1 Jan 2025Open access
<p><span>A Heterogeneous Deep Ensemble Approach for Anomaly Detection in Class Imbalanced Energy Consumption Data</span></p>Publisher siteSSRN Electronic Journal, Energy Load and Power Forecasting
Active, last published 2026
In electricity theft detection techniques
David Kaimenyi
Marangu
Scholar“Research focused on Electricity Theft Detection Techniques and adjacent fields.”
Claim Your Profile1
H-index
3
Citations
David has not officially claimed their profile. If you are David, claim it free.
Claim Your Profile
Pioneer
LOCKED
Pathfinder
LOCKED
Scholar
EARNED
Innovator
LOCKED
Inventor
LOCKED
Catalyst
LOCKED
Expert
UPGRADE
01 · About the work
What I study
avid Kaimenyi Marangu is a researcher working on Electricity Theft Detection Techniques. A fuller summary will appear once they update their profile.
02 · Reach
Publication output and reach
David's work has been cited 3 times across 2 active years. Bars show publications per year; the line shows cumulative citation totals across publications first appearing in each year.
03 · Research focus
Topics
Electricity Theft Detection Techniques×6Energy Load and Power Forecasting×4
04 · Where I am
Affiliations
Affiliation on published researchMurang'a University of Technology, KenyaDrawn from the institution listed on this researcher’s published work.
Research themes (UN SDGs)
05 · Selected work
Recent publications
4 works1 Jan 2025Open access
A COMPARATIVE ANALYSIS OF CLASS IMBALANCE HANDLING TECHNIQUES FOR DEEP MODELS IN THE DETECTION OF ANOMALIES IN ENERGY CONSUMPTIONPublisher siteSSRN Electronic Journal, Electricity Theft Detection Techniques
29 May 2024Open access1cites
Systematic Review of Models Usedto Handle Class Imbalance in Anomaly Detection for Energy ConsumptionPublisher siteInternational Journal of Artificial Intelligence & Applications, Electricity Theft Detection Techniques
1 Jan 2024Open access1cites
Systematic Review of Models Used to Handle Class Imbalance in Anomaly Detection for Energy ConsumptionPublisher siteSSRN Electronic Journal, Electricity Theft Detection Techniques
Expert Academic Profiles go further
Citation trend analytics, exportable publication records, and direct enquiry routing from industry and funders.
Are you David?
Claim it to verify your details, connect with industry partners, and explore Fractional Domain Expert opportunities through MARATTO™.
African researchers are full of potential that too often goes unrecognised. Your MARATTO™ profile gives your work the commercial pathway it deserves.
Claim Your Profile
Free to claim · takes a minute to verify it’s you