Optimizing Sentiment Analysis of Digital Wayang Viewer Comments using SMOTE and the Naïve Bayes Algorithm by mawar hardiyanti, Maria Karmelia Fajarlestari

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Enhancing Surgery Scheduling in Health Care Settings With Metaheuristic Optimization Models: Algorithm Validation Study by João Lopes, Tiago Guimarães, Júlio Duarte, Manuel Santos

“…By implementing these AI-driven strategies, hospitals can minimize patient wait times, maximize resource use, and enhance surgical outcomes through improved planning. This development highlights how AI algorithms can effectively adapt to changing health care environments, having a transformative impact.…”
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A Modified Horse Herd Optimization Algorithm and Its Application in the Program Source Code Clustering by Bahman Arasteh, Peri Gunes, Asgarali Bouyer, Farhad Soleimanian Gharehchopogh, Hamed Alipour Banaei, Reza Ghanbarzadeh

“…This paper applied the horse herd optimization algorithm, a distinctive population-based and discrete metaheuristic technique, in clustering software modules. …”
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Unmanned Aerial Vehicle Path Planning Based on Sparrow-Enhanced African Vulture Optimization Algorithm by Weixiang Zhu, Xinghong Kuang, Haobo Jiang

“…Drones can improve the efficiency of point-to-point logistics and distribution and reduce labor costs; however, the complex three-dimensional airspace environment poses significant challenges for flight paths. …”
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Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling by Linghao Ren, Xinyue Li, Renjie Song, Yuning Wang, Meiyun Gui, Bo Tang

“…Next, we create a dynamic adaptive public transit optimization model using an entropy weight-TOPSIS decision framework coupled with an improved simulated annealing algorithm (ISA-TS), achieving coordinated suburban–urban network optimization while maintaining 92.3% solution stability under simulated node failure conditions. …”
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A multi-objective optimization-based ensemble neural network wind speed prediction model by Haoyuan Ma, Chang Liu, Ziyuan Qiao, Yuan Liang, Hongqing Wang

“…Built upon the NSGA-II framework, NS-ADPOA enhances offspring generation by leveraging a probabilistic error-driven fusion of Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), combining their strengths in local and global search, respectively. …”
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Optimal Design of Short Fiber Bragg Grating Using Bat Algorithm With Adaptive Position Update by Ahmed Al-Muraeb, Hoda Abdel-Aty-Zohdy

“…We propose a new method to optimally design short triangular-spectrum fiber Bragg gratings (TS-FBGs), using the metaheuristic bat algorithm (BA). …”
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An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks by Mohit Kumar, Ashwani Kumar, Sunil Kumar, Piyush Chauhan, Shitharth Selvarajan

“…To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. …”
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The Active and Reactive Power Generation Reduction Based on Optimal location of UPFC Based on Genetic Algorithm by Sana Khalid Abd Al Hassan, Firas Mohammed Tuaimah, Yasser Nadhum Abd, Ali Adil Al-Lami

“… The Unified Power Flow Controller (UPFC) is a most complex power electronic device, which can simultaneously control a local bus voltage and optimize power flows in the electrical power transmission system. …”
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Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm by Chunfeng Jiang, Zegang Niu, Jingru Qu, Yulan Zhao, Amin Rezaeipanah

“…Specifically, the proposed algorithm demonstrates a 9.2% improvement in average influence spread over the best existing method, while effectively addressing the trade-offs between influence, fairness, and complexity.…”
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Multiscale Modeling and Reconstruction of Joint Motion: Finite Element Optimization Based on Particle Swarm Algorithm by Jiaju Zhu, Zhong Zhang, Runnan Liu, Meixue Ren, Guodong Ma

“…Additionally, iterative reconstruction decreased the error in the knee region by approximately 30% compared to non-iterative methods. The optimization process facilitated by the particle swarm algorithm revealed that most particles achieved high fitness levels after the initial iteration, and a considerable proportion shifted to the foreground region during the second iteration once fitness values dropped below 0.2. …”
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Integration of Solar Energy into Smart Grids: A Cost-Effective Framework for Sustainable Power Management by Ali Raza Larik, Rahool Rai, Kashif Ahmed, Halar Mustafa

“…This system reduces consumer unit costs, ensures a steady electricity supply, enhances the current grid by feeding back excess power, and employs a smart algorithm to select the optimal power source from among the various options. …”
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ISCCO: a deep learning feature extraction-based strategy framework for dynamic minimization of supply chain transportation cost losses by Yangyan Li, Tingting Chen

“…This research proposed a new framework named Intelligent Supply Chain Cost Optimization (ISCCO). ISCCO integrates deep learning with advanced optimization algorithms. …”
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Research on Impact of Planned Path Length and Yaw Cost on Collaborative Search of Unmanned Aerial Vehicle Swarms by Heng Zhang, Wenyue Meng, Yanan Liu, Guanyu Liu, Jian Zhang

“…To address the unclear impacts of a planned path length and yaw cost on search performance in large-scale Unmanned Aerial Vehicle (UAV) swarm collaborative search scenarios under complex and dynamic environments, a path grid determination algorithm is proposed, transforming the path-planning problem into an optimal waypoint selection problem, enabling UAVs to make rapid decisions using the Particle Swarm Optimization (PSO) algorithm. …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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Research on the A* Algorithm Based on Adaptive Weights and Heuristic Reward Values by Xizheng Wang, Gang Li, Zijian Bian

“…Secondly, a radial basis function is used to act as the adaptive weighting coefficient of the heuristic function and adjust the proportion of heuristic functions in the algorithm accordingly to the search distance. Again, optimize the cost function using the reward value provided by the target point so that the current point is away from the local optimum. …”
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Advanced Sales Route Optimization Through Enhanced Genetic Algorithms and Real-Time Navigation Systems by Wilmer Clemente Cunuhay Cuchipe, Johnny Bajaña Zajia, Byron Oviedo, Cristian Zambrano-Vega

“…Although GAAM-TS incurs higher computational costs, it is best suited for offline or batch optimization scenarios, whereas GA-AM provides a balanced alternative for near-real-time applications. …”
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A Shortest Distance Priority UAV Path Planning Algorithm for Precision Agriculture by Guoqing Zhang, Jiandong Liu, Wei Luo, Yongxiang Zhao, Ruiyin Tang, Keyu Mei, Penggang Wang

“…To address these challenges, this study proposes an enhanced Q-learning algorithm designed to optimize UAV path planning by combining static and dynamic obstacle avoidance features. …”
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A Hybrid ARO Algorithm and Key Point Retention Strategy Trajectory Optimization for UAV Path Planning by Bei Liu, Yuefeng Cai, Duantengchuan Li, Ke Lin, Guanghui Xu

“…An effective path planning algorithm can greatly improve the operational efficiency of UAVs in complex environments like urban and mountainous areas, thus offering more extensive coverage for various tasks. …”
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Robust multi-objective optimization for water flooding under geological uncertainty by Abobakr Sori, Mohammad Sharifi, Nooshin Jabari

“…By employing a multi-objective optimization (MOO) algorithm, we aim to minimize the sensitivity of objective functions to geological variability. …”
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