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GUANGDONG WISHER TECH CO LTD

Overview
  • Total Patents
    13
  • GoodIP Patent Rank
    131,734
About

GUANGDONG WISHER TECH CO LTD has a total of 13 patent applications. Its first patent ever was published in 2019. It filed its patents most often in China. Its main competitors in its focus markets computer technology, measurement and it methods for management are STATE GRID ZHEJIANG ELECTRIC POWER CO LTD MARKETING SERVICE CENTER, ZHONGSHAN POWER SUPPLY BUREAU GUANGDONG POWER GRID CO and ANHUI NANRUI ZHONGTIAN ELECTRIC POWER ELECTRONICS CO LTD.

Patent filings in countries

World map showing GUANGDONG WISHER TECH CO LTDs patent filings in countries
# Country Total Patents
#1 China 13

Patent filings per year

Chart showing GUANGDONG WISHER TECH CO LTDs patent filings per year from 1900 to 2020

Top inventors

# Name Total Patents
#1 Yu Jiequan 13
#2 Chang Wei 13

Latest patents

Publication Filing date Title
CN110689140A Method for intelligently managing rail transit alarm data through big data
CN110728373A Method for sorting rail transit alarm data through machine learning algorithm
CN110596595A Method for predicting RUL of rail-traffic lithium battery through big data
CN110850297A Method for predicting SOH of rail-traffic lithium battery through big data
CN110596594A Method for predicting SOE of rail-traffic lithium battery through big data
CN110689184A Method for predicting rail traffic stream of people through deep learning
CN110704409A Method for optimizing rail transit data quality through data triangular prism algorithm
CN110608711A Method for predicting deformation of rail-crossing tunnel through big data
CN110598905A Method for predicting thermal runaway of rail-to-rail cable through multipoint data acquisition
CN110766034A Method for predicting track deformation through big data
CN110596600A Rail transit battery maintenance prediction method based on battery life calculation table
CN110286668A A kind of rail friendship signal system VIM board faults prediction technique based on big data
CN110610016A Method for predicting rail transit stopping problem based on big data machine learning