BISCARRI TRIVIÑO , Félix

Este conjunto de datos respalda los objetivos de un estudio que busca analizar el impacto de una plataforma de movilidad en el desarrollo cognitivo de niños con discapacidades severas (niveles IV-V de GMFCS). La locomoción es crucial en el desarrollo psicológico de las personas, estrechamente vinculada al rápido crecimiento neurocognitivo. El...

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Datamining has become increasingly common in both the public and private sectors. A non-technical loss is defined as any consumed energy or service which is not billed because of measurement equipment failure or ill-intentioned and fraudulent manipulation of said equipment. The detection of non-technical losses (which includes fraud detection)...

Improving the use made of the water in supply systems means monitoring flow measurements as a basis for calculating volume distribution and water loss. This raises the question of how to detect and correct flow measurement errors without resorting to costly, and often practically impossible, measurements "in situ". This article presents a...

Currently, power distribution companies have several problems that are related to energy losses. For example, the energy used might not be billed due to illegal manipulation or a breakdown in the customer's measurement equipment. These types of losses are called non-technical losses (NTLs), and these losses are usually greater than the losses...

Ground testing is an essential, but also expensive, process performed by the Airbus Defence and Space Company (Airbus DS) in the manufacturing cycle of an aircraft. Thus, this process involves a large number of company staff and a significant amount of resources. Consequently, both staff work hours and resource usage imply significant costs,...

The detection of non-technical losses (NTLs), in most papers, commonly deals with the utilization of the registered consumption for each customer; besides, some researchers used the economic activity, the active/reactive ratio and the contract power. Currently, utility company databases store enormous amounts of information on both...

This paper describes a method proposed in order to recover electrical energy (lost by abnormality or fraud) by means of a data mining analysis based in outliers detection. It provides a general methodology to obtain a list of abnormal users using only the general customer databases as input. The hole input information needed is taken...

This paper deals with the characterization of customers in power companies in order to detect consumption Non-Technical Losses (NTL). A new framework is presented, to find relevant knowledge about the particular characteristics of the electric power customers. The authors uses two innovative statistical estimators to weigh variability and trend...

The MIDAS project began in 2006 as collaboration between Endesa, Sadiel, and the University of Seville. The objective of the MIDAS project is the detection of Non-Technical Losses (NTLs) on power utilities. The NTLs represent the non-billed energy due to faults or illegal manipulations in clients' fa cilities. Initially, research lines study...

A non-technical loss (NTL) is defined as any consumed energy or service which is not billed because of measurement equipment failure or illintentioned and fraudulent manipulation of said equipment. This paper describes new advances that we have developed for Midas project. This project is being developed in the Electronic Technology Department...

The Non-Technical Losses (NTLs) represent the non-billed energy due to faults or illegal manipulations in customer facilities. The objective of the Midas project is the detection of NTL through the application of computational intelligence over the information stored in utility company databases. This project has several research lines. Some...

For the electrical sector, minimizing non-technical losses is a very important task because it has a high impact in the company profits. Thus, this paper describes some new advances for the detection of non-technical losses in the customers of one of the most important power utilities of Spain and Latin America: Endesa Company. The study is...

The Endesa Company is the main power utility in Spain. One of the main concerns of power distribution companies is energy loss, both technical and non-technical. A non-technical loss (NTL) in power utilities is defined as any consumed energy or service that is not billed by some type of anomaly. The NTL reduction in Endesa is based on the...

A non-technical loss is defined as any consumed energy or service which is not billed because of measurement equipment failure or ill-intentioned and fraudulent manipulation of said equipment. This paper describes new approaches to the detection of these for electrical companies. Concretely two different methods are proposed: one based on the...

This paper proposes a comprehensive framework to detect non-technical losses (NTLs) and recover electrical energy (lost by abnormalities or fraud) by means of a data mining anal ysis, in the Spanish Power Electric Industry. It is divided into four section: data selection, data preprocessing, descriptive, and pre dictive data mining. The authors...

This paper uses an experimental method to estimate the variance of flowmeter errors (random errors or Type A errors), focusing on problems of detecting defects existing in sensors even with verysmall magnitudes. An inexpensive and simple but accurate test bed is shown, based on the detailed experimental estimation method submitted. Some of the...

The MIDAS project began at 2006 as collaboration between Endesa, Sadiel and the University of Seville. The objective of the MIDAS project is the detection of Non-Technical Losses (NTLs) on power utilities. The NTLs represent the non-billed energy due to faults or illegal manipulations in clients' facilities. Initially, research lines study the...

Usually, the fraud detection method in utility companies uses the consumption information, the economic activity, the geographic location, the active/reactive ration and the contracted power. This paper proposes a combined text mining and neural networks to increase the efficiency in NonTechnical Losses (NTLs) detection methods which...