A Chaotic Decomposition-Based Approach for Enhanced Multi-Objective Optimization by Javad Alikhani Koupaei, Mohammad Javad Ebadi

“…The results establish the proposed algorithm as a promising alternative for solving multi-objective optimization problems.…”
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Calculation of economic velocity in supercritical CO2 transport pipelines by Yuhan CHENG, Changjun LI, Wenlong JIA, Qian GAO, Shixiong FU, Wenqin ZHANG

“…ObjectiveCarbon Capture, Utilization and Storage (CCUS) is widely recognized as a leading solution for reducing greenhouse gas emissions, while pipeline transport is the optimal method for large-scale, long-distance CO2 transport. …”
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Structural Optimization-Based Enhancement of the Dynamic Performance for Horizontal Axis Wind Turbine Blade by Ahmed Zarzoor, Alaa Jaber, Ahmed Shandookh

“…It employs a complex optimization framework that combines aerodynamics and structural analysis via MATLAB and a genetic algorithm. The investigation maximizes the length of the chord, the angle of twist, and the selection of airfoils while maintaining constraints. …”
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The Bregman Modified Second APG Method for DC Optimization Problems by Lumiao Wang, Ziye Liu, Chunguang Liu

“…To address this limitation, researchers often employ Bregman distance as an alternative to Euclidean distance in existing DC algorithms. While this substitution relaxes the requirements on DC functions, it simultaneously introduces greater complexity in theoretical analysis. …”
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A hybrid GA-SA resource allocation scheme enhanced with SINR optimization for NOMA-MIMO systems in 5G networks by Murad Halabouni, Mardeni Roslee, Sufian Mousa Ibrahim Mitani, Osama M.S. Abujawa, Anwar Faizd Osman, Fatimah Zaharah Ali

“…Genetic Algorithm (GA) optimizes user pairing by evolving high-throughput configurations, while Simulated Annealing (SA) refines power allocation to maximize Signal-to-Interference-plus-Noise Ratio (SINR) and minimize interference. …”
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Comprehensive Benefit Evaluation for Prefabricated Buildings Based on NSGA-II and Simulated Annealing Optimization Projection Pursuit Method by Fang Wang, Binbin Dai, Shiyu Song

“…Finally, the NSGA-II and simulated annealing algorithm optimization projection pursuit method are applied to solve and evaluate the comprehensive benefit model, obtaining the optimal prefabricated component solution with the best comprehensive benefits. …”
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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…This operation also reduces the computational cost by decreasing the amount of required feature map channels, while maintaining the effectiveness of the feature representation. (3) he Minimum Point Distance Intersection over Union loss function is employed to optimize bounding box detection during model training. (4) to construct the overall network structure, the Layer-wise Adaptive Momentum Pruning algorithm is used for thinning.ResultsExperiments on the TinyPerson dataset demonstrate that IYFVMNet achieves a 46.3% precision, 30% recall, 29.3% mAP50, and 11.8% mAP50-95.DiscussionThe model exhibits higher performance in terms of accuracy and efficiency when compared to other benchmark models, which demonstrates the effectiveness of the improved algorithm (e.g., YOLO-SGF, Guo-Net, TRC-YOLO) in small-object detection and provides a reference for future research.…”
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Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

“…These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
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Optimization of Ecosystem Service Bundles from a Trade-Off and Synergistic Perspective: A Case Study of Qinghai Province by Qiwei Wu, Jian Gong, Shishi Wu, Jiasheng Lin

“…Based on these synergies, we developed a novel optimization algorithm to generate spatial bundles that amplify synergistic interactions while minimizing costs. …”
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Optimizing quantum convolutional neural network architectures for arbitrary data dimension by Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Ju-Young Ryu, Daniel K. Park, Daniel K. Park

“…., the number of features) of the input data that can be processed, restricting the applicability of QCNN algorithms to real-world data. To address this issue, we propose a QCNN architecture capable of handling arbitrary input data dimensions while optimizing the allocation of quantum resources such as ancillary qubits and quantum gates. …”
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Multivariate time series clustering analysis of the Global Dietary Database to uncover patterns in dietary trends (1990–2018) by Adriano Matousek, Tiffany H Leung, Herbert Pang

