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Dergiler / Sakarya University Journal of Computer and Information Sciences / 2026 / Volume: 7 Issue: 1

Predicting Engine Emissions Using Eco-Friendly Fuels for Sustainable Transportation

Beytullah Eren(Sakarya University)0000-0001-6747-7004
İdris Cesur(SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ)0000-0001-7487-5676
Sayfa
—
Yayın Tarihi
2024-04-30
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

It promotes environmental sustainability by providing valuable insights into vehicle emissions prediction and guiding the development of eco-friendly fuels for a more efficient transportation system.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In recent years, increasing concerns about vehicle emissions' environmental and public health impacts have led to the desire to use eco-friendly fuels as alternatives to traditional fossil fuels.
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Temel Bulgular & Veri:This study proposes using artificial neural networks (ANN), a machine learning technique, to accurately predict vehicle emissions associated with eco-friendly fuels across different compositions and engine speeds.
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Sonuç & Katkı:It promotes environmental sustainability by providing valuable insights into vehicle emissions prediction and guiding the development of eco-friendly fuels for a more efficient transportation system.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Engine emissions prediction · Eco-friendly fuels · Artificial neural network

Abstract

In recent years, increasing concerns about vehicle emissions' environmental and public health impacts have led to the desire to use eco-friendly fuels as alternatives to traditional fossil fuels. Biofuels, hydrogen, and electric power offer lower greenhouse gas emissions and improved air quality, resulting in their development and adoption globally. Predicting vehicle emissions using these fuels is crucial for assessing their environmental benefits. This study proposes using artificial neural networks (ANN), a machine learning technique, to accurately predict vehicle emissions associated with eco-friendly fuels across different compositions and engine speeds. The ANN model has a strong correlation between predicted and observed emissions values, indicating the effectiveness of its model. The research underscores the importance of adopting innovative approaches to address environmental challenges and promote sustainable transportation solutions. This study contributes to reducing the adverse effects of vehicle emissions on air quality and public health by assisting policymakers, car manufacturers, and city planners in making effective decisions. It promotes environmental sustainability by providing valuable insights into vehicle emissions prediction and guiding the development of eco-friendly fuels for a more efficient transportation system.

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Bu Makaleye Atıf Yap

Eren, B., Cesur, İ. (2024). Predicting Engine Emissions Using Eco-Friendly Fuels for Sustainable Transportation. Sakarya University Journal of Computer and Information Sciences, Volume: 7 Issue: 1. https://doi.org/10.35377/saucis...1444155

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