Konu "Artificial intelligence" için Mühendislik Fakültesi listeleme
Toplam kayıt 6, listelenen: 1-6
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Estimating the compressive strength of fly ash added concrete using artificial neural networks
(Manisa Celal Bayar Üniversitesi Fen Bilimleri Enstitüsü, 2022)The aim of this study is to develop an artificial intelligence that predicts the compressive strength of fly ash substituted concretes using material mixing ratios. Within the scope of the study, 5 different fly ash mixed ... -
Experimental investigation and application of soft computing models for predicting flow energy loss in arc-shaped constrictions
(IWA Publishing, 2024)This investigation focuses on flow energy, a crucial parameter in the design of water structures such as channels. The research endeavors to explore the relative energy loss (Delta E-AB/E-A) in a constricted flow path of ... -
Forecasting wind power generation using artificial neural network
(Munzur Üniersitesi, 2023)Today, among renewable energy sources, wind energy is used effectively as a clean and sustainable energy source in electricity generation. The uncertain nature of renewable energy sources and the smart ability of the ... -
Optimizing soybean biofuel blends for sustainable urban medium-duty commercial vehicles in India: an AI-driven approach
(Springer, 2024)This article presents the outcomes of a research study focused on optimizing the performance of soybean biofuel blends derived from soybean seeds specifically for urban medium-duty commercial vehicles. The study took into ... -
Recycling dam tailings as cemented mine backfill: Mechanical and geotechnical properties
(Hindawi, 2022)As a result of developing technology and scientific studies, employing dam tailings as critical raw material and vital economic reserve has become widespread recently. Employing dam tailings as a main ingredient of CPB ... -
Weather impact on solar farm performance: A comparative analysis of machine learning techniques
(MDPI, 2023)Forecasting the performance and energy yield of photovoltaic (PV) farms is crucial for establishing the economic sustainability of a newly installed system. The present study aims to develop a prediction model to forecast ...