Open AccessPredictions of World Population Life Expectancy Using Cyclical Order Weight / Bias
Author(s) -
Mhd. Khafiroh Zamzamy Sormin,
Poltak Sihombing,
Andin Vita Amalia,
Anjar Wanto,
Dedy Hartama,
Defri Muhammad Chan
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1255/1/012017
Subject(s) - life expectancy , population , government (linguistics) , welfare , population health , estimation , population ageing , expectancy theory , economics , demographic economics , demography , sociology , linguistics , philosophy , management , market economy
Life expectancy is the average number of years of life that is still lived by someone who has reached a certain age. Life Expectancy is a tool to evaluate government performance in improving the welfare of the population in general and improving health status in particular. The purpose of this paper is to estimate the life expectancy of the world population so that the government has a benchmark in determining policies to further improve the health and health of the people in their respective countries. The estimation stated in this paper will use the Cyclical Order Weight Neural Network method. The data used in this paper is the number of world population expectations. Data sources come from the United Nations: “World Population Prospect: The 2010 Revision Population Database”. The results of this study are expected to be a reference for the governments of each country to pay more attention to the level of health and welfare of its population so that the life expectancy of the population will be higher. This study uses 5 architectural models. Of these 5 models, the best architectural model is 3-5-10-1 with an accuracy of 97% and an MSE value of 0,0008358919.