Retracted: An Enhanced Hybrid Glowworm Swarm Optimization Algorithm for Traffic-Aware Vehicular Networks by Pratima Upadhyay, Venkatadri Marriboina, Shiv Kumar, Sunil Kumar, Mohd Asif Shah

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A Track Segment Association Method Based on Heuristic Optimization Algorithm and Multistage Discrimination by Yiming Chen, Zhikun Zhang, Hui Zhang, Weimin Huang

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A New Logistic Dynamic Particle Swarm Optimization Algorithm Based on Random Topology by Qingjian Ni, Jianming Deng

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Prioritized Multi‐Step Decision‐Making Gray Wolf Optimization Algorithm for Engineering Applications by Idriss Dagal, Alpaslan Demirci, Ambe Harrison, Wulfran Fendzi Mbasso, Said Mirza Tercan, Burak Akın, Kürşat Tanriöven, Havva Aysun Sezgin Köksal, Ahmet Nayir

“…This visual representation highlights the computational efficiency of PMS‐GWO compared to other algorithms. …”
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An Improved Binary Spider Wasp Optimization Algorithm for Intrusion Detection for Industrial Internet of Things by Mousa'b Mohammad Shtayat, Mohammad Kamrul Hasan, Anil Kumar Budhati, Rossliawati Solaiman, Shayla Islam, Bishwajeet Pandey, Huda Saleh Abbas, Mamoon Mohammed Ali Saeed

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A Multidimensional Particle Swarm Optimization-Based Algorithm for Brain MRI Tumor Segmentation by Zsombor Boga, Csanád Sándor, Péter Kovács

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Optimization of hybrid-forecasting algorithm parameters using a model ensemble in real time by Elena A. Kochegurova, Sofia M. Saybert, Ksenia V. Tatyankina

“…This made it possible to increase the efficiency of the recurrent P-spline as a real-time forecasting model, reduce computational costs and increase the performance of forecasting algorithms.…”
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Residential Building Energy Usage Prediction Using Bayesian-Based Optimized XGBoost Algorithm by Nabaa Riyadh Baqer, Parviz Rashidi-Khazaee

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Improved Hybrid A* Algorithm Based on Lemming Optimization for Path Planning of Autonomous Vehicles by Yong Chen, Yuan Liu, Wei Xu

“…Path planning for autonomous vehicles is a core component of intelligent transportation systems, playing a key role in ensuring driving safety, improving driving efficiency, and optimizing the user experience. To address the challenges of safety, smoothness, and search efficiency in path planning for autonomous vehicles, this study proposes an improved hybrid A* algorithm based on the lemming optimization algorithm (LOA). …”
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Optimization of Rendering Parameters of Cesium 3DTiles Model Based on Differential Evolution Algorithm by Doujun Zhang, Yong Wu, Youcong Ni, Tinghuang Zhang, Chenxiang Gao

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Deep learning for algorithmic trading: A systematic review of predictive models and optimization strategies by MD Shahriar Mahmud Bhuiyan, MD AL Rafi, Gourab Nicholas Rodrigues, MD Nazmul Hossain Mir, Adit Ishraq, M.F. Mridha, Jungpil Shin

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A Novel Method for News Recommendation on Websites Using the Clustered-Vectors Optimization Algorithm by Piyanuch Chaipornkaew, Thepparit Banditwattanawong

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An Enhanced Differential Evolution Based Algorithm with Simulated Annealing for Solving Multiobjective Optimization Problems by Bili Chen, Wenhua Zeng, Yangbin Lin, Qi Zhong

“…An enhanced differential evolution based algorithm, named multi-objective differential evolution with simulated annealing algorithm (MODESA), is presented for solving multiobjective optimization problems (MOPs). …”
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An Efficient Optimization Algorithm for Measurement Matrix Based on SVD and Improved Nesterov Accelerated Gradient by B. ZHANG, R. YI, Z. WANG, J. PU, . Y. SUN

“…An efficient optimization algorithm for measurement matrix is proposed on the basis of alternating minimization. …”
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A Fast Satellite Selection Algorithm Based on Hierarchical Clustering and Iterative Subset Optimization by Dan Jing, Weidie Li, Liang Han, Xinchen Li, Liangchao Li, Yan Zhang, Liang Guo, Mengdao Xing

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Preprocessing optimization algorithm based on partial channel information feedback in wideband OFDM systems by WANG Xia1, ZHANG Guo-mei1, XUE Tao2

“…To mitigate inter-block interference（IBI） and inter-carrier interference（ICI） in an orthogonal frequency divi-sion multiplexing（OFDM） system,pre-processing approaches at transmitters based on full channel state information（CSI） had been proposed,the performance improved and receiver simplied.However,feeding full CSI back would oc-cupy scarce bandwidth and was impractical sometimes for the systems with high real-time demand.To deal with this problem,a preprocessing optimization based on partial CSI feedback was investigated and three selected preprocessing approaches of optimization matrix were developed and tested.Computer simulation results showed that the proposed op-timization algorithm can effectively cancel IBI and ICI and significantly improve the performance in wideband OFDM systems.Compared with the pre-processing approaches at transmitters based on full CSI,under the condition of meeting the demand for quality of services（QoS）,the proposed scheme has high spectral efficiency and low feedback and com-putation complexity.…”
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Pedestrian Re-Recognition Algorithm Based on Optimization Deep Learning-Sequence Memory Model by Feng-Ping An

“…Based on the above explanation, this paper proposes a pedestrian re-recognition algorithm based on an optimized LSTM deep learning-sequence memory learning model. …”
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Optimization algorithm of CT image edge segmentation using improved convolution neural network. by Xiaojuan Wang, Yuntao Wei

“…To address the problem of high failure rate and low accuracy in computed tomography (CT) image edge segmentation, we proposed a CT sequence image edge segmentation optimization algorithm using improved convolution neural network. …”
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An optimized cubic B-spline algorithm for high-precision approximation of nonlinear transport phenomena by Rabia Noureen, Muhammad Kashif Iqbal, Maryam Asgir, Bandar Almohsen, Muhammad Azeem, Husam A. Neamah

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A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
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