Recommended System for Controlling Malnutrition in Iranian Children 6 to 12 Years Old using Machine Learning Algorithms

Document Type : Original Article

Authors

1 M.Sc. in Information Technology Engineering, Ghiaseddin Jamshid Kashani University, Abyek, Iran

2 Faculty Member of Computer Department, Faculty of Computer, Eyvanekey Non-Profit University, Semnan

Abstract

Iran is facing low levels of all three types of children's nutrition like nutrient and micronutrients deficiency and overeating. The most common nutritional problems and child deaths are vitamin deficiencies and food quality. The purpose of this research is to plan food recommended system to control malnutrition in children 6 to 12 years old using hybrid machine learning algorithms.  The results of this research are applicable in terms of target research. In terms of the implementation method, it is a descriptive survey and the process of gathering information is quantitative data. The dataset used includes 1001 data points collected from the health centers of Mianeh city located in East Azerbaijan in Iran from the integrated apple web system. In this research, the Python programming language has been used to analyze the child nutrition dataset, and AdaBoost and Decision Tree hybrid algorithms have been utilized for the child nutrients recommender system. We concluded that the number of meal features using the Decision Tree algorithm with 98.5% accuracy was more important than other nutritional features of children in recognizing malnutrition in them. From a review of 1001 data into the child nutrition dataset, 807 children are underweight and malnourished, 170 children are normal weight, 20 children are obese and four children are overweight. Therefore, the high exactness of hybrid algorithms in these studies has been able to have a high alignment with the opinion of nutritionists from 2019 to 2020.

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Main Subjects

References

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Shahla Najaflou was born in 1990 in Mianeh, Iran. She received her B.Sc. in Computer Engineering - Software from Islamic Azad University, Mianeh Branch in 2013 and M.Sc. in Information Technology Engineering (E-Commerce) from the University of Ghiaseddin Jamshid Kashani Abyek (Qazvin Province, Iran), in 2019. Her master's thesis is in the field of intelligent decision support systems for controlling nutrition children 6 to 12 years ago. Her interests include data mining, machine learning.

 

 Mohammad Rabiei was born in 1983 in Karaj, Iran. He received his B.Sc. In Computer Engineering - Hardware from Islamic Azad University in 2006 and received the M.Sc. Degree at the Industrial University of Science and Technology (IUST), Iran, in March 2009 with the highest mark by discussing a thesis concerning the “Human information literacy and e-readiness”. Also, he received his Ph.D. in Information Technology in Industrial Engineering (Robotics) from Udine University, Italy in 2015 and a Ph.D. specializing in ontology in robotics from the University of Leuven, Belgium in 2016. He has been an assistant professor and faculty member at the Department of Computer Engineering, University of Eyvanekey, and also an assistant professor at the University of Ghiaseddin Jamshid Kashani Abyek since the year 2016 to the present. His research interests include image processing, machine vision, natural language processing, machine learning, deep learning, Implementing robotics projects and industrial robots using interdisciplinary science and Implementing new business intelligence techniques in public and private organizations, Managing customer relationship and loyalty and e-commerce, Implement social networks in e-marketing and replace this advertising strategy.

 

 

 

International Journal of Web Research
Volume 4, Issue 1
Winter-Spring
June 2021
Pages 27-33

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