On-line and indirect tool wear monitoring in turning with artificial neural networks: a review of more than a decade of research
B Sick - Mechanical systems and signal processing, 2002 - Elsevier
The supervision of tool wear is the most difficult task in the context of tool condition
monitoring for metal-cutting processes. Based on a continuous acquisition of signals with …
monitoring for metal-cutting processes. Based on a continuous acquisition of signals with …
Machine learning techniques for civil engineering problems
Y Reich - Computer‐Aided Civil and Infrastructure Engineering, 1997 - Wiley Online Library
The growing volume of information databases presents opportunities for advanced data
analysis techniques from machine learning (ML) research. Practical applications of ML are …
analysis techniques from machine learning (ML) research. Practical applications of ML are …
Statistical methods versus neural networks in transportation research: Differences, similarities and some insights
In the field of transportation, data analysis is probably the most important and widely used
research tool available. In the data analysis universe, there are two 'schools of thought'; the …
research tool available. In the data analysis universe, there are two 'schools of thought'; the …
Modeling wine preferences by data mining from physicochemical properties
We propose a data mining approach to predict human wine taste preferences that is based
on easily available analytical tests at the certification step. A large dataset (when compared …
on easily available analytical tests at the certification step. A large dataset (when compared …
Neural networks for classification: a survey
GP Zhang - IEEE Transactions on Systems, Man, and …, 2000 - ieeexplore.ieee.org
Classification is one of the most active research and application areas of neural networks.
The literature is vast and growing. This paper summarizes some of the most important …
The literature is vast and growing. This paper summarizes some of the most important …
On comparing classifiers: Pitfalls to avoid and a recommended approach
SL Salzberg - Data mining and knowledge discovery, 1997 - Springer
An important component of many data mining projects is finding a good classification
algorithm, a process that requires very careful thought about experimental design. If not …
algorithm, a process that requires very careful thought about experimental design. If not …
Perspective: Machine learning in experimental solid mechanics
Experimental solid mechanics is at a pivotal point where machine learning (ML) approaches
are rapidly proliferating into the discovery process due to significant advances in data …
are rapidly proliferating into the discovery process due to significant advances in data …
Towards parameter-free data mining
Most data mining algorithms require the setting of many input parameters. Two main
dangers of working with parameter-laden algorithms are the following. First, incorrect …
dangers of working with parameter-laden algorithms are the following. First, incorrect …
A data mining approach to predict forest fires using meteorological data
P Cortez, AJR Morais - 2007 - repositorium.sdum.uminho.pt
Forest fires are a major environmental issue, creating economical and ecological damage
while endangering human lives. Fast detection is a key element for controlling such …
while endangering human lives. Fast detection is a key element for controlling such …
A systematic comparison of supervised classifiers
Pattern recognition has been employed in a myriad of industrial, commercial and academic
applications. Many techniques have been devised to tackle such a diversity of applications …
applications. Many techniques have been devised to tackle such a diversity of applications …