Harmonization of multi-center diffusion tensor tractography in neonates with congenital heart disease: Optimizing post-processing and application of ComBat by Benjamin Meyers, Vincent K. Lee, Lauren Dennis, Julia Wallace, Vanessa Schmithorst, Jodie K. Votava-Smith, Vidya Rajagopalan, Elizabeth Herrup, Tracy Baust, Nhu N. Tran, Jill V. Hunter, Daniel J. Licht, J. William Gaynor, Dean B. Andropoulos, Ashok Panigrahy, Rafael Ceschin

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Masked face image segmentation using a multilevel threshold with a hybrid fitness function by Nada AbdElFattah Ibrahim, Ehab R. Mohamed, Hanaa M. Hamza, Yousef S. Alsahafi, Khalid M. Hosny

“…This algorithm achieved promising results in several optimization tasks, such as masked face segmentation. …”
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Usability and Perceived Efficiency of an Adaptive Route Optimization Solution for Commercial Vehicles by Florian Anghelache, Nicolae Goga, Constantin Viorel Marian, Dan Alexandru Mitrea, Ionel-Bujorel Pavaloiu

“…This paper details the outcome of a European scientific research and development project, funded to prototype a commercial solution for vehicle fleets. While current route optimization solutions have data sources such as real-time road traffic and weather conditions, our solution was developed to offer companies a proposed plan with adapted optimized routes, considering critical operational requirements, local conditions, and drivers’ driving experience. …”
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A hybrid Genetic Algorithm and Fuzzy Logic approach to ergonomic design of workstations in metal casting operations by Intan Berlianty, Irwan Soejanto, Indun Titisariwati, Favian Ersanta Andhika Putra, Wahyu Tri Utami, Mohamad Kamil Insani

“…Fuzzy Logic processes this data, while GA optimizes the system's parameters for enhanced accuracy and adaptability. …”
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Research on the construction of English vocabulary learning recommendation system based on multi-objective crow search algorithm by Mengli Li

“…Regarding the experiments, we compared MOCSO with traditional single - objective optimization algorithms like Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). 56.4 % of users believe that the recommended vocabulary content meets their deep learning needs, while 18.2 % of learners hope that the system can further improve the practical application ability of vocabulary. …”
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Optimization for Express/Local Train Stop Plans on City Rapid Rail Transit Lines by GUO Jingfan

“…[Objective] To minimize passenger travel time while reducing operational costs for enterprises, it is necessary to identify an optimal balance between these two competing objectives. …”
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Application of stochastic fractal search algorithm in novel harmonic blocking filter design for optimizing harmonic mitigation and hosting capacity in electric distribution systems... by Abdallah Aldosary, Ziad M Ali, Shady H E Abdel Aleem, Ahmed M Zobaa

“…Two multi-objective optimization algorithms: Multi-Objective Artificial Hummingbird (MOAHA) and Multi-Objective Atomic Orbital Search (MOAOS) efficiently determine the ideal HBF design to maximize the system's Harmonic-Constrained Hosting Capacity (HCHC) and minimize PLOSS to support RES while minimizing voltage and current total demand distortion (THDV and TDDI). …”
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Hybrid optimization technique for matrix chain multiplication using Strassen’s algorithm [version 2; peer review: 3 approved, 1 approved with reservations] by Srinivasarao Thota, Rakshitha T, Thulasi Bikku

“…Our approach consists of two key phases: (i) matrix chain order optimization, using a top-down memoized DP approach, we compute the best multiplication sequence, and (ii) hybrid multiplication strategy, we selectively apply Strassen’s algorithm for large matrices (n ≥ 128), reducing the complexity from O(n3) to O(n2.81), while using standard multiplication for smaller matrices to avoid recursive overhead. …”
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A hybrid constrained multi-objective algorithm for dynamic economic emission dispatch by Shuqu Qian, Huihui He, Huihong Wu, Philippe Fournier-Viger, Hui Li, Shoude Huang

