Research on Algorithms of Dietary Collocations(Recommendation)

Aiming at the problems of health and diet in modern life. The dietary habits, working and sleeping patterns of modern people and their effects on health were analyzed. Starting with the "Preventive Treatment of Diseases" of Traditional Chinese Medicine, Then the importance of introducing TCM dietary therapy and arranging diet reasonably is discussed. And from the traditional dietary collocation practices, Researchers found and put forward the urgent problems to be solved. By digitalizing and informationizing the traditional methods, Researchers can solve the problems encountered by the traditional methods and make up for their shortcomings. The new solution divides the problem into three parts, and the corresponding research is also divided into three core algorithm modules, In turn, the core algorithm of human body feature information classification, the core algorithm of dietary therapy collocation and the core algorithm of dietary recommendation. Using K-Nearest Neighbor (KNN) algorithm, Depending on the data of the unique characteristics and functions of the human body, For example, physical fitness, fat, bone mineral density and other characteristics. In order to classify the human body data with diversity and complexity of information, so as to obtain specific physical types. Then, according to the nine general qualities and sub-health syndrome commonly referred to in traditional Chinese medicine, the types of human symptoms can be calculated. Dietotherapy collocation algorithm is based on all kinds of symptoms with dietotherapy conditions, which are generally accepted in traditional Chinese medicine, According to the type of human body constitution and the type of human body symptoms, Combined with food which with therapeutic effect, Combinatorial algorithm is used to generate a complete diet plan. Dietary recommendation algorithm is based on their own physical needs and personal preferences, combined with location, climate, season, temperature, humidity, air quality, air pressure, combined with weight factors and combination recommendation algorithm to generate recommended diet.