This paper presents a systematic simulation-based framework for comparing the structural performance and energy efficiency of robotic arm links fabricated from Aluminium 6061-T6 and Carbon Fiber Reinf...
This paper proposes an intelligent control method based on the Camel Marching Optimization Algorithm (CJOA) for the adaptive adjustment of control parameters of grid structured photovoltaic inverters ...
Mixed-Integer Programs (MIPs) are NP-hard optimization models that arise in a broad range of decision-making applications, including finance, logistics, energy systems, and network design. Although mo...
This study investigates electrical energy conservation opportunities at SABIC Research and Technology Centre, Bangalore, aligning with SABIC’s global sustainability goal of a 15% reduction in energy c...
In modern manufacturing value chains, achieving optimal product quality and sustainability necessitates collaboration across interconnected stakeholders. Conventional Latent Variable Model Inversion (...
This work takes a step toward Automated Machine Learning (AutoML) by moving beyond the traditional black-box approach often seen in engineering applications of neural networks. The primary objective i...
Brain tumours cause severe morbidity. Needs to be diagnosed in the minimum time and with the Highest accuracy. It takes a long time to learn Deep learning Models that can predict the type and severity...
To address the reduction in structural strength and the decreased safety of separated-type aqueduct bodies due to erosion damage caused by sediment-laden flow, an erosion damage model for the aqueduct...
This study proposes a Machine Learning-Optimized 3D Hybrid Chaotic Map (Logistic–Tent–Hénon–Chebyshev) for secure and energy-efficient encryption of images and multimedia data in resource-constrained ...
This paper presents DT-AOF, a decision-theoretic adaptive optimization framework designed to address dynamic optimization problems under uncertainty. The proposed method integrates three key component...
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