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Analysis of Bioactive Amino Acids from Fish Hydrolysates with a New Bioinformatic Intelligent System Approach

机译:一种新型生物信息智能系统方法分析鱼肉水解物中的生物活性氨基酸

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摘要

The current economics of the fish protein industry demand rapid, accurate and expressive prediction algorithms at every step of protein production especially with the challenge of global climate change. This help to predict and analyze functional and nutritional quality then consequently control food allergies in hyper allergic patients. As, it is quite expensive and time-consuming to know these concentrations by the lab experimental tests, especially to conduct large-scale projects. Therefore, this paper introduced a new intelligent algorithm using adaptive neuro-fuzzy inference system based on whale optimization algorithm. This algorithm is used to predict the concentration levels of bioactive amino acids in fish protein hydrolysates at different times during the year. The whale optimization algorithm is used to determine the optimal parameters in adaptive neuro-fuzzy inference system. The results of proposed algorithm are compared with others and it is indicated the higher performance of the proposed algorithm.
机译:鱼蛋白行业的当前经济学要求蛋白生产的每个步骤都需要快速,准确和表达能力强的预测算法,尤其是在全球气候变化的挑战下。这有助于预测和分析功能和营养质量,从而控制高变态反应性患者的食物过敏。而且,通过实验室实验测试了解这些浓度非常昂贵且耗时,尤其是进行大规模项目时。因此,本文提出了一种基于鲸鱼优化算法的自适应神经模糊推理系统的智能算法。该算法用于预测一年中不同时间鱼蛋白水解物中生物活性氨基酸的浓度水平。鲸鱼优化算法用于确定自适应神经模糊推理系统中的最佳参数。将该算法的结果与其他算法进行了比较,表明该算法具有较高的性能。

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