TY -的A2 Alzahrani穆罕默德Yahya AU -阿里,Zainab n . AU - Askerzade伊玛尼盟——Abdulwahab萨达姆PY - 2021 DA - 2021/02/26 TI -面包质量能力评估模型采用模糊加权相关向量机分类器SP - 6670316六世- 2021 AB -估计食品产品的质量是至关重要的在确定食物的属性和有效性有关发酵等生产过程。本文考虑的质量评估标准条件下的小麦面包烤。感觉数据实时采集,获得数据分析使用有效数据分析预测产品的质量。获得的数据集包括300个面包样品准备在15天内的重要物理、化学和感觉到流变措施。读的措施是通过感官收集工具和数据集。获得的数据通常是原始,因此,所需的功能是通过降维使用线性判别分析(LDA)。处理数据和属性作为分类器的输入来获取最终的评估结果。有效的模糊加权关联向量机(FWRVM)分类器模型实现这一目标。提出了质量评估模型,使用MATLAB编程实现环境所需的设置FWRVM分类器。模型的训练和测试输入数据集与数据分析的步骤。 Some state-of-the-art classifiers are also implemented to compare the evaluated performance of the proposed model. The estimation accuracy is obtained by comparing the number of correctly detected bread classes with the wrongly classified breads. The results indicate that the proposed FWRVM-based classifier estimates the quality of the breads with 96.67% accuracy, 96.687% precision, 96.6% recall, and 96.6% F-measure within 8.96726 seconds processing time which is better than the compared Support vector machine (SVM), RVM, and Deep Neural Networks (DNN) classifiers. SN - 1176-2322 UR - https://doi.org/10.1155/2021/6670316 DO - 10.1155/2021/6670316 JF - Applied Bionics and Biomechanics PB - Hindawi KW - ER -