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841
QUIRCY: QUantum Integrated ResilienCY for Power Systems
Published 2025-01-01“…This paper introduces quantum integrated resiliency for power systems (QUIRCY), a new resilience approach aimed at optimizing resource allocation in power systems. The proposed framework integrates a two-level quantum algorithm that combines the Harrow-Hassidim-Lloyd (HHL) algorithm for highly efficient quantum power flow analysis with quadratic unconstrained binary optimization (QUBO) to strategically allocate distributed energy resources (DERs). …”
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842
Auditing Flood Vulnerability Geo-Intelligence Workflow for Biases
Published 2024-11-01Get full text
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843
Classification of start-ups’ digital marketing adoption experiences: an investigation of characteristics and interactions
Published 2025-03-01“…Data were collected on the usage of digital marketing tools, level of utilization, duration of adoption, resource allocation, and budget. A nonparametric decision tree algorithm, visualized using R, was employed for data analysis. …”
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844
Artificial intelligence in triage of COVID-19 patients
Published 2024-12-01“…Systems capable of predicting individuals at higher risk of progressing to severe forms of the disease could optimize the allocation and direction of resources. In this work, we evaluated the performance of different Machine Learning algorithms when predicting clinical outcomes of patients hospitalized with COVID-19, using clinical data from hospital admission alone. …”
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845
Information Content Assessment of the Federal Budget and the Budget Process in the Russian Federation
Published 2022-08-01Get full text
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846
SOE: A Multi-Objective Traffic Scheduling Engine for DDoS Mitigation with Isolation-Aware Optimization
Published 2025-06-01“…When interception fails, effectively allocating mixed benign and malicious traffic under resource constraints becomes a critical challenge. …”
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847
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848
A Bi-Layer Collaborative Planning Framework for Multi-UAV Delivery Tasks in Multi-Depot Urban Logistics
Published 2025-07-01“…To address the modeling complexity and multi-objective collaborative optimization challenges in multi-depot and multiple unmanned aerial vehicle (UAV) delivery task planning, this paper proposes a bi-layer planning framework, which comprehensively considers resource constraints, multi-depot coordination, and the coupling characteristics of path execution. …”
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849
Deep Reinforcement Learning-Based Dynamic Scheduling for Real-Time Applications in LTE and RAN Slicing for eMBB in 5G
Published 2025-01-01“…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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850
The coupled model of water delivery and distribution regulation for single-canal pool systems
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851
Supply Chains Problem During Crises: A Data-Driven Approach
Published 2024-12-01“…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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852
The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market
Published 2024-09-01“…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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853
Natural gas logistics management using multi-criteria optimisation methods
Published 2024-10-01“…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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854
Combined use of long short‐term memory neural network and quantum computation for hierarchical forecasting of locational marginal prices
Published 2025-02-01“…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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855
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856
Optimizing group utility in itinerary planning: a strategic and crowd-aware approach
Published 2025-08-01“…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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857
Multi-Project Staff Scheduling Optimization Considering Employee Welfare in Construction Projects
Published 2025-05-01“…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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858
THE CONCEPT AND NATURE OF THE FUTURE MANAGERS COMMUNICATIVE-STRATEGIC BEHAVIOR
Published 2015-10-01“…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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859
Optimization of multi-user scheduling in WPCNs
Published 2025-04-01“…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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860
Machine Learning in the National Economy
Published 2025-07-01“…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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