首页|Study Findings from Yazd University Broaden Understanding of Ma- chine Learning (A machine learning approach for predicting and lo- calizing the failure and damage point in sewer networks due to pipe properties)
Study Findings from Yazd University Broaden Understanding of Ma- chine Learning (A machine learning approach for predicting and lo- calizing the failure and damage point in sewer networks due to pipe properties)
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NETL
NSTL
Iwa Publishing
2024 FEB 20 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial intelligence have been published. According to news originating from Yazd, Iran, by NewsRx correspondents, research stated, “As a basic infrastructure, sewers play an important role in the innards of every city and town to remove unsanitary water from all kinds of livable and functional spaces.” Our news editors obtained a quote from the research from Yazd University: “Sewer pipe failures (SPFs) are unwanted and unsafe in many ways, as the disturbance that they cause is undeniable. Unlike water distribution systems, sewer pipe networks meet manholes more often as water movement is due to gravity and manholes are needed in every intersection as well as through pipe length. Many studies have been focused on sewer pipe failures and so on, but few investigations have been done to show the effect of manhole proximity on pipe failure. Predicting and localizing the sewer pipe failures are affected by different parameters of sewer pipe properties, such as material, age, slope, and depth of the sewer pipes.”
NETL
NSTL
Iwa Publishing
