An intelligent framework for sarcasm detection in Arabic tweets using deep learning with Al-Biruni earth radius optimization algorithm by Reema G. AL-anazi, Muhammad Swaileh A. Alzaidi, Majdy M. Eltahir, Wafa Sulaiman Almukadi, Samah Hazzaa Alajmani, Abdulbasit A. Darem, Mohammed Alshahrani, Nawaf Alhebaishi

“…The experimental results of the AIDSD-ODL method are examined under the Arabic tweets dataset. …”
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Market Oriented Low-Carbon Optimal Scheduling of Virtual Power Plants Considering Multiple User-Side Resources Coordination by Mingbing LI, Qiang LI, Xiyang GUAN, Haoyang ZHOU, Rui LU, Yankun FENG

“…To leverage the synergistic effects of diverse user-side resources, enhance the revenue of Virtual Power Plants (VPPs) participating in the joint electricity-carbon market, and mitigate risks arising from the uncertainty of renewable energy sources (such as wind and solar) and electricity prices, an optimized low-carbon dispatching method for VPPs considering the coordination of diverse user-side resources in a market environment is proposed. …”
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A Comprehensive Review on Uncertainty and Risk Modeling Techniques and Their Applications in Power Systems by Peyman Afzali, Seyed Amir Hosseini, Saeed Peyghami

“…The results show Monte Carlo simulation combined with the K-Means method is consistently a more accurate uncertainty model for wind speeds, closely aligning with real-case scenarios, compared to other methods such as Markov Chain Monte Carlo (MCMC), robust optimization (RO), and information-gap decision theory (IGDT).…”
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A robust Logistics-Electric framework for optimal power management of electrified ports under uncertain vessel arrival time by Ilias Sarantakos, Saman Nikkhah, Meltem Peker, Annabel Bowkett, Timur Sayfutdinov, Arman Alahyari, Charalampos Patsios, John Mangan, Adib Allahham, Eleni Bougioukou, Alan Murphy, Kayvan Pazouki

“…An optimal power flow method is developed for a real-life port, with consideration for multiple port logistic assets such as cargo handling equipment, reefers, and renewable energy sources. …”
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Research on the Capacity Allocation Optimization of Island Micro-grid Including Wind Power, Tidal Current Energy and Energy Storage by PANG Jiameng, ZANG Xiaodi

“…The three-objective optimization model uses the multi-objective particle swarm optimization algorithm to solve the established model, and obtains different capacity allocation schemes. …”
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Optimal Scheduling Strategy of Wind–Solar–Thermal-Storage Power Energy Based on CGAN and Dynamic Line–Rated Power by Sile Hu, Yuan Gao, Wenbin Cai, Jianan Nan, Ye Li, Muhammad Farhan Khan, Yucan Zhao, Jiaqiang Yang

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Optimizing multi-objective hybrid energy systems with pumped hydro storage for enhanced stability and efficiency in renewable energy integration by Junxian Li, Jiaxin Yuan, Xuxin Yue

“…The investigation primary aim is minimizing the electricity fluctuations’ impact through the renewable enegy sources integration in the large scale. The optimization strategy encompasses a series of complex constraints in term of hydropower plant, in which pumped hydro energy storage provides an accurate flexibity. …”
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Deep Learning and Methods Based on Large Language Models Applied to Stellar Light Curve Classification by Yu-Yang Li, Yu Bai, Cunshi Wang, Mengwei Qu, Ziteng Lu, Roberto Soria, Jifeng Liu

“…Light curves serve as a valuable source of information on stellar formation and evolution. …”
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Low‐carbon optimal scheduling strategy for multi‐agent integrated energy system of the park based on Stackelberg–Nash game by Yanbo Chen, Jiaqi Li, Zhe Fang, Ning Zhang, Tao Huang, Zuomao Chen

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Offshore wave and wind energy development in the Southern Hemisphere will remain optimal between 20°E and 180°E by 2100 by Xiaohu Zhao, Guohe Huang, Yongping Li, Chen Lu, Chuyin Tian, Tangnyu Song, Xiong Zhou, Wenchang Tang, Bo Pang

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Numerical investigation on structure optimization and heat transfer of a phase change accumulator based on changing eccentricity and fin parameters by Shi Yiting, Zhang Liting, Yang Yongwen, Zhang Tao, Li Qifen

