The efficient and appropriate power flow technologies are necessary for better performance of renewable energy system applications. The comparative study of different MPPT algorithms, which are best for RES applicatio...
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The possibility of optimization stochastic image referencing algorithms using mutual information as a target function of image referencing quality is investigated. Three types of mutual information Renyi, Tsallis and ...
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A lot of computational power is needed for the intra prediction procedure in the H.264 video encoder. A reconfigurable similarity-based intra prediction method for the H.264 video encoder is thus presented in this pap...
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The identification of anomalies in power distribution networks is a critical component in ensuring the reliability and stability of energy systems. This investigation aims to find anomalous patterns and vulnerabilitie...
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In this literature, we investigate the repercussions of integrating decentralized generation on active power systems networks. This research will further be applied to the recently integrated 70 MW Ramarothole Solar P...
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In modern production control systems, efficient management of resources and coordination among multiple agents are crucial for optimizing performance and achieving operational goals. This study introduces the Spectral...
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This paper proposes a solar photovoltaic (PV) supported reconfigurable electric vehicle (EV) battery charging with the possibility of grid feeding. The reconfigurable topology has two power transfer options, including...
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In municipal engineering construction management, to enhance on-site layout progress, a Multi-Objective (MO) optimization model is used to estimate the rationality of Site Layout (SL) based on the most important indic...
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Agriculture is vital for the economy and the country's development. Minimizing plant and fruit diseases is crucial, and early detection has become essential in modern agriculture. Today, agriculture is rapidly evo...
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Online Anomaly detection in operational data from dynamic systems is challenging due to the inherent complexity and variability of these datasets. This research introduces an innovative approach that leverages the Sli...
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