Titlebook: Geo-Spatial Knowledge and Intelligence; 4th International Co Hanning Yuan,Jing Geng,Fuling Bian Conference proceedings 2017 Springer Nature

辞职

Exonerate

织物

Predict Port Throughput Based on Probabilistic Forecast Modelips. The commuters’ travel behaviors can be described through a probabilistic model in transportation planning. In this study, we adopt the transportation probabilistic forecast model to forecast port throughput. First, we amend the model with a port attraction coefficient to forecast port throughpu

Foment

cancellous-bone

Progressive Network Transmission Method Research of Vector Dataon of vector data. By studying the traditional progressive transmission method of vector data and considering the spatial position and geometric features of vector data, we proposed an efficient progressive transmission method. We divided the vector data into blocks based on spatial location, then a

Venules

心胸开阔

Application of Different Composite Index Methods in the Evaluation of Soil Heavy Metal Pollutionex, Yao Index and Mixed Weighted Model of three different composite index methods, and compares the suitability of three methods. Nemerow Pollution Index adopts arithmetic mean of subindex to improve the contribution rate of the most polluted elements and undermines the contribution of each partial

细菌等

起皱纹

A Least-Squares Ellipse Fitting Method Based on Boundaryhe problem of the ship targets extraction and parameters estimation in SAR image. For the least-squares ellipse fitting method, all of the sample points on the boundary were involved in operation and causing deviation of the final results of ellipse fitting. For this kind of situation, a least-squar

cathartic

Training Convolutional Neural Networks Based on Ternary Optical Processorprove the concurrency and throughput of the training process of CNN. Reviewing the irrelevance data and the inherent parallelism module of the CNN, this paper discusses the preprocessing way of arbitrary number of two-dimensional data which include feature maps, convolutional kernels and mini-batche