MFF optimizes the fitness function in GEP by special approach called probability correlation factor, which increases the precision by 27%.
MFF中采用了有特色的概率相关系数对GEP中的适应度函数进行优化，使得精度提高了27%。
Because of a particular character of self-learned, this new method increases the precision of detecting and locating, and reduces the incidence of false alarms.
这种方法基于统计分析的原理，并将模式识别加入其中，形成一套独特的自学习方法，提高了泄漏检测和定位的精确度，并有效降低了误报警率。
The utility model effectively avoids false operation, increases the precision and the reliability of the measurement by the sensor, and can be used for the fields of medical detection, etc.
本实用新型可有效的避免误操作，提高传感器测量的精度和可靠性，可广泛的应用于医疗检测等领域。
应用推荐