Unsupervised non-technical losses identification through optimum-path forest
نویسندگان
چکیده
منابع مشابه
Learning to Identify Non-Technical Losses with Optimum-Path Forest
In this work we have proposed an innovative and accurate solution for non-technical losses identification using the Optimum-Path Forest (OPF) classifier and its learning algorithm. Results in two datasets demonstrated that OPF outperformed the state of the art pattern recognition techniques and OPF with learning achieved better results for automatic nontechnical losses identification than recen...
متن کاملFast Petroleum Well Drilling Monitoring Through Optimum-Path Forest
Automatic inspection of petroleum well drilling has became paramount in the last years, mainly because of the crucial importance of saving time and operations during the drilling process in order to avoid some problems, such as the collapse of the well borehole walls. In this paper, we extended another work by proposing a fast petroleum well drilling monitoring through a modified version of the...
متن کاملSupervised Pattern Classification Using Optimum-Path Forest
We present a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), and describe one of its classifiers developed for the supervised learning case. This classifier does not require parameters and can handle some overlapping among multiple classes with arbitrary shapes. The method reduces the pattern recognition problem into the computation of an optimum-path forest in ...
متن کاملRecent advances on optimum-path forest for data classification: supervised, semi-supervised and unsupervised learning
Although one can find several pattern recognition techniques out there, there is still room for improvements and new approaches. In this book chapter, we revisited the Optimum-Path Forest (OPF) classifier, which has been evaluated over the last years in a number of applications that consider supervised, semi-supervised and unsupervised learning problems. We also presented a brief compilation of...
متن کاملLand Use Classification Using Optimum-Path Forest
It was introduced in this paper the Optimum-Path Forest for land use classification aiming a better environmental management, using images obtained from CBERS 2B CCD satellite covering the area of the Rio das Pedras watershed, Itatinga City, São Paulo State, Brazil. We also compared the Optimum-Path Forest algorithm with the well known supervised classifiers: Artificial Neural Networks using Mu...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Electric Power Systems Research
سال: 2016
ISSN: 0378-7796
DOI: 10.1016/j.epsr.2016.05.036