A healthy nutrition suggestion model for indian women sports players & active youth using long short-term memory

IF 0.9 Q4 TELECOMMUNICATIONS
Keerthana Ramaraj, Valliammal Narayan, Thookanayakanpalayam Thyagarajan Dhivyaprabha, Parthasarathy Subashini
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引用次数: 0

Abstract

Sports nutrition is the balanced diet or diet chart that helps to improve performance of sports persons. It is globally accepted that Indian foods are rich in nutrition. It is greatly preferred by yogis, gurus and dieticians to intake Indian foods in order to maintain a wellness and healthy lifestyle. Smart watches, wearable devices, mobile applications and digital portals are available to suggest foods to the sports persons. But software application based on Indian foods specifically for women athletes are not exists so far. In this paper an intelligent food recommendation system based on Long Short-Term Memory (LSTM) and LSTM with GRU is proposed to suggest meals for women athletes. LSTM has connections and it processes the entire sequence of data thus, it is week suitable for suggestion models. The performance of the model is validated using evaluation metrices and the result demonstrate its effectiveness.

利用长短期记忆为印度女运动员和活跃青年提供健康营养建议模型
运动营养是指有助于提高运动员成绩的均衡饮食或饮食图表。全球公认印度食品营养丰富。瑜伽师、大师和营养师都非常喜欢摄入印度食品,以保持健康的生活方式。智能手表、可穿戴设备、移动应用程序和数字门户网站都可以向运动者推荐食物。但目前还没有专门针对女性运动员的印度食品应用软件。本文提出了一种基于长短期记忆(LSTM)和带有 GRU 的 LSTM 的智能食物推荐系统,为女运动员推荐膳食。LSTM 具有连接性,能处理整个数据序列,因此适合用于建议模型。使用评估指标对模型的性能进行了验证,结果证明了其有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
3.10
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