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September 24, 2025Digital TransformationOpen Access

Developing a Machine Learning Model for a Smart Home System

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Authors

МЛМ. М. Лукашевич

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Overview

Model predicts heating and cooling loads in smart home systems, suggesting improved energy efficiency.

Key Points

  • Machine learning enhances the efficiency of smart home systems, improving automation and regulation of energy use.
  • The study demonstrates a neural network model predicting heating and cooling loads, achieving high accuracy with regression metrics.
  • Exploratory data analysis and grid search methods were utilized to optimize hyperparameter selection for the machine learning models.
  • This research emphasizes constant data expansion and retraining for improving smart home automation technologies.

Cite This Study

М. М. Лукашевич (2025) studied this question.

synapsesocial.com/papers/68d6e16f8b2b6861e4c4012ehttps://doi.org/10.35596/1729-7648-2025-31-3-22-32
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Also Consider

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  1. 1Predictive Modelling for Heating and Cooling Load Systems of Residential Building2024
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  5. 5Harnessing Multidimensional Insights and Advanced Machine Learning for Optimized Energy Efficiency: Revolutionizing Sustainable Systems through Predictive Optimization, Ensemble Learning and IoT Integration for Enhanced Heating and Cooling Load Management2024 · 1 citations