Optimization, Design, and Implementation of Biodiversity-Focused Fisheries Survey Stations: A Case Study of the Coastal Waters of Maoming by Yuexiu DENG, Yongheng HUANG, Jianyu DONG, Ning CHEN, Jing ZHANG, Xuefeng WANG

“…This package, based on a genetic algorithm, can determine the optimal stratification, sample size, and sample allocation to meet precision constraints in the presence of multiple stratification variables and multiple target variables. …”
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Optimising test intervals for individuals with type 2 diabetes: A machine learning approach. by Sasja Maria Pedersen, Nicolai Damslund, Trine Kjær, Kim Rose Olsen

“…<h4>Objective</h4>To demonstrate the potential of ML to guide resource allocation and tailored disease management, this study aims to predict the optimal testing interval for monitoring blood glucose (HbA1c) for patients with Type 2 Diabetes (T2D). …”
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Wireless sensor network positioning technology based on improved sampling box and fuzzy reasoning by Ningyun Dan, Lun Zhao, Wenjin Pan, Yan Cai

“…The research results indicate that on the UCI and MIT Reality datasets, the Rand coefficient of the fuzzy clustering algorithm optimized for time series is stable at 0.89 when the weight allocation index is 5, which is superior to other comparative algorithms. …”
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Improving Secrecy Capacity in the Face of Eavesdropping in SWIPT CIoT Networks With Actor-Critic DRL by Nada Abdel Khalek, Walaa Hamouda

“…We then propose a deep reinforcement learning (DRL) approach to determine the optimal strategy for secure transmission and resource allocation. Specifically, we derive the instantaneous secrecy rate and employ a deep deterministic policy gradient (DDPG) algorithm with a lightweight actor-critic architecture to efficiently address dynamic channel occupancy, EH opportunities, and fading conditions. …”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…These improvements contribute to enhanced operational efficiency and better human-machine collaboration by minimizing unnecessary interventions and optimizing resource allocation.…”
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Runoff Prediction and Uncertainty Analysis for Xijiang River Basin Based on CMIP6 Climate Scenarios by WU Huiming, YAN Meng, ZHOU Shuai

“…The results can provide an important scientific basis for water management agencies to plan, allocate, and utilize water resources reasonably in the basin, thereby reducing the influence of GCMs and SSPs uncertainty on runoff prediction uncertainty.…”
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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…Numerical experiments demonstrate RLEHBA’s superior performance over State-of-the-Art algorithms on the CEC 2017 benchmark. A case study of China’s 2026 pork regulation confirms the system’s practical value in stabilizing the supply-demand balance and optimizing resource allocation. …”
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A Reconfigurable Access Scheme for Massive-MIMO MTC Networks by Atoosa Dalili Shoaei, Duc Tuong Nguyen, Tho Le-Ngoc

“…At the beginning of each frame, the base station decides how to partition the two segments, the resource allocation in the grant-based segment and the access probabilities in the grant-free segment to maximize the expected throughput based on the device traffic profiles. …”
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Optimizing Zakat Distribution with GIS and Data Mining in Community Empowerment at BAZNAS Deli Serdang by Sinta Dara Efita, Triase Triase

“…Tanjung Morawa was identified as the district with the highest number of zakat recipients, namely 239 people, which shows a significant need. The K-Means algorithm plays an important role in identifying areas that need help, so this Geographic Information System-based grouping is proven to improve the efficiency of zakat resource allocation. …”
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Network-, Cost-, and Renewable-Aware Ant Colony Optimization for Energy-Efficient Virtual Machine Placement in Cloud Datacenters by Ali Mohammad Baydoun, Ahmed Sherif Zekri

“…The approach integrates real-time solar energy availability, dynamic PUE modeling, and multi-criteria decision-making to enable environmentally and cost-efficient resource allocation. The experimental results show that NCRA-DP-ACO reduces power consumption by 13.7%, carbon emissions by 6.9%, and live VM migrations by 48.2% compared to state-of-the-art methods while maintaining Service Level Agreement (SLA) compliance. …”
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Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning by A. Ahajjam, M. Allgaier, R. Chance, E. Chukwuemeka, J. Putkonen, T. Pasch

“…First, NASA’s Fire Information for Resource Management System (FIRMS) dataset spanning +20 years is processed using a spatio-temporal clustering algorithm to create refined wildfire datasets. …”
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Context-Aware Beam Selection for IRS-Assisted mmWave V2I Communications by Ricardo Suarez del Valle, Abdulkadir Kose, Haeyoung Lee

“…This approach enables optimized resource allocation and significantly improves coverage, data rate, and resource utilization compared to conventional methods.…”
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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

“…To address these challenges, deep learning technologies have emerged as a promising solution for the accurate and timely identification of plant diseases and pests, thereby reducing crop losses and optimizing agricultural resource allocation. By leveraging its advantages in image processing, deep learning technology has significantly enhanced the accuracy of plant disease and pest detection and identification. …”
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Distributed Optimization for Mobile Robots under Mobile Edge Computing Environment by Hui Luo, Quan Yin

“…The mmW base station provides reliable communication services for MRs under the coverage of information cloud (IC). We design a joint resource and power allocation strategy aimed at minimizing network energy consumption. …”
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SUSTAINABLE BACKUP POWER WITH V2G INTEGRATION IN HYBRID MICROGRID by B. Karthikeyan, K. S. Yamuna, K. Padmapriya, S. Priyadharsini, K. Sabareeshwari, P. Sree Mathi

“…The gadget ensures uninterrupted energy for critical systems which includes the Intensive Care Unit and emergency gadget whilst deprioritizing non-vital loads to optimize aid allocation. Advanced manage algorithms dynamically manage power flows ensuring effective operation even in the face of renewable power variability. …”
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A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance by Wenhui Zhang, Fan Gao, Shurui Sun, Qiuying Yu, Jinjun Tang, Bohang Liu

“…This paper focuses on efficiently allocating parking spaces to the demanders. A double-objective model is proposed that considers both the utilizing rate and the walking distance. …”
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Artificial intelligence in project management: A bibliometric analysis by Nurkhat Ibadildin, Zhaxat Kenzhin, Gaukhar Yeshenkulova, Rymkul Ismailova, Assel Nurguzhina, Samalgul Nassanbekova, Aiman Kadyrova

“…The analysis maps the evolution of AI-driven project management practices, focusing on resource allocation, risk management, and scheduling optimization. …”
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Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios by Jie Chen, Kai Xiao, Kai You, Xianguo Qing, Fang Ye, Qian Sun

“…At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. …”
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Artificial intelligence analysis in cyber domain: A review by Liguo Zhao, Derong Zhu, Wasswa Shafik, S Mojtaba Matinkhah, Zubair Ahmad, Lule Sharif, Alisa Craig

“…This method permits for the allocation of multiple log source types through a sliding time window and provides a scalable solution, which is a much-needed function.…”
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Predicting the Energy Consumption in Chillers: A Comparative Study of Supervised Machine Learning Regression Models by Mohamed Salah Benkhalfallah, Sofia Kouah, Saad Harous

“…In particular, accurate regression-based energy forecasting of the energy consumption in various sectors plays a key role in informed decision-making, efficiency improvements, and resource allocation. This paper examines the application of artificial intelligence and supervised machine learning techniques to modeling and predicting the energy consumption patterns in the smart grid sector of a commercial building located in Singapore. …”
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