In recent years, with the large increase in the number of motor vehicles in colleges and universities and the lag in campus planning, the relative shortage of parking spaces on campus has become increasingly serious. ...In recent years, with the large increase in the number of motor vehicles in colleges and universities and the lag in campus planning, the relative shortage of parking spaces on campus has become increasingly serious. Taking Baoding College as an example, this article analyzes the current situation of static traffic on campus and finds out the problem of parking on campus through questionnaire surveys and field surveys. Analyze the growth trend of the number of motor vehicles based on the data, use the GM (1, 1) model and the linear fitting model to predict the number of motor vehicles in the future, and determine the size and layout of the parking lot based on the campus size, functional zoning, and road layout. The big campus-based parking system planning method based on big data can effectively solve the problems of small sample data, low accuracy, and poor timeliness of traditional methods, which improves the practicability and scientificity of planning results.展开更多
针对苹果大小分级图像处理过程中苹果直径像素数与实际直径映射不准确的问题,设计了一种基于线性拟合模型的苹果大小分级方法。将图像色彩表达方式由RGB(red green blue,红、绿、蓝)颜色空间转换到HSV(hue saturation value,色调、饱和...针对苹果大小分级图像处理过程中苹果直径像素数与实际直径映射不准确的问题,设计了一种基于线性拟合模型的苹果大小分级方法。将图像色彩表达方式由RGB(red green blue,红、绿、蓝)颜色空间转换到HSV(hue saturation value,色调、饱和度、明度)颜色空间,利用H、S、V三项阈值从图像中分割出苹果区域作为苹果最大横切面,提取苹果横切面轮廓并过滤图像中噪声轮廓。用最小外接圆法求苹果轮廓最小外接圆,其直径作为苹果直径。按苹果实际直径大小的分布规律从总体样本中选取数据作为建模集,计算建模集中苹果直径像素数,用最小二乘法将直径像素数与实际直径拟合为线性模型。将直径像素数输入模型,计算得到的苹果直径数值用于大小分级。用75组数据测试模型,得到92%的总体分级准确率及0.56 mm的平均测量误差。该方法分级准确率高,直径测量误差小,能满足苹果产后分级需求。展开更多
文摘In recent years, with the large increase in the number of motor vehicles in colleges and universities and the lag in campus planning, the relative shortage of parking spaces on campus has become increasingly serious. Taking Baoding College as an example, this article analyzes the current situation of static traffic on campus and finds out the problem of parking on campus through questionnaire surveys and field surveys. Analyze the growth trend of the number of motor vehicles based on the data, use the GM (1, 1) model and the linear fitting model to predict the number of motor vehicles in the future, and determine the size and layout of the parking lot based on the campus size, functional zoning, and road layout. The big campus-based parking system planning method based on big data can effectively solve the problems of small sample data, low accuracy, and poor timeliness of traditional methods, which improves the practicability and scientificity of planning results.