“…Dynamic Economic Emission Dispatch (DEED) problems present a critical multi-objective optimization challenge in power systems, requiring simultaneous minimization of conflicting objectives of costs and emissions while addressing complex operational constraints. …”
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Improved Lyrebird optimization for multi microgrid sectionalizing and cost efficient scheduling of distributed generation by Karthik Nagarajan, Arul Rajagopalan, Mohit Bajaj, Valliappan Raju, Vojtech Blazek, Lukas Prokop

“…This paper introduces the Improved Lyrebird Optimization Algorithm (ILOA) for optimal sectionalizing and scheduling of multi-microgrid systems, aiming to minimize generation costs and active power losses while ensuring system reliability. …”
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Autonomous UAV Path Optimization Using Genetic and Multiobjective Evolutionary Algorithms for Effective Data Retrieval in Cache-Enabled Mobile Ad-Hoc WSNs by Umair B. Chaudhry, Chris Ian Phillips

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Hybrid Genetic Algorithm-Based Optimal Sizing of a PV–Wind–Diesel–Battery Microgrid: A Case Study for the ICT Center, Ethiopia by Adnan Kedir Jarso, Ganggyoo Jin, Jongkap Ahn

“…This optimization problem is solved using a hybrid genetic algorithm (HGA). …”
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Maximizing efficiency and performance of water distribution systems through the implementation of optimization algorithms: A comprehensive analysis of valve and chlorine booster pl... by Mohamadreza Najarzadegan, Mehrtash Eskandaripour

“…By employing advanced optimization algorithms, specifically the Genetic Algorithm (GA) and Slime Mould Algorithm (SMA), the research identifies optimal configurations across two benchmark networks, Jowitt and Xu and GoYang. …”
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Cost-Based Modeling for Optimal Energy Management of Smart Buildings with Renewable Energy Resources and Electric Vehicles Using a Scenario-Based Algorithm by Hanlie Cheng

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Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

“…So, this study integrates the ANFIS (adaptive neuro-fuzzy inference system) and ELM (extreme learning machine) machine learning models with three optimization algorithms, i.e., WCA (water cycle algorithm), PSO (particle swarm optimization), and GWO (grey wolf optimizer) to precisely estimate the CS of fiber-reinforced concrete (FRC) containing SiO2. …”
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Ammonia and ethanol detection via an electronic nose utilizing a bionic chamber and a sparrow search algorithm-optimized backpropagation neural network. by Yeping Shi, Yunbo Shi, Haodong Niu, Jinzhou Liu, Pengjiao Sun

“…Response data are classified and regressed using a sparrow search algorithm (SSA)-optimized backpropagation neural network (BPNN). …”
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Comparison, optimization and application of multiple prestack inversion algorithm for intermediate basic volcanic reservoirs: A case study of Huoshiling Formation in Chaganhua area by LI Ruilei,CAO Lei,FAN Xuepei,FENG Xiaohui,LI Ning

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Coordinated Control of the Volt-Var Optimization Problem Under PV-Based Microgrid Integration into the Power Distribution System: Using the Harmony Search Algorithm by Gulcihan Ozdemir, Pierluigi Siano, Smitha Joyce Pinto, Mohammed AL-Numay

“…The harmony search (HS) algorithm, which is a metaheuristic-based optimization algorithm, was used to determine global optimum settings of related devices to operate efficiently under changing conditions. …”
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Comprehensive improvement of energy efficiency and indoor environmental quality for university library atrium—A multi-objective fast optimization framework by Shen Xu, Yongzhong Chen, Jianlin Liu, Jian Kang, JinFeng Gao, Yuchen Qin, Wenjun Tan, Gaomei Li

“…Finally, a multi-objective fast optimization framework coupled with machine learning algorithms was used to achieve the optimal design of university library atrium. …”
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Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis by Yi Xu, Ying Mao, Xiaoting Hua, Yan Jiang, Yi Zou, Zhichao Wang, Zubi Liu, Hongrui Zhang, Lingling Lu, Yunsong Yu

“…By constructing training and test datasets on all SNPs, intersected SNPs, and randomly generated SNPs, we developed a Machine learning (ML) framework using twelve different algorithms. Then, we compared the performances of the various ML models and used the SHapley Additive exPlanations (SHAP) framework to decipher why and how decisions are made within the optimal algorithm. …”
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