通过迭代的自适应识别测试获取识别公式中的权重系数，利用该公式在自动系统中实现纤维的无人工干预识别，并达到了预期的苎麻和棉纤维识别率。
The final identification equations were utilized in the system and the overall tolerance for false identification of cotton or ramie fibers was controlled in an anticipated scope.
生物免疫是一个高度复杂的自适应系统，具有学习、记忆和模式识别的能力。
Biological Immune is a highly complexity and self-adaptive system with capability of learning, memory acquisition, pattern recognition and so on.
数据融合方法采用经典的自适应加权融合估计算法，配合智能判别技术，增强了火灾特征识别的可靠性。
Combined with intelligent recognition technology, data fusion technology adopts the classical self-adapting weighting fusion algorithm to increase the reliability of fire characteristics recognition.
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