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| http://dx.doi.org/10.1016/j.jvscit.2024.101611 | DOI Listing |
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Application of artificial intelligence based on state grid ESG platform in clean energy scheduling optimization.
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School of Public Administration, Guangzhou University, Guangzhou, 510006, China.
The randomness and volatility of existing clean energy sources have increased the complexity of grid scheduling. To address this issue, this work proposes an artificial intelligence (AI) empowered method based on the Environmental, Social, and Governance (ESG) big data platform, focusing on multi-objective scheduling optimization for clean energy. This work employs a combination of Particle Swarm Optimization (PSO) and Deep Q-Network (DQN) to enhance grid scheduling efficiency and clean energy utilization.
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Department of Earth and Planetary Sciences, University of California, Riverside, CA, 92521, USA.
The Salton Sea (SS), California's largest inland lake at 816 square kilometers, formed in 1905 from a levee breach in an area historically characterized by natural wet-dry cycles as Lake Cahuilla. Despite more than a century of untreated agricultural drainage inputs, there has not been a systematic assessment of nutrient loading, cycling, and associated ecological impacts at this iconic waterbody. The lake is now experiencing unprecedented degradation, particularly following the 2003 Quantification Settlement Agreement-the largest agricultural-to-urban water transfer in the United States.
View Article and Find Full Text PDFA quantitative benchmark of neural network feature selection methods for detecting nonlinear signals.
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Department of Medical Sciences, University of Torino, Torino, Italy.
Classification and regression problems can be challenging when the relevant input features are diluted in noisy datasets, in particular when the sample size is limited. Traditional Feature Selection (FS) methods address this issue by relying on some assumptions such as the linear or additive relationship between features. Recently, a proliferation of Deep Learning (DL) models has emerged to tackle both FS and prediction at the same time, allowing non-linear modeling of the selected features.
View Article and Find Full Text PDFConservation challenges for Brazilian primates and the role of protected areas in a changing climate.
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The negative effects of land-use changes on biodiversity significantly contribute to climate change. Primates are among the animals most affected by these changes, because of their high dependence on forest cover where a lack of forest connectivity can limit their dispersal and segregate their populations. In this sense, protected areas (PAs) are crucial for conserving endangered primates, especially endemic species.
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Department of Orthopedics, Guru Gobind Singh Medical College and Hospital, Faridkot, Punjab, 151203, India.
Generative Artificial Intelligence (AI), characterized by its ability to generate diverse forms of content including text, images, video and audio, has revolutionized many fields, including medical education. Generative AI leverages machine learning to create diverse content, enabling personalized learning, enhancing resource accessibility, and facilitating interactive case studies. This narrative review explores the integration of generative artificial intelligence (AI) into orthopedic education and training, highlighting its potential, current challenges, and future trajectory.
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