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Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany by Loukas Kyriakidis, Rushit Kansara, Maria Isabel Roldán Serrano

“…Industrial energy systems are increasingly required to reduce operating costs and CO₂ emissions while integrating variable renewable energy sources. Managing these objectives under uncertainty requires advanced optimization strategies capable of delivering reliable and real-time decisions. …”
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Comprehensive optimization of active and reactive power scheduling in smart microgrids by accounting for line transmission losses using genetic algorithm by F.Z. Zahraoui, H.E. Chakir, M. Et-taoussi, H Ouadi

“…Smart microgrids face increasingly complex challenges in providing optimal power flow due to the integration of intermittent renewable energy sources, reactive power demand, and transmission line losses. …”
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Advancing Energy Transition: A Circular Economy Framework for Co-Optimizing Energy, Water, and Emissions in Low-Carbon Systems by Mohamed Elsir, Ameena Saad Al-Sumaiti, Mohamed Shawky El Moursi

“…We employ a novel risk-multi-objective stochastic (RMOBS) optimization method, coupled with a two-stage stochastic programming model, to address uncertainties through hidden Markov processes and conditional value-at-risk (CVaR) techniques. …”
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Investigation of a horizontal low power wind turbine by S. Yu. Shamanin, V. L. Blinov, V. V. Savchenko, Yu. M. Brodov

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Noise Analysis and Suppression Methods for the Front-End Readout Circuit of a Microelectromechanical Systems Gyroscope by Chunhua He, Yingyu Xu, Xiaoman Wang, Heng Wu, Lianglun Cheng, Guizhen Yan, Qinwen Huang

“…Therefore, it is essential to analyze and suppress the noises in the key analog circuits, which are the main noise sources. This study presents an optimized front-end readout circuit and noise suppression methods. …”
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Big data classification method of non relational distributed submission information under differentiated requirements by Lu HAN, Weiyu CHEN, Fei ZHANG, Jianfeng HE, Huaizhen SU

“…The classification method of non-relational distributed submitted information big data under the differentiated demand was studied, aiming at the problem of multi-source heterogeneous, widely distributed submitted information with more differentiated application requirements and inability to distinguish the available information.Firstly, the usability, openness and expansibility of the non-relational distributed submission information database were analyzed.The unstructured database storage TRIP was used to store non-relational distributed submission information by combining the basic requirements of field types.Then, the hashing process within the Hamming hash family was analyzed.Under the constraint of linearity level requirements, cellular automata with multiple attractors were used to optimize the system.The optimal parameters of the multiple attractor cellular automata classifier were improved through genetic algorithm, thus improving the big data classification method.Experimental results show that this method can effectively identify and classify structured data and unstructured data in non relational distributed submission information, and has high classification accuracy.…”
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Modern Methods Used in Enterprise Resource Planning About the Business of International and Iraqi Commercial Companies by AlaaelDeen Ramadan, Hanaa Sharhan Hashim

“…Plan and expand the resources, methods, and techniques used in these activities. …”
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Hierarchical deep Q-network-based optimization of resilient grids under multi-dimensional uncertainties from extreme weather by Shimeng Dong, Chao Wang, Yan Zhang, Yanan Wang, Xiaodong Zhang, Linrun Guo, Liwei Ju

“…This paper introduces an innovative optimization framework leveraging Deep Q-Networks (DQN) to integrate renewable energy sources, energy storage systems, and advanced resilience metrics into a cohesive decision-making model. …”
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Machine learning and optimization in hybrid energy storage systems: Integrating MPC, PSO, MILP, and ANN for grid stability and efficiency by Rajesh M. Bhagat, Dilendra B. Jasutkar, Amitkumar B. Ranit, Vikrant S. Vairagade, Balram Yelamasetti, Sagar D. Shelare, Shubham Sharma, Abinash Mahapatro, V.K. Bupesh Raja, Quadri Noorulhasan Naveed, Naoufel Kraiem, Saiful Islam, Jasmina Lozanovic

“…Hybrid Energy Storage Systems (HESS) can provide solutions for grid stability and integration of renewable energy sources. A novel model integrating Model Predictive Control (MPC), Particle Swarm Optimization (PSO), Mixed-Integer Linear Programming (MILP), and Artificial Neural Networks (ANN) is developed to optimize HESS performance. …”
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