Stochastic Multi-objective Distribution Network Reconfiguration Considering Wind Turbines by Ehsan Azad Farsani, Mohsen Zare

“…The objectives of proposed DNR policy are minimization of active power losses, total electrical energy costs, and total emissions of the network. To solve the problem, an improved version of Honey Bee Mating Optimization (IHBMO) algorithm is implemented. …”
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Optimal Design of Integrating Two‐Level Artificial Intelligent With Three Degrees of Freedom‐PDF (TLNF‐3DOFPDF) Controller for AGC of Three‐Area Multi‐Sources Power System... by Getaneh Mesfin Meseret, Rajesh Kumhar, Tarkesh Kumar Mahato, Nishant Kumar, Poonam Lakra, M. D. Mofeed Alam

“…Controller parameters are fine‐tuned using a novel metaheuristic method called the Skill Optimization Algorithm (SOA). The research assesses controller performance using multiple indices Integral of Time‐weighted Squared Error (ITSE), Integral of Squared Error (ISE), Integral of Time‐weighted Absolute Error (ITAE), and Integral of Absolute Error (IAE) and finds that ISE yields the most optimal results. …”
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Hybrid harbor seal and jellyfish optimization technique for selecting the optimal location of hybrid renewable energy system by Radwa S. A. Gad, Hegazy Zaher, H. Al-Wahsh, M. H. Eid, Wael M. AlMetwaly, Islam M. Abdelqawee

“…Abstract Availability of a dependable electricity source is essential for improving living standards. When designing a micro-grid system, two key factors must be considered: cost-effectiveness and service quality. …”
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The Application of PSO in Structural Damage Detection: An Analysis of the Previously Released Publications (2005–2020) by Parsa Ghannadi, Seyed Sina Kourehli, Seyedali Mirjalili

“…Among different algorithms, the particle swarm optimization (PSO) approach has been of the most popular ones. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The algorithm divides the population into two parts, using the non-dominated sorting genetic algorithm II (NSGA-II) and the multi-objective particle swarm optimization algorithm (MOPSO) for solving, with improvements to enhance the algorithm’s performance. …”
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…After 231 iterations of particle swarm optimization algorithm, the optimal value is 6.83650785e-001. …”
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Blind equalization algorithm based on complex support vector regression by Ling YANG, Liang CHEN, Bin ZHAO, Guolong ZHANG, Yuan LI

“…A new blind equalization algorithm for complex valued signals was proposed based on the framework of complex support vector regression(CSVR).In the proposed algorithm,the error function of multi-modulus algorithm (MMA) was substituted into CSVR to construct the cost function,and the regression relationship was established by widely linear estimation,and the equalizer coefficients were determined by the iterative re-weighted least square (IRWLS) method.Different from spliting the complex valued signals into real valued signals used in support vector regression,the Wirtinger’s calculus was used in complex support vector regression to analyze the complex signals directly in the complex regenerative kernel Hilbert space.Simulation experiments show that for QPSK modulated signals,compared with the blind equalization algorithm based on support vector regression,the equalization performance of the proposed algorithm is significantly improved in linear channel and nonlinear channel by choosing appropriate kernel function and iterative optimization method.…”
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Vehicle-routing problem for low-carbon cold chain logistics based on the idea of cost–benefit by Yan Liu, Fengming Tao, Rui Zhu

“…Therefore, based on the idea of cost–benefit, a comprehensive vehicle routing problem optimization model with the objective function of minimizing the cost of unit satisfied customer is presented. …”
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Interior Point Algorithm for Multi-UAVs Formation Autonomous Reconfiguration by Wang Jian-hong, Rana Javed Masood

“…Combined with three kinds of cost functions, nonlinear dynamic equations, and four inequality constraints, one nonlinear multiobjective optimization problem is constructed. …”
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Path Planning in Narrow Road Scenarios Based on Four-Layer Network Cost Structure Map by Ping Wang, Hao Zhang, Youming Tang

“…Second, an improved A* algorithm is employed for global planning to ensure safe navigation. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…In addition, the multi-feature fusion and feature selection method is proposed to enhance the query cost information. The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…In addition, the multi-feature fusion and feature selection method is proposed to enhance the query cost information. The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Training multi-layer binary neural networks with random local binary error signals by Luca Colombo, Fabrizio Pittorino, Manuel Roveri

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Combining Parallel Stochastic Methods and Mixed Termination Rules in Optimization by Vasileios Charilogis, Ioannis G. Tsoulos, Anna Maria Gianni

“…In this study, a combination of termination criteria is proposed, utilizing three different criteria to end the algorithmic process. These criteria include measuring the difference between optimal values in successive iterations, calculating the mean value of the cost function in each iteration, and the so-called “DoubleBox” criterion, which is based on the relative variance of the best value of the objective cost function over a specific number of iterations. …”
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Hybrid Adaptive Sheep Flock Optimization and Gradient Descent Optimization for Energy Management in a Grid-Connected Microgrid by Sri Harish Nandigam, Krishna Mohan Reddy Pothireddy, K. Nageswara Rao, Surender Reddy Salkuti

“…Results demonstrate the efficiency of the proposed hybrid algorithm, achieving substantial improvements in energy efficiency and cost reduction compared to traditional methods like interior point optimization, gradient descent, branch and bound, and a population-based algorithm named Golden Jackal optimization. …”
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MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…To address this issue, this paper proposes MGL-YOLO, a lightweight one-dimensional barcode detection network based on an improved YOLOv8, which aims to achieve a high detection accuracy at low computational cost. …”
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THE ALGORITHM FOR THE TREATMENT OF PATIENTS WITH TREATMENT-RESISTANT HYPERTENSION AT THE OUTPATIENT STAGE by O. S. Kulbachuk, E. V. Sid, O. V. Soloviov, A. V. Piskun

“…Optimization of pharmacotherapy by prescribing drugs with fixed combinations can improve control of drug administration. …”
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Investigating of Machine Learning Based Algorithms for Liver Cirrhosis Prediction by Young Choi, Eunsung Oh

“…These findings not only underscore the superiority of the algorithm but also highlight its potential to revolutionize liver cirrhosis diagnosis and management practices, potentially leading to improved patient outcomes and reduced healthcare costs. …”
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Multiobjective Optimized Routing Protocol for VANETs by Taqwa O. Fahad, Abduladhem A. Ali

“…Fuzzy controllers were employed to assess routes’ costs and their lifetimes. Furthermore, artificial bee colony (ABC) algorithm was used to concurrently optimize all used fuzzy systems and obtain the optimal highest rank of links’ cost values within which the neighbors could be selected as relay nodes in route discovery process. …”
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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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