Integration of artificial intelligence and advanced optimization techniques for continuous gas lift under restricted gas supply: A case study by Leila Zeinolabedini, Forough Ameli, Abdolhossein Hemmati-Sarapardeh

“…In addition, the net present value (NPV) serves as the objective function. To optimize the selected input variables, including tubing inside diameter, gas injection rate, and separator pressure, various optimization algorithms such as particle swarm optimization (PSO), ant colony optimization (ACO), genetic algorithm (GA), and a Novel optimization algorithm in a gas-lift study called grey wolf optimization (GWO), were utilized considering the constraint of the limited available gas. …”
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Optimizing Transportation Costs: Enhancing Logistics Efficiency and Resource Utilization in Dynamic Environments by Cao Ngoc Anh, Tran Bich Thao, Tran Ba Hung, Trinh Thu Huong, Nguyen Viet Hung

“…However, as the logistics industry continues to grow and transaction volumes increase, transportation scenarios are expected to become more complex, and customer requirements more diverse. …”
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Multi-Robot Navigation System Design Based on Proximal Policy Optimization Algorithm by Ching-Chang Wong, Kun-Duo Weng, Bo-Yun Yu

“…We use topological maps to simplify the map representation for multi-robot path planning so that the proposed method can perform path planning for more robots in more complex environments. The proximal policy optimization (PPO) is used as the algorithm for deep reinforcement learning. …”
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Decomposition-Based Multiobjective Evolutionary Optimization with Adaptive Multiple Gaussian Process Models by Xunfeng Wu, Shiwen Zhang, Zhe Gong, Junkai Ji, Qiuzhen Lin, Jianyong Chen

“…However, this approach only uses one standard Gaussian process model with fixed variance, which may not work well for solving various multiobjective optimization problems (MOPs). To alleviate this problem, this paper introduces a decomposition-based multiobjective evolutionary optimization with adaptive multiple Gaussian process models, aiming to provide a more effective heuristic search for various MOPs. …”
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Portfolio Optimization under ESG Constraints: Markowitz Model vs. Index Model by Wu Mengjie

“…The results show that MM is more effective in integrating ESG constraints, which can improve the portfolio ESG score and reduce the exposure to high carbon emission industries, and is more suitable for investors who prioritize sustainability, while IM is more suitable for investors who adopt passive investment strategy. …”
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Dynamic Parameter Optimization and Experimental Study of Tuned Slab Damper on Metro Systems by Guang-Hui Xu

“…With the increase of axle weight and speed, the interaction between vehicles and the track becomes more and more intense, and the problem of wheel-rail dynamic action is more serious. …”
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Evaluation and comparison of methods for neuronal parameter optimization using the Neuroptimus software framework. by Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar, Gábor Farkas, Szabolcs Káli

“…Finding optimal parameters for detailed neuronal models is a ubiquitous challenge in neuroscientific research. …”
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An optimization model of computer network security based on GABP neural network algorithm by Jiangang Wang, Xiaoyan Wang

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Efficiently computing Pareto optimal G-skyline query in wireless sensor network by Leigang Dong, Guohua Liu, Xiaowei Cui, Quan Yu

“…How to mine vital information from these large amount of data is very important for decision-making. Aiming at mining more interesting information for users, the skyline technology has attracted more attention due to its widespread use for multi-criteria decision-making. …”
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The VSAS approach gives the Best MPPT for Solar Energy Sources by Nacer Kouider Msirdi, Bechara Nehme

“…More and more MPPT (Maximum Power Point Tracking) algorithms are in competition to maximize energy extracted from PV systems. …”
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Optimizing Treatment Strategies for Distal Radius Fractures in Osteoporosis: A Comparative Review by Eric J. Gullborg, Jason H. Kim, Caitlin M. Ward, Xavier C. Simcock

“…Conversely, nonoperative management may be more suitable for patients with lower functional demands or higher surgical risks, despite the increased risk of malunion. …”
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An Analytical Approach to Power Optimization of Concentrating Solar Power Plants with Thermal Storage by Andrii Cheilytko, Spiros Alexopoulos, Andriy Pozhuyev, Oliver Kaufhold

“…In addition, the use of additional factors and the combination of the proposed method with existing numerical methods allows for more refined optimization, which allows for the more accurate selection of the capacity for specific geographical conditions. …”
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Optimization of Village Grouping Using Comparison of K-Means and K-Medoids Methods by Eza Rahmanita, Yeni Kustiyahningsih, Putri Nihayatul Husna, Adhelia Firdaus Al-Najib

“…The results show that K-Medoids offers more stable clustering, especially in the presence of outliers, while K-Means is more efficient in computation. …”
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Exploring Optimal Group Sizes for Learning in Medical Simulation: A Systematic Review by Cassandra Mackey, Simi Jandu, James Fidrocki, Tyler Raduzycki, Jennifer Carey

“…For procedural skills, groups of 2 to 4 are most effective, and effectiveness declines with more than 6 participants. Smaller groups allow for more hands-on learning and cognitive engagement. …”
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Optimizing Group Multi-Factor Authentication for Secure and Efficient IoT Device Communications by Salem AlJanah, Ning Zhang, Siok Wah Tay

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Optimization Path and Design of Intelligent Logistics Management System Based on ROS Robot by Ruijie Wu

“…In addition, compared with the traditional transportation method, the daily transportation weight of each robot is up to 310.1% and the monthly profit is up to 171%, which shows that the intelligent logistics management system designed in this paper is more efficient in logistics and transportation and can bring more profits.…”
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Homeostatic synaptic normalization optimizes learning in network models of neural population codes by Jonathan Mayzel, Elad Schneidman

“…Incorporating more biological features and utilizing synaptic normalization in the learning process, results in accurate models that are more efficient. …”
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Optimal robust monetary policy in a small open emerging-market economy by Marine Charlotte André, Sebastián Medina Espidio

“…On the other hand, when it has a preference for robustness only for the UIP, the central bank should be more aggressive to demand and cost-push shocks. Third, a sensitivity analysis suggests that conducting a global robust optimal monetary policy with the same misspecification in all equations is limited due to the persistence of inflation, the low exchange-rate pass-through and the need to anchor inflation expectations. …”
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Determination of Optimal Parameters of the Ground Filling During the Laying of Power Cable Lines by M. E. Vysotski

“…One of the ways to improve cooling conditions is to use a special backfill with lower thermal resistance values, which is more expensive than the ground one. This raises the question of the feasibility of such a solution, since more expensive materials may not pay off in some cases. …”
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Numerical analysis and optimization of the residual stresses distribution induced by cold expansion technique by Abdelghani Baltach, Abdelkader Djebli, Mostefa Bendouba, El Hadj Besseghier, Abdelkrim Aid

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