利用 GPS 定位系統與開放的 OpenStreetMap,自製企業地圖。掌控企業因公外出之人、車、物..最新地理位址與動態,與客戶、廠商的相對關係。同時呈現在企業地圖中一覽無遺。全球數控系統超越硬體與網路傳輸限制,提供使用者智慧影像擷取服務,使用工業通訊協定,將遠地機器設備、資產、進行地圖定位與即時監控、採集數據。所有定位與採集監控數據回傳雲端平臺,精準掌握企業脈動。
Using the GPS positioning system and the open OpenStreetMap, self-made enterprise maps. Control the people, cars and things that the enterprise goes out on business The latest geographical address and dynamics, and the relative relationship with customers and manufacturers. At the same time, it is presented in the enterprise map at a glance. The global CNC system transcends the hardware and network transmission restrictions, provides users with intelligent image capture services, and uses industrial communication protocols to locate remote machines, assets, conduct real-time monitoring, and collect data. All positioning and collection monitoring data are transmitted back to the cloud platform to accurately grasp the enterprise pulse. (2024-03-30, Others, 0KB, 下载0次)
斯洛伐克城市、地区边界和国家边界的GeoJSON数据库。世界棱镜中的所有数据坐标...
GeoJSON database of Slovak cities, district boundaries, and country boundaries. All data coordinates in World Mercator ( EPSG 3395) (2016-04-12, Others, 2276KB, 下载0次)
使用Arduino发出包括GPS位置的莫尔斯电码消息
Use an Arduino to beep out a morse code message including GPS position (2015-05-28, Others, 4KB, 下载0次)
解释说明格洛纳斯系统的详细参数及其特性。
The detailed parameters and characteristics of the Glonas system are explained. (2019-01-07, Others, 1KB, 下载1次)
针对基于GPS／GIS的浮动车数据特点，总结其中无效的数据类型，并给出数据有效处理的方法。以支持向量机原理、交通状态预测方法为基础，分析了常用支持向量回归机、核函数及模型参数的性能，以及各核函数及模型参数对支持向量机性能的影响及作用。针对路段平均速度预测中的小样本、非线性、高维回归等特点，将支持向量回归机方法引入基于浮动车数据的路段车辆速度预测，构建了路段平均速度短时预测模型。并以杭州市某路段的实际数据为例，详细阐述了支持向量回归机预测模型的具体建模和求解过程。运用LibSVM2．84软件包，进行预测模型的参数选择、样本训练以及预测求解，并通过预测结果的对比分析，验证了预测模型的可用性和有效性。
Characteristics of the GPS/GIS-based floating car data, summary of which types of invalid data, and gives the effective data processing method. Support vector machine, the traffic state prediction method based on analysis of commonly used support vector regression machines, nuclear function and performance of the model parameters, as well as the kernel function and model parameters on the performance of SVM and effect. Small sample, nonlinear, high dimensional regression for the prediction of average speed characteristics, the support vector regression machine to the introduction of prediction based on floating car data section of the speed of vehicles, build a short-term forecasting model of average speed. In Hangzhou section of the actual data, for example, elaborated on the specific modeling and solving process of the support vector machine for regression prediction model. Use LibSVM2.84 package forecast model parameter selection, sample training, and forecasting solution, and verif (2012-06-24, Others, 2156KB, 下载32次)