Muhammad Buhari

Papers

Total Citations

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About

Muhammad Buhari’s research centers on applying artificial intelligence and machine learning techniques to energy systems, with a particular focus on short-term load forecasting. His most-cited work, “Short-Term Load Forecasting Using Artificial Neural Network” (2012, 42 citations), demonstrates how artificial neural networks (ANNs) can effectively model the nonlinear and complex patterns inherent in electricity demand. By leveraging the learning capabilities of ANNs, Buhari has contributed to more accurate and reliable forecasting methods, which are critical for grid stability, energy management, and operational planning. His work bridges the gap between advanced computational models and practical energy sector challenges, offering solutions that improve efficiency and decision-making. With 42 citations on this foundational paper alone, Buhari’s research has influenced subsequent studies in load forecasting and AI applications in power systems. His contributions are particularly valuable for students and researchers exploring the intersection of machine learning and energy analytics, providing a clear example of how neural networks can solve real-world forecasting problems.