Open AccessPredicting Crisis in Global Trade Network: An Enhanced Decision Tree Based Methods
Author(s) -
Vashisht Marhwal,
Piyush Bamel,
Tanay Agarwal
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.a1059.1291s319
Subject(s) - centrality , social network analysis , natural disaster , computer science , financial crisis , decision tree , network analysis , international trade , business , economics , artificial intelligence , geography , engineering , social media , statistics , macroeconomics , mathematics , world wide web , meteorology , electrical engineering
International Trade Relations represent a natural Social Information Network that has been extensively analyzed for various purposes like monitoring the global economy. The aim is to use the Global Trade Network to predict the occurrence of natural disasters or financial crisis based on the fact that the trade relations tax a hit in their patterns. The Global Network compromises of Export-Import Relations between the countries in the form of a Weighted Social Network. Predicting Trade relations help us effectively predict any future crisis and prepare for the same. An analysis of the Global Trade Network would discuss the centrality measures and Degree strengths. Using a list of crises which has occurred in the past and with the help of an efficient Machine Learning Model and Sampling Technique the aim is to improve the accuracy and precision of our prediction and discuss the implications on the network.