Performance of quantum approximate optimization with quantum error detection by Zichang He, David Amaro, Ruslan Shaydulin, Marco Pistoia

“…Abstract The quantum approximate optimization algorithm (QAOA) is a promising candidate for scaling up to tackle real-world applications. …”
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ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

“…This paper proposes a novel improved crisscross optimization (ICSO) algorithm, a hybrid evolutionary approach that integrates crisscross optimization and perturbation mechanisms to find the suitable latent vector. …”
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Anomaly detection using unsupervised machine learning algorithms: A simulation study by Edmund Fosu Agyemang

“…Future work should explore parameter optimization, the impact of dataset characteristics on model performance, and the application of these models to real-world datasets to validate their efficacy in practical anomaly detection scenarios.…”
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Newly diagnosed acute myeloid leukemia in unfit patients: 2026 treatment algorithms by Naseema Gangat, Courtney D. Dinardo

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Decomposition-Based Multiobjective Evolutionary Algorithm for Community Detection in Dynamic Social Networks by Jingjing Ma, Jie Liu, Wenping Ma, Maoguo Gong, Licheng Jiao

“…In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. …”
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Optimization of emission scheduling in microgrids with electric vehicle integration by Peng Cao, Daowang Wang, Xingyang Jiang

“…Then, aiming to minimize both the operational cost and pollution emission treatment cost of the microgrid, an emission dispatch optimization model was developed. The whale optimization algorithm (WOA) was chosen as the solving algorithm, and an improved WOA (IWOA) was obtained by optimizing the original WOA in terms of population initialization and position updating parameters. …”
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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…The ensemble learning algorithm combines multiple prediction models to improve the prediction accuracy and stability. …”
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Optimizing the Performance of Data Warehouse by Query Cache Mechanism by Ch Anwar Ul Hassan, Muhammad Hammad, Mueen Uddin, Jawaid Iqbal, Jawad Sahi, Saddam Hussain, Syed Sajid Ullah

“…In the era of Big Data, the cache is regarded as one of the most effective techniques to improve the performance of accessing data. …”
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A Hybrid EV Charging Approach Based on MILP and a Genetic Algorithm by Syed Abdullah Al Nahid, Junjian Qi

“…The proposed method includes (1) a centralized day-ahead optimal scheduling mechanism and EV shifting process based on mixed-integer linear programming (MILP) and (2) a distributed control strategy based on a genetic algorithm (GA) that dynamically adjusts the charging rate in real-time grid scenarios. …”
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A nonrevisiting genetic algorithm based on multi-region guided search strategy by Qijun Wang, Chunxin Sang, Haiping Ma, Chao Wang

“…This study proposes a nonrevisiting genetic algorithm with a multi-region guided search to improve the search efficiency. …”
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CP-YOLO: An Algorithm for Cigarette Pack Defects Detection Based on CCD Images by Peng Dong, Weihua Feng, Rui Wang, Mingyan Zhang, Qunye Hong, Yongsheng Wang, Di Wang, Guohao Zong

“…Consequently, this paper proposes an improved CP-YOLO algorithm based on YOLOv5 to address the characteristics of cigarette pack defects including large size variations and complex foreground-background information. …”
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Prediction of Arrival Time of Pure Electric Bus Based on FA-BP Algorithm by Yuanwen Lai, Hangyu Liang, Liling Huang

“…Based on the analysis of the influencing factors of the arrival time of the pure electric bus, the BP neural network arrival time prediction model optimized by the firefly algorithm (FA-BP prediction model) is established by selecting vehicle type, SOC value, battery age, and time as input conditions. …”
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Multiobjective TOU Pricing Optimization Based on NSGA2 by Huilan Jiang, Bingqi Liu, Yawei Wang, Shuangqi Zheng

“…Fast and elitist nondominated sorting generic algorithm (NSGA2) is an improved multiobjective genetic algorithm with good convergence and robustness. …”
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Data-Enabled Predictive Control for Optimal Pressure Management by Gal Perelman, Avi Ostfeld

“…Recent developments in control theory coupled with the growing availability of real-time data have paved the way for improved data-driven control methodologies. This study explores the application of a data-enabled predictive control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). …”
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Optimal Operation of Microgrid Considering Photovoltaic,Storage and Turbine by XIANG Hongwei, CHANG Xiqiang, L Menglin, XING Zhanli, WANG Han

“…Constraints include power balance constraints, etc. The improved particle swarm optimization algorithm is used to solve the problem. …”
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A METHOD FOR MONITORING RICE SEED LOSS BASED ON WOA-BP ALGORITHM by Jin Chen, Ting Shi, Yaoming Li, Yahui Zhu, Caoyuan Niu

“…ABSTRACT The combine harvester is a widely used piece of agricultural equipment in modern agriculture, and the seed loss rate is one of the important indexes used to measure its operational performance, so the monitoring of the seed loss rate is crucial for adjusting the operational parameters of combine harvesters and improving the quality of grain harvesting. Aiming at the problems of the slow response speed and low monitoring accuracy of the existing domestic seed loss rate monitoring models, this paper proposed a rice seed loss rate monitoring method based on the whale optimization algorithm-back propagation neural network (WOA-BP). …”
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An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Instead, it performs dimensionality reduction on input features through adaptive average pooling and utilizes the state update mechanism of the SSM module to significantly enhance feature representation and optimize information flow. Second, to address the limitations of SSM models in local feature modeling, this study incorporates the ConvNeXtV2 module to optimize the backbone network, improving the model’s ability to capture fine-grained local details and thereby strengthening its overall representation capability. …”
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Optimal Design of Variable-Stiffness Fiber-Reinforced Composites by Evangelos P. Hadjigeorgiou, Christos A. Patsouras, Vassilios K. Kalpakides

“…The fiber orientation is assumed to be constant within each element of the model but varies from element to element. The optimal design problem is solved numerically using a global optimization method based on a genetic algorithm. …”
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Reflection Reduction on DDR3 High-Speed Bus by Improved PSO by Huiyong Li, Hongxu Jiang, Bo Li, Miyi Duan

“…Additionally, an improved particle swarm optimization algorithm with adaptive perturbation is presented to solve the impedance mismatch problem (IPSO-IMp) based on the above model. …”
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Optimization Methods for Customized Bus Routes in Random Environments by Fangyuan Gong, Chuanjun Jia, Xu Wu

“…This algorithm starts by generating an optimized initial path based on initial reservation demands and then employs a dynamic adjustment mechanism to respond to real-time requests. …”
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