Titlebook: Geo-informatics in Sustainable Ecosystem and Society; 6th International Co Yichun Xie,Anbing Zhang,Lili Feng Conference proceedings 2019 Sp

監(jiān)禁

https://doi.org/10.1007/978-981-13-7025-0Airborne Lidar; Artificial Intelligence; Image Processing; Image Reconstruction; Imaging Systems; K-means

流動才波動

MELON

Communications in Computer and Information Science383035.jpg

Locale

Exploit

delta-waves

Anita Runge,Lieselotte Steinbrüggethe optimization of K - Means clustering algorithm in the UCI machine learning database data set Sentiment labelled sentences and Sentence experiments on Corpus show that the algorithm not only can get better clustering results, The clustering results have high stability.

IST

Soil Property Surface Modeling Based on Ensemble Learning for Complex Landforms,curacy was 6.42%, 7.28%, 11.56% and 9.38% higher than that of Regression Kriging (RK), Bayesian Kriging (BK), Inverse Distance Weighting (IDW) and Ordinary Kriging (OK), respectively. (2) The HASMSP-EL can provide more details in the geographical boundary, which made the simulation results consisten

Chromatic

Mapping the Distribution of Exotic Mangrove Species in Shenzhen Bay Using Worldview-2 Imagery,N) classifier and support vector machine (SVM) classifier were applied to spectral and textural features, and six mangrove species classification results were obtained. Considering the six classification results together, the distribution of Sonneratia was mapped based on the criteria that, for each

含水層

white-matter

Soil Property Surface Modeling Based on Ensemble Learning for Complex Landforms,n of global interpolation model and poor adaptability, a high accuracy surface modeling for soil property based on ensemble learning and fusion geographical environment variables was proposed (HASMSP-EL). The simulation accuracy of different interpolation methods was evaluated by using Mean Error (M