“…Results: In a three-class test specific to the domain, the MTSclust programme achieved a mean accuracy of 71·5 % (adjusted Rand Index [ARI] = 0·381) while the mean accuracy of a popular algorithm, DTWclust, was 58 % (ARI = 0·224). …”
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Research on Modern Power Spectral Estimation on Radar Velocity Measurement by MEI Jialun, WANG Xiao, BAO Yansheng

“…Radar velocity measurement was widely used in the rail transit, while the algorithm was the key to the system. Relevant contents of the classical power spectral estimation and modern power spectral estimation were introduced, the latter was expounded emphatically. …”
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Deployment scheme of RSU based on connection time in VANET by Zhengchao DING, Zhenchun WEI, Lin FENG

“…For the roadside unit (RSU) placement problem in vehicular Ad Hoc network (VANET),the deployment scheme of RSU based on connection time was proposed.The scheme find the optimal positions of RSU for maximizing the number of vehicles while ensuring a certain level of connection time under the limited number of RSU.The problem was modeled as a maximum coverage problem,and a binary particle swarm algorithm was designed to solve it.The simulation experiment was carried out with the real Beijing road network map and taxi GPS data.The simulation results show that the algorithm is convergent,stable and feasible.Compared with the greedy algorithm,the proposed scheme can provide continuous network service for more vehicles.…”
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Deployment scheme of RSU based on connection time in VANET by Zhengchao DING, Zhenchun WEI, Lin FENG

“…For the roadside unit (RSU) placement problem in vehicular Ad Hoc network (VANET),the deployment scheme of RSU based on connection time was proposed.The scheme find the optimal positions of RSU for maximizing the number of vehicles while ensuring a certain level of connection time under the limited number of RSU.The problem was modeled as a maximum coverage problem,and a binary particle swarm algorithm was designed to solve it.The simulation experiment was carried out with the real Beijing road network map and taxi GPS data.The simulation results show that the algorithm is convergent,stable and feasible.Compared with the greedy algorithm,the proposed scheme can provide continuous network service for more vehicles.…”
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EM-based blind LDPC identification in multipath channels by Yu LIU, Fanggang WANG, Jingwen ZHANG, Bo AI, Zhangdui ZHONG

“…As the advent of cognitive radios,blind encoder identification has attracted increasingly attentions since it plays an important role.The existing works mainly focus on additive white Gaussian noise (AWGN) channel,while the blind identification in multipath scenarios has not been sufficiently investigated.Considering the blind low density parity-check (LDPC) codes identification in the presence of unknown multipath fading channel,a likelihood-based classifier was proposed using the expectation maximization (EM) algorithm to obtain the maximum likelihood estimates of the unknown parameters.Then,an average log-likelihood ratio (LLR) estimator was adopted to classify the unknown encoder.Numerical results show that the proposed algorithm provides promising identification performance in multipath channels,especially in the low signal-to-noise ratio region.…”
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MULTI-OBJECTIVE OPTIMIZATION OF A MEDICAL ROBOT MODEL IN TRANSIENT STATES by Grzegorz ILEWICZ, Andrzej HARLECKI

“…In order to uncover the optimal solution, a multi-objective genetic algorithm was used, guaranteeing the optimality of the manipulator model in the Pareto sense. …”
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Unveiling the Shadows—A Framework for APT’s Defense AI and Game Theory Strategy by Pedro Brandão, Carla Silva

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Analysis of Receiver Operating Characteristic Curves for Cure Survival Data and Mismeasured Biomarkers by Li-Pang Chen

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Optimizing Residential Electricity Demand with Bipartite Models for Enhanced Demand Response by Jonathan Campoverde, Marcelo Garcia Torres, Luis Tipan

“…The methodology relies on linear programming, specifically the Simplex algorithm, to optimize power distribution while minimizing costs. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…Simulation results demonstrate that our algorithm optimally balances delay and energy consumption requirements compared to existing methods, while enhancing the diversity and convergence of non-dominated solutions.…”
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