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Optimizing Household Electricity With Linear Regression-Based Prediction And Fuzzy Appliance Matching

  • Unique Paper ID: 176402
  • Volume: 11
  • Issue: 11
  • PageNo: 5198-5201
  • Abstract:
  • This invention presents an intelligent electricity management system designed to optimize household energy consumption using linear regression-based prediction and fuzzy appliance matching. By collecting detailed data on home appliances—such as power rating, usage duration, and age—the system leverages machine learning to accurately forecast monthly electricity usage for each device. High-consumption appliances are identified and matched with energy-efficient alternatives through fuzzy string matching techniques, ensuring personalized and practical recommendations. Visual analytics further enhance user awareness by illustrating consumption trends and potential savings. The system promotes sustainable energy practices, reduces electricity bills, and supports smart home integration for future-ready environmental solutions.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 11
  • PageNo: 5198-5201

Optimizing Household Electricity With Linear Regression-Based Prediction And Fuzzy Appliance Matching

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8.01 (Year 2024)
UGC Approved
Journal no 47859

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