Understanding Quality of Products from Customers’ Attitude Using Advanced Machine Learning Methods

Advanced machine learning methods for wind erosion monitoring in southern Iran

Extended abstract Introduction Wind erosion is one the most important factors of land degradation in the arid and semi-arid areas and it is one the most serious environmental problems in the world. In Fars province, 17 cities are prone to wind erosion and are considered as critical zones of wind erosion. One of the most important factors in soil wind erosion is land use/cover change. T...

Data Mining Using Machine Learning to Rediscover Intel’s Customers

Since the PoC, Intel sales and marketing teams have delivered communications to eight vertical industries across four geographies and in eight languages. When we tracked resellers in the engagement chain, we found that, in comparison with the rest of the sales pipeline, twice as many resellers advanced from leads to qualified leads. Their click-through rate for email newsletters is now three ti...

Machine learning algorithms in air quality modeling

Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...

UNDERSTANDING MACHINE LEARNING From Theory to Algorithms

Fault Detection of Anti-friction Bearing using Ensemble Machine Learning Methods

Anti-Friction Bearing (AFB) is a very important machine component and its unscheduled failure leads to cause of malfunction in wide range of rotating machinery which results in unexpected downtime and economic loss. In this paper, ensemble machine learning techniques are demonstrated for the detection of different AFB faults. Initially, statistical features were extracted from temporal vibratio...