Research on Constraint Processing Method of High-dimensional Optimization Operation Problem of Cascade Reservoirs by Zhongzheng HE, Shuliang LI, Wei HUANG, Feng YAN, Jisi FU, bin XIONG

“…The intelligent optimization algorithm is a multidimensional linkage random search, which boasts a vast optimization space but suffers from low optimization efficiency. Therefore, this study introduces a constraint processing approach that integrates a penalty function with nested DPSA–POA and intelligent algorithms and applies it to the optimal flood control operation problem of cascade reservoirs in the middle reaches of the Ganjiang River, with decision variables extending to 2196 dimensions. …”
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Analysis of value-based healthcare (VBHC) framework by incremental cost-effectiveness of surgical and therapeutic interventions: a retrospective study at tertiary private health gr... by Mona Khamis, Zainab Almoosa, Marie Santos, Engineer Diaa Kamal, Suhail Yaghmor, Muhammad Daniyal, Abbas Al Mutair

“…Additionally, ICER values were positively associated with better functional outcomes in MS and stroke patients, with mobility (b = 1.027, p = 0.003) and activity (b = 1.768, p < 0.001). …”
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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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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…The Kolmogorov-Arnold Network (KAN) is a computational framework rooted in the Kolmogorov-Arnold representation theorem, which states that any continuous function of multiple variables can be expressed as a superposition of univariate functions. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In addition, the closed-form solutions of the optimized variables are obtained. Simulation results demonstrate that the proposed collaborative training scheme based on D2D can reduce the impact of heterogeneity on FL model performance and IRA can effectively reduce energy consumption while simultaneously enhancing training efficiency of FL.…”
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Topologic Reorganization of White Matter Connectivity Networks in Early-Blind Adolescents by Zhifeng Zhou, Long Qian, Jinping Xu, Yumin Lu, Fen Hou, Jingyi Zhou, Jinpei Luo, Gangqiang Hou, Wentao Jiang, Hengguo Li, Xia Liu

“…Moreover, decreased regional efficiency and increased nodal path length in some visual and default-mode areas were strongly associated with the period of blindness in EBA cohort, suggesting that the function of these areas would gradually weaken in the early-blind brains. …”
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Modeling and optimizing the atmospheric water harvesting System: Application of PAN-PDMS polymeric membrane by Sepehr Sanaye, Pouya Rezvani Gil Kalaee, Javad Mahmoudimehr

“…The water production rate and the total annual cost rate were considered as two objective functions. Also, five design variables are selected after considering their effects on the objective functions. …”
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Time-Jerk Optimal Robotic Trajectory Planning Under Jerk and Continuity Constraints via Convex Optimization by Chen Qian, Jianjun Yao, Yikun Zhang

“…Additionally, the objective function is improved to optimize both time and joint jerk simultaneously. …”
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Research on Side Lobe Suppression of Time-Modulated Sparse Linear Array Based on Particle Swarm Optimization by Lei Liang, Jie Sun, Hailin Li, Jialing Liu, Yachao Jiang, Jianjiang Zhou

“…An efficient pattern synthesis approach is proposed for the synthesis of a time-modulated sparse linear array (TMSLA) in this paper. …”
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A New Optimization Approach for Maximizing the Photovoltaic Panel Power Based on Genetic Algorithm and Lagrange Multiplier Algorithm by Mahdi M. M. El-Arini, Ahmed M. Othman, Ahmed Fathy

“…The technique which is based on objective function represents the output power of the PV panel and constraints, equality and inequality. …”
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A Three-Block Inexact Heterogeneous Alternating Direction Method of Multipliers for Elliptic PDE-Constrained Optimization Problems with a Control Gradient Penalty Term by Xiaotong Chen, Tongtong Wang, Xiaoliang Song

“…In some practical applications, it is necessary to smooth the control variables and suppress their large fluctuations, especially at the boundary. …”
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Optimization of Aerodynamic Design of a Winged UAV Through Genetic Algorithms and Large Eddy Simulation by Mohammad Javad Ebrahimi, Mahmoud Pasandidehfard, Ali Esmaeili, Mohammad Hossein Moghimi Esfandabadi

“…Optimization was conducted for six variables in a single stage, with 25 tests performed. …”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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Optimal tuning of multi-PID controller using improved CMOCSO algorithm by Ying Hu, Xiongyan Liu, Hao Chen

“…In this model, the parameters are designated as decision variables, the performance index serves as the objective function, and the stability constraints of the system are incorporated. …”
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Performance Investigation of Coated Carbide Tools in Milling Procedures by Paschalis Charalampous

“…The optimization of the manufacturing conditions in milling processes composes a crucial task for enhancing machining efficiency and extending the tool’s lifespan. This study presents an investigation of the cutting tool’s performance under varying machining parameters via the generation of an experimental dataset that was obtained through laboratory-controlled milling operations. …”
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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Analytical expressions for key QoS indicators (delay, variability, loss, energy consumption) as functions of the shift parameter are derived, and a multi-factor reward function is constructed. …”
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Understanding the Role of Organic Hole Transport Layers on Pinhole Blocking and Performance Improvement in Sb2Se3 Solar Cells by Thomas P. Shalvey, Christopher H. Don, Leon Bowen, Tim D. Veal, Jonathan D. Major

“…After successive record‐efficiencies using a range of device structures, spiro‐OMeTAD has emerged as the default hole transport material (HTM), however, the function of HTM layers remains poorly understood. …”
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Mi-DETR: For Mitosis Detection From Breast Histopathology Images an Improved DETR by Fatma Betul Kara Ardac, Pakize Erdogmus

“…In the decoder layer, unnecessary model parameters have been filtered out using a layer reduction strategy to improve model efficiency and reduce computational costs. Additionally, a more stable model has been obtained by using the CIoU loss function instead of the L1+GIoU loss function used in the DETR model. …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…This prominent research gap has been addressed in this paper by introducing Logical Social Group Optimization (LSGO), a logic-based binarized variant of Social Group Optimization (SGO) that leverages Boolean logic for improved efficiency. In LSGO, after the binarization by replacing the arithmetic operators with logical operators, one of the variables gets cancelled out. …”
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Comparison of river and drinking water quality of infiltration intakes based on statistical colour data by Yalaletdinova Alina, Malkova Maria, Vozhdaeva Margarita, Serebryakov Pavel, Kantor Evgeny

“…The construction of cross-correlation functions on the average monthly values of the indicator for the whole observation period and in the model year showed that there is a relationship between the colour of river water and drinking water. …”
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