Perbandingan Metode Penyelesaian Permasalahan Optimasi Lintas Domain dengan Pendekatan Hyper-Heuristic Menggunakan Algoritma Reinforcement-Late Acceptance by Anang Firdaus, Ahmad Muklason, Vicha Azthanty Supoyo

“…In improving performance, this study examines the effect of the adaptation of the Reinforcement Learning (RL) algorithm as LLH selection combined with the Late Acceptance algorithm as a move acceptance. …”
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Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning by Lin Song, Xingwei Wu, Mengjia Xu, Ling Xue, Xun Yu, Zongqi Cheng, Chenrong Huang, Liyan Miao

“…Thus, the purpose of this study was to develop and optimize models by Cox regression and machine learning algorithms to predict the risk of aGVHD in which cyclosporin A exposure and common clinical factors were included as variables. …”
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Energy-Efficient Dual-Iteration Power Allocation for Two-Phase Relay System with Massive Antennas by Long Zhao, Wei Xiang, Jie Mei, Hui Zhao, Hang Long, Lin Li

“…Numerical results show that the proposed DIPA algorithms can greatly improve EE while guaranteeing spectrum efficiency (SE) when compared with the equal power allocation algorithm. …”
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Economic sizing and placement of hydrogen fueling and electric vehicles charging stations powered by renewable and battery systems in smart distribution network by Mehdi Veisi

“…The solution is derived using Benders decomposition algorithm to achieve optimal results. The primary innovation highlighted in this paper includes integrating renewable resources and battery systems to power the refueling station, leveraging reactive power control for improved station performance, and addressing both operational and economic objectives in the distribution system. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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Distributed Collaborative Control Strategy for Intra-regional AGC Units in Interconnected Power System with Renewable Energy by Lei ZHANG, Xiaowei MA, Manliang WANG, Li CHEN, Bingtuan GAO

“…It is also proved that the objective of economic optimization for frequency regulation can be fulfilled by setting reasonable coefficients, without directly solving the optimization problem. …”
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Modernizing the Design Process for US Organ Allocation Policy: Toward a Continuous Distribution Policy for Kidneys by Elijah Pivo, PhD(c), James Alcorn, JD, Dimitris Bertsimas, PhD, Sarah E. Booker, MPH, Keighly Bradbrook, PhD, Thomas G. Dolan, MS, Lindsay V. Larkin, BA, Kayla R. Temple, BA, Nikolaos Trichakis, PhD

“…Methods. A new simulation algorithm was developed that reduces the time required to simulate 1 y of allocation from >6 h down to about 15 s while using the same simulation model as the preexisting simulator used by the Organ Procurement and Transplantation Network. …”
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Distributed RL-Based Resource Allocation and Task Offloading for Vehicular Edge of Things Computing by Ghada Afifi, Bassem Mokhtar

“…We formulate a belief-based optimization problem to maximize the QoE of vehicular users while providing performance guarantees that account for geospatial uncertainty associated with the availability of embedded resources. …”
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Development of intelligent controller for high performance electric drives with hybrid CSA and RERNN technique by J. Prabhakaran, P. Thirumoorthi, M. Mathankumar, S. P. Mangaiyarkarasi

“…The primary objective is to control the speed of electric drives using complex mechanical configurations and variable parameters. The CSA optimizes the voltage source inverter’s control signal, while RERNN predicts the optimal control signal. …”
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Faster Convergence With Less Communication: Broadcast-Based Subgraph Sampling for Decentralized Learning Over Wireless Networks by Daniel Perez Herrera, Zheng Chen, Erik G. Larsson

“…Decentralized stochastic gradient descent (D-SGD) is a widely adopted optimization algorithm for decentralized training of machine learning models across networked agents. …”
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Iterative Assessment of Edge Criticality: Efficiency Enhancement or Hidden Insufficiency Detection by Vasily Lubashevskiy, Hamza Ejjbiri, Ihor Lubashevsky

“…The second is the Optimization-based approach, which treats network decomposition as an integral process and optimizes the edge sequence for network decomposition using genetic-like algorithms. …”
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Investigating the Nonlinear Relationship Between the Built Environment and Urban Vitality Based on Multi-Source Data and Interpretable Machine Learning by Wenhao Liu, Zhen Yang, Chen Gui, Gen Li, Hongyi Xu

“…Optimizing the built environment to foster urban vitality is essential for effective urban planning and sustainable development. …”
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Degree-Constrained k-Minimum Spanning Tree Problem by Pablo Adasme, Ali Dehghan Firoozabadi

“…Our numerical results indicate that the proposed models and algorithms allow obtaining optimal and near-optimal solutions, respectively. …”
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ENHANCING GRID INTEGRATION OF A SINGLE-PHASE SOLAR INVERTER THROUGH ADVANCED CONTROL TECHNIQUES AND REAL-TIME VALIDATION by Anupama Subhadarsini, Babita Panda, Byamakesh Nayak

“…The CMAES-CMBO algorithm optimizes the controller's parameters. Comparative analysis of the CMAES-CMBO-HFF-2DoF-FOTIDC controller with other state-of-the-art controllers demonstrates its superior performance and effectiveness. …”
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GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…Enhanced by local mean optimization and adaptive noise regulation, the ICEEMDAN algorithm effectively suppresses pseudo-modes and minimizes residual noise, enabling its decomposed intrinsic mode functions (IMFs) to more accurately capture the multi-scale features of GNSS-PWV. …”
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The Forecasting Yield of Highland Barley and Wheat by Combining a Crop Model with Different Weather Fusion Methods in the Study of the Northeastern Tibetan Plateau by Peng Li, Liang He, Xuetong Wang, Mengfan Zhao, Fan Li, Ning Jin, Ning Yao, Chao Chen, Qi Tian, Bin Chen, Gang Zhao, Qiang Yu

“…For HB, sequential selection and an improved KNN algorithm were optimal, while for wheat, sequential selection performed best. …”
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Adaptive multi-agent reinforcement learning for dynamic pricing and distributed energy management in virtual power plant networks by Jian-Dong Yao, Wen-Bin Hao, Zhi-Gao Meng, Bo Xie, Jian-Hua Chen, Jia-Qi Wei

“…Our proposed MARL framework enables adaptive, decentralized decision-making for both the distribution system operator and individual VPPs, optimizing economic efficiency while maintaining grid stability. …”
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Research on soybean leaf disease recognition in natural environment based on improved Yolov8 by Chen Chen, Chen Chen, Xiaolei Lu, Lei He, Lei He, Ruoxue Xu, Ruoxue Xu, Yi Yang, Yi Yang, Jing Qiu, Jing Qiu

“…Experimental results demonstrate that YOLOv8-DML achieves a mAP50 of 96.9%, marking a 1.8% improvement over the original YOLOv8 algorithm, while also achieving an 18.6% reduction in parameters. …”
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Synergistic Effect of <i>Bacillus</i> and Chitosan: From Flocculation to Enhanced Antimicrobial Activity by Selena Dmitrović, Nataša Lukić, Ivana Danilov, Vanja Vlajkov, Jovana Grahovac, Aleksandar Jokić

“…The response surface approach, followed by desirability function optimization and the genetic algorithm were applied. …”
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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 order to solve the mixed integer nonlinear problem (MINLP), a data offloading selection strategy based on proximity discovery and an iterative method-based resource allocation algorithm (IRA) are proposed. In addition, the closed-form solutions of the optimized variables are obtained. …”
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