Task scheduling strategy for cloud-fog computing system of IoV based on improved quantum genetics and QoS awareness method by ZHANG Fuqi, JIANG Huilin, LIU Fu, HOU Tao, LIU Yujia, GUAN Yueqi, MU Xingtong

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A novel and easy‐to‐implement modulation scheme for reducing modulation complexity in modular multilevel converter by Zichen Wang, Zhijie Liu, Ke‐Jun Li, Jinxin Dou, Zhonglin Guo, Xiaoxue Ge

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The coupled model of water delivery and distribution regulation for single-canal pool systems by Ke Zhou, Yu Fan, Zhanyi Gao, Haorui Chen, Xinrong Zheng, Yun Yang, Jie Liu

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A Bi-Layer Collaborative Planning Framework for Multi-UAV Delivery Tasks in Multi-Depot Urban Logistics by Junfu Wen, Fei Wang, Yebo Su

“…The novelty of this work lies in the seamless integration of an enhanced genetic algorithm and tailored swarm optimization within a unified two-tier architecture. …”
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Deep Reinforcement Learning-Based Dynamic Scheduling for Real-Time Applications in LTE and RAN Slicing for eMBB in 5G by Houssem Eddine Benmadani, Mohamed Azni, Turki Essa Alharbi, Mohammed S. Alzaidi, Mohamed Tounsi

“…Classic resource allocation methods cannot cope with the dynamics of the changing network environment; hence, there is an increasing need for faster and smarter resource allocation schemes. …”
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Combined use of long short‐term memory neural network and quantum computation for hierarchical forecasting of locational marginal prices by Xin Huang, Guozhong Liu, Jiajia Huan, Shuxin Luo, Jing Qiu, Feiyan Qin, Yunxia Xu

“…Abstract Accurate locational marginal price forecasting (LMPF) is crucial for the efficient allocation of resources. Nevertheless, the sudden changes in LMP make it inadequate for many existing long short‐term memory (LSTM) network‐based prediction models to achieve the required accuracy for practical applications. …”
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Supply Chains Problem During Crises: A Data-Driven Approach by Farima Salamian, Amirmohammad Paksaz, Behrooz Khalil Loo, Mobina Mousapour Mamoudan, Mohammad Aghsami, Amir Aghsami

“…Results demonstrate significant improvements in cost reduction, resource allocation, and service levels, highlighting the model’s practical applicability in real-world scenarios. …”
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An Integrated Electricity–Gas–Heat Energy System Based on the Synergy of Long- and Short-Term Energy Storage by Min Zhang, Jinhao Wang, Huiqiang Zhi, Jun Zhao, Xiao Chang, Shifeng Zhang, Xiangyu Guo, Tengxin Wang

“…Firstly, an adaptive noise integration empirical modal decomposition method based on the optimization improvement of the grey wolf algorithm is designed for the power allocation strategy of the hybrid energy storage system; secondly, for the electric–gas system, an energy management strategy for the hybrid electric–gas energy storage system, taking into account the operating characteristics of the alkaline electrolyzer, is proposed in order to strengthen the complementary mechanism between electric energy storage and gas energy storage. …”
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Natural gas logistics management using multi-criteria optimisation methods by Sergey N. Lanin

“…The study demonstrates that the proposed approach can significantly reduce transaction costs and increase revenue through more efficient management of transport and resource allocation. The paper emphasises the importance of adaptability and flexibility of the logistics system in a dynamically changing external environment. …”
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The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…The method takes into account the characteristics and uncertainties of renewable energy sources such as solar and wind energy, and incorporates advanced multi-objective optimization algorithms. …”
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Mental Workload Detection and Assessment Through Statistical Features Extraction and Optimization Using GEL-RF Method for EEG Signals Using N-Back Dataset by Waleed Manzoor, Noman Naseer, Imran Fareed Nizami, Syed Hammad Nazeer, Husam A. Neamah

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Optimizing group utility in itinerary planning: a strategic and crowd-aware approach by Junhua Liu, Aldy Gunawan, Kristin L. Wood, Kwan Hui Lim

“…SCAIR models itinerary recommendation as a Markov Decision Process (MDP) and incorporates a novel State Encoding mechanism that facilitates real-time, efficient itinerary planning and resource allocation in linear time. By prioritizing group outcomes over individual preferences, SCAIR explicitly mitigates the adverse effects of selfish routing. …”
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Multi-Project Staff Scheduling Optimization Considering Employee Welfare in Construction Projects by Junlong Peng, Fei Zhou

“…A mixed-integer programming model is proposed, integrating task allocation, resource scheduling, income growth, and workload balance as core optimization objectives. …”
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THE CONCEPT AND NATURE OF THE FUTURE MANAGERS COMMUNICATIVE-STRATEGIC BEHAVIOR by Victoria V. Levchenko, Anna V. Gorelova

“…In their roles of entrepreneurs, resource allocators and negotiators, it is necessary for managers to know the mechanisms for predicting the communication results and the possible behavior of interlocutors, to know the basic strategies of business communication, as well as the algorithm of strategic communication and strategic ways of solving communication problems; use different communication strategies to most effectively achieve the communication objectives; analyze and correct communicative behavior and choose communication strategies depending on the situation. …”
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Optimization of multi-user scheduling in WPCNs by Lina Yuan, Huajun Chen, Tingsui Liu, Ging Gong

“…However, WPCNs face new challenges in multi-user scheduling due to factors like energy collection efficiency and resource allocation, which are crucial for optimizing network performance. …”
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Dynamic Optimization of Tunnel Construction Scheduling in a Reverse Construction Scenario by Jianying Wei, Yuming Liu, Xiaochun Lu, Rong Zhao, Gan Wang

“…The Mixed-Integer Programming (MIP) approach is used to build the mathematical model, solved with both exact algorithms and Genetic Algorithms (GA), and implemented in Python 3.12.7. …”
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Machine Learning in the National Economy by Azamjon A. Usmonov

“…Machine learning provides a valuable approach for predicting economic indexes, managing risks, and optimizing resource allocation. However, the effectiveness of these models depends on the quality of the data used, and there are challenges related to data completeness, model interpretability, and computational resources. …”
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Risk and resilience based residential electric vehicle integration framework for restoration of modern power distribution networks by Abdullah Ali M. Alghamdi, Dilan Jayaweera

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Enhanced forecasting of emergency department patient arrivals using feature engineering approach and machine learning by Bruno Matos Porto, Flavio Sanson Fogliatto

“…Feature engineering (FE) improved the performance of the ML algorithms. Conclusion Accuracy in predicting ED arrivals, achieved through the FE approach, is key for managing human and material resources, as well as reducing patient waiting times and lengths of stay.…”
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Carbon Dioxide Storage Site Location and Transport Assignment Optimization for Sustainable Maritime Transport by Yanmeng Tao, Ying Yang, Yuquan Du, Shuaian Wang

“…To enhance practical applicability, a two-stage planning framework is proposed, where the first stage selects storage sites, and the second employs a genetic algorithm (GA) for transport assignment. The GA-based solution achieves a total cost only 2.4% higher than the exact MIP model while reducing computational time by 57.9%. …”
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