In the context of increasing water scarcity and the need to enhance water distribution network efficiency, this study focuses on optimizing the design of pumping stations using data-driven evolutionary algorithms guid...
详细信息
The increase in water consumption and demand has highlighted the need to improve the efficiency of water distribution networks (WDNs). Pumping stations (PS) represent a significant challenge due to their high energy c...
详细信息
Accurate segmentation of brain tumors from Magnetic Resonance Imaging (MRI) scans presents notable challenges. This particularly in differentiating tumors from surrounding tissues with similar intensity. This study ut...
详细信息
Wind power forecasting plays a crucial role in optimizing the integration of wind energy into the grid by predicting wind patterns and energy *** enhances the efficiency and reliability of renewable energy *** approac...
详细信息
Wind power forecasting plays a crucial role in optimizing the integration of wind energy into the grid by predicting wind patterns and energy *** enhances the efficiency and reliability of renewable energy *** approaches inform energy management strategies,reduce reliance on fossil fuels,and support the broader transition to sustainable energy *** primary goal of this study is to introduce an effective methodology for estimating wind power through temporal data *** research advances an optimized Multilayer Perceptron(MLP)model using recently proposedmetaheuristic optimization algorithms,namely the FireHawk Optimizer(FHO)and the Non-Monopolize Search(NO).A modified version of FHO,termed FHONO,is developed by integrating NO as a local search mechanism to enhance the exploration capability and address the shortcomings of the original *** developed FHONO is then employed to optimize the MLP for enhanced wind power *** effectiveness of the proposed FHONO-MLP model is validated using renowned datasets from wind turbines in *** results of the comparative analysis between FHONO-MLP,conventionalMLP,and other optimized versions of MLP show that FHONO-MLP outperforms the others,achieving an average RootMean Square Error(RMSE)of 0.105,Mean Absolute Error(MAE)of 0.082,and Coefficient of Determination(R^(2))of 0.967 across all *** findings underscore the significant enhancement in predictive accuracy provided by FHONO and demonstrate its effectiveness in improving wind power forecasting.
The widespread adoption of digital communication technologies across various domains has led to a significant shift towards digitalization. However, this evolution has also introduced vulnerabilities, including unauth...
详细信息
This review investigates the effectiveness of exploiting the massive Artificial Intelligence (AI) technology in the diagnosis of prostate cancer histopathological images. It focuses on studying and analyzing the curre...
详细信息
The rapid evolution of 6G networks demands innovative solutions to address the dual challenges of ensuring robust physical layer security (PLS) and optimizing energy efficiency. This paper introduces an innovative fra...
详细信息
With the rapid increase in cloud services and the increasing shift toward them, balancing the cloud load has become a critical research issue. The increasing demand from customers for technology services worldwide is ...
详细信息
作者:
Suman, SaurabhPacharaney, UtkarshaGote, Pradnyawant M.
Faculty of Engineering and - Technology Department of Computer Science & Design Maharashtra Wardha442001 India
Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India
Gestational Diabetes Mellitus (GDM) is a condition that can put at risk both mother and fetus but early and proper risk assessment need to be carried out for effective management. This paper discloses a Mamdani-kind F...
详细信息
Transferable adversarial attacks are a threat to deep neural networks, in particular, for black-box scenarios where access to model information is limited. One can, for example, exploit the intermediate layer neurons ...
详细信息
暂无评论