Implications of algorithmic bias in AI-driven emergency response systems by Katsiaryna Bahamazava

“…Unlike existing research, which mostly addresses technical or ethical aspects in isolation, our approach integrates economic theory with algorithmic fairness to quantify and systematically analyze how biases in data quality and algorithm design impact resource allocation efficiency, response time equity, healthcare outcomes, and social welfare. …”
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Anomaly Detection and Root Cause Analysis for Energy Consumption of Medium and Heavy Plate: A Novel Method Based on Bayesian Neural Network with Adam Variational Inference by Qiang Guo, Fenghe Li, Hengwen Liu, Jin Guo

“…Anomaly detection and root cause analysis of energy consumption not only optimize energy use and improve equipment reliability but also contribute to green and low-carbon development. …”
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Transactive energy management for efficient scheduling and storage utilization in a grid-connected renewable energy-based microgrid by Peter Anuoluwapo Gbadega, Olufunke Abolaji Balogun

“…This study presents an advanced Transactive Energy Management (TEM) approach employing the Slime Mould Algorithm (SMA) to optimize scheduling and storage utilization in grid-connected renewable energy microgrids. …”
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A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

“…The experimental results show that the proposed algorithm can achieve a nearly 10 percent mean average precision value improvement with nearly half the model size, compared with counterparts. …”
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An Efficient Resource Allocation Algorithm for Task Offloading in the Internet of Vehicles by Ahmad Salehi, Sadoon Azizi

“…Simulation results demonstrate that the proposed algorithm reduces memory costs and penalties from rejected tasks, while improving overall system profit. …”
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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 framework exhibits excellent capability in multi-objective collaborative optimization. The ENSGA-II algorithm outperforms baseline algorithms significantly across performance metrics, achieving a hypervolume (HV) value of 1.0771 (improving by 72.35% to 109.82%) and an average inverted generational distance (IGD) of 0.0295, markedly better than those of comparison algorithms (ranging from 0.0893 to 0.2714). …”
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The performance evaluation of chaotic maps in estimating the shape parameters of radial basis functions to solve partial differential equations by Javad Alikhani Koupaei, Mohammad Javad Ebadi, Majid Iran Pour

“…Purpose: This study aims to investigate the potential of chaotic optimization algorithms in improving performance compared to other optimization methods, focusing on determining the appropriate shape parameter of radial basis functions for solving partial differential equations.Methodology: In this research, a two-stage process is employed where the Kansa method, based on meshless local techniques, is combined with the FCW method. …”
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A modified instantaneous reactive power algorithm for shunt compensation by Namrata Mishra, S. P. Gawande, Shailesh Deshmukh, K. T. Tan, Khalid Ansari, T. M. Yunus Khan, Naif Almakayeel, Wahaj Ahmad Khan

“…This paper proposes a new approach of IRP p-q theory for reference current generation in Distribution Static Compensator (DSTATCOM) in 3-ph, 4-wire distribution system with unbalanced, distorted source and non-linear loads, both. Algorithm is developed based on fundamental concept of equal current criteria to handle magnitude unbalance, improved formulations using time synchronization of source phase-a voltage for compensating phase unbalance, and fundamental positive sequence extraction to eliminate distortion in the source currents. …”
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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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Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction by QIAN Yuchen, NIE Ting, HUA Yanming, XU Shiying, GUO Sheng, ZHANG Xin, LUO Xiaohu, LIU Yanan

“…Artificial intelligence algorithms can be continuously optimized based on prior knowledge and real-time data, which significantly improves the prediction efficiency of antibacterial peptides and reduces research and development costs. …”
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Cost-effectiveness analysis of best management practices for non-point source pollution in watersheds: A review by CHANG Jian, YU Jie, WANG Fei’er, ZHENG Siyuan

“…According to the accounting results, two optimization criteria, namely cost minimization and benefit maximization, were employed to screen for the most cost effective measures. …”
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Hierarchical guided manta ray foraging optimization for global continuous optimization problems and parameter estimation of solar photovoltaic models by Zhentao Tang, Kaiyu Wang, Lan Zhuang, Mingxin Zhu, Yongxuan Yao, Huiqin Chen, Jing Li, Xiaoxiang Wu, Shangce Gao

“…Abstract The manta ray foraging optimization (MRFO) algorithm has gained widespread application in engineering problems due to its notable performance and low computational cost. …”
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Adaptive Differential Evolution Algorithm for Forward Position Solution of Parallel Mechanism by Yi Jian

“…Aiming at the basic DE algorithm has some weaknesses,such as evolutionary stagnation and falling into local extremum domains,an adaptive strategy for introducing new individuals is presented to improve its optimization performance. …”
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Effects of Reliability Index on Optimal Configuration of Hybrid Solar/Battery Energy System by Optimization Approach: A Case Study by Hao Liu, Baojia Wu, Akbar Maleki, Fathollah Pourfayaz, Roghayeh Ghasempour

“…The objective of the current work is to the optimal configuration of a stand-alone hybrid photovoltaic/battery energy storage system with the help of an efficient metaheuristic algorithm, improved harmony search, to supply electrical of a residential load in Iran. …”
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EPRSA: interference resource scheduling algorithms for air-ground communication networks by Wenpeng Wu, Zhenhua Wei, Haiyang You, Xiaoqing Li, Jianwei Zhan, Zhaoguang Zhang

“…Based on this, this paper proposes the interference link margin in the mathematical model and normalizes and quantifies the optimization objectives. Strategies such as cycle and initial quantity selection, elastic initialization, double tabu power scheduling, and jammer conversion are designed to improve the scheduling ability of the Elastic Parallel Random Search Algorithm (EPRSA) in terms of system operation duration and interference cost. …”
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Capuchin search algorithm based task scheduling in cloud computing environment by Sivakumar Ramu, Rameshkumar Ranganathan, Ramakrishnan Ramamoorthy

“…Then, we develop a modified capuchin search (MCS) algorithm for priority based optimal task scheduling which minimize makespan and improve resource utilization. …”
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Qualitative Simulation Algorithm for Resource Scheduling in Enterprise Management Cloud Mode by Jiaohui Yu

“…Aiming at the problem of resource scheduling optimization in enterprise management cloud mode, a customizable fuzzy clustering cloud resource scheduling algorithm based on trust sensitivity is proposed. …”
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Nonlinear Optimization and Adaptive Heuristics for Solving Irregular Object Packing Problems by János D. Pintér, Ignacio Castillo, Frank J. Kampas

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Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting by Zihan CHEN, Wei TENG, Xuefeng XU, Xian DING, Yibing LIU

“…In order to make full use of the prior relationships among data features and improve the prediction accuracy of medium and long term wind power at wind farms, a medium and long term wind power prediction model based on graph convolution neural network (GCN), wind velocity differential fitting (DF), and particle swarm optimization (PSO) is proposed. …”
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Precise wind allocation scheme decision based on attraction-repulsion algorithm by NI Jingfeng, CHEN Dunwei, LIU Yujiao

“…Performance test results showed that AROA had a significant advantage in comprehensive optimization performance compared to Genetic Algorithm (GA), Simulated Annealing-Improved Particle Swarm Optimization (SA-IPSO), and Monotonic Basin Hopping (MBH). …”
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