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Prevention of Obesity using Artificial Intelligence Techniques

Journal Name:

  • International Journal of Science and Engineering Investigations

Publication Year:

  • 2012

Key Words:

Author Name
Abstract (2. Language): 
Obesity has many causes. The reasons for the imbalance between calorie intake and consumption vary by individual. Age, Sex, Genes (GAD2), Negative Emotions, Diseases and Drugs, and environmental factors (Energy imbalance, Larger Portion sizes, High-calorie foods,) all may contribute. The most important environmental factor is lifestyle. Eating habits and activity level (Lack of physical activity) are partly learned from the people. Pregnancy: Women tend to weigh an average of 4-6 pounds more after a pregnancy than they did before. All these factors are characterized by uncertainty, vagueness and inaccuracy. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially fuzzy logic inference. The use of the fuzzy logic model, demonstrate his capability for addressing problems of uncertainty and vagueness in data. The fuzzy model was structured to prevent apparition of obesity according the conditions in inputs of system (9 factors). After the system is completely constructed, it can learn new information in both numerical and linguistic forms. Each parameter involved with a degree in membership function, a data base of the rules is established, the result to the output of the program is the degree of occurrence of moderate, severe or pathogenic obesity.
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  • 9
146-150
  • English

REFERENCES

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International Journal of Science and Engineering Investigations, Volume 1, Issue 9, October 2012 150
www.IJSEI.com Paper ISSN: 2251-8843 ID: 10912-27
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