sunyong2016

academicpages.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

ANFIS

Fuzzy Q learning in Tensorflow , Training an ANFIS.

DeepRL-Chinese

PostGIS-Examples

常用的PostGIS的一些函数使用方法以及自定义函数，比如：pg连接oracle、pg连接sqlserver、导出csv、导入csv、查询XX米范围内数据、模糊查询、热力图聚合、生成扇形、生成栅格、生成泰森多边形、生成蜂巢图、裁剪多边形、计算点所在区域、路径分析、近邻计算等

pytorch_cluster

PyTorch Extension Library of Optimized Graph Cluster Algorithms

Semantic-Parsing

shp2geosparql

Java console tool to convert geometries from shape files to RDF using GeoSPARQL OGC standard . You can extract geometries and spatial relations of a SHP and convert them to RDF in WGS84 Reference System. Geometry2RDF: https://github.com/boricles/geometry2rdf was taken as the base of this develpment.

SKS

A high performance geospatial database that supports spatial keyword search.

TTMF

TTMF: A Triple Trustworthiness Measurement Frame for Knowledge Graphs

sunyong2016/shp2geosparql

Java console tool to convert geometries from shape files to RDF using GeoSPARQL OGC standard . You can extract geometries and spatial relations of a SHP and convert them to RDF in WGS84 Reference System. Geometry2RDF: https://github.com/boricles/geometry2rdf was taken as the base of this develpment.

sunyong2016/ANFIS-1

Adaptive neuro fuzzy inference system (ANFIS) is a kind of neural network that is based on TSK fuzzy inference system. Since it integrates both neural networks and fuzzy logic principles, it has potential to capture the benefits of both in a single framework. Its inference system corresponds to a set of fuzzy IF–THEN rules that have learning capability to approximate nonlinear functions. Hence, ANFIS is considered to be universal approximator.

sunyong2016/Assignment-Problem

Items related to the maximum weight perfect matching in a weighted bipartite graph

sunyong2016/data-structures-and-algorithms-in-python

"Data Structures and Algorithms in Python" is designed to provide an introduction to data structures and algorithms, including their design, analysis, and implementation. The authors take advantage of the beauty and simplicity of Python to present executable source code that is clear and concise. Furthermore, a consistent object-oriented viewpoint is retained throughout the book, including the use of inheritance, both to maximize code reuse and to draw attention to the clear similarities and differences of various abstract data types and algorithmic approaches.

sunyong2016/MovieRecommendationSystem

School project to design and develop collaborative filtering algorithms that predict the unknown ratings in the test data by learning users' preference from the training data. This project is developed in C#.