[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Odoom, 2020 - Google Patents

A Methodology in Utilizing Machine Learning Algorithm for Electricity Theft Detection in Ghana

Odoom, 2020

View PDF
Document ID
2955276476677272239
Author
Odoom D
Publication year
Publication venue
Available at SSRN 3659614

External Links

Snippet

Many countries across the world including Ghana face the menace of electricity theft which exerts negative influence on the income-generating ability of its electricity providers leading to losses of over a billion according to a World Bank report. The purpose of this work seeks …
Continue reading at papers.ssrn.com (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6279Classification techniques relating to the number of classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce

Similar Documents

Publication Publication Date Title
Li et al. Electricity theft detection in power grids with deep learning and random forests
Zidi et al. Theft detection dataset for benchmarking and machine learning based classification in a smart grid environment
Takiddin et al. Deep autoencoder-based anomaly detection of electricity theft cyberattacks in smart grids
Xia et al. Detection methods in smart meters for electricity thefts: A survey
Glauner et al. The challenge of non-technical loss detection using artificial intelligence: A survey
Shi et al. Power system event identification based on deep neural network with information loading
Maamar et al. Machine learning techniques for energy theft detection in AMI
Lin et al. Electricity theft detection based on stacked autoencoder and the undersampling and resampling based random forest algorithm
Gu et al. Electricity theft detection in AMI with low false positive rate based on deep learning and evolutionary algorithm
Bian et al. Abnormal detection of electricity consumption of user based on particle swarm optimization and long short term memory with the attention mechanism
CN115688035A (en) Time sequence power data anomaly detection method based on self-supervision learning
Tehrani et al. Decision tree based electricity theft detection in smart grid
Han et al. Conditional abnormality detection based on AMI data mining
Javaid et al. Using GANCNN and ERNET for detection of non technical losses to secure smart grids
Ye et al. A novel self-supervised learning-based anomalous node detection method based on an autoencoder for wireless sensor networks
Banga et al. Accurate detection of electricity theft using classification algorithms and Internet of Things in smart grid
Zhang Financial data anomaly detection method based on decision tree and random forest algorithm
Kabir et al. Detection of non-technical losses using MLP-GRU based neural network to secure smart grids
Zhou et al. Credit card fraud identification based on principal component analysis and improved AdaBoost algorithm
Shehzad et al. Deep learning-based meta-learner strategy for electricity theft detection
Ali et al. Exploiting machine learning to tackle peculiar consumption of electricity in power grids: A step towards building green smart cities
Odoom A Methodology in Utilizing Machine Learning Algorithm for Electricity Theft Detection in Ghana
Olivares-Rojas et al. Machine learning model for the detection of electric energy fraud using an edge-fog computing architecture
Nichiforov et al. Learning dominant usage from anomaly patterns in building energy traces
Zhang et al. A multiscale electricity theft detection model based on feature engineering