <https://computerresearch.org/index.php/computer/article/view/498>. Date accessed: 24 jan. 2021.