A New Reliability Rock Mass Classification Method Based on Least Squares Support Vector Machine Optimized by Bacterial Foraging Optimization Algorithm by S. Zheng, A. N. Jiang, X. R. Yang, G. C. Luo

“…LSSVM parameters were optimized by the BFOA to form a hybrid BFOA-LSSVM algorithm. …”
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Optimized fiducial marker placement using B‐spline surface modeling and graph theory for Cyberknife stereotactic body radiotherapy for superficial tumors by Jing Huang, Xianlong Xiong, Cheng Chen, Yuhan Li, Ruijie Wang, Zhitao Dai

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Risk and resilience based residential electric vehicle integration framework for restoration of modern power distribution networks by Abdullah Ali M. Alghamdi, Dilan Jayaweera

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Research on Audit Risk Prediction in Enterprise Management Based on Optimized BP Neural Network Algorithm by Wang Mingming

“…Under the development of enterprise management intelligence, there are more and more studies on the identification and evaluation of audit risks, in order to accurately identify enterprise audit risks, enterprises have created an audit risk identification model with artificial intelligence algorithm as the core, which aims to identify enterprise audit risks with high quality and significantly improve audit efficiency. …”
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Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network by Noor Habib Khan, Yong Wang, Raheela Jamal, Sheeraz Iqbal, Mohamed Ebeed, Yazeed Yasin Ghadi, Z. M. S. Elbarbary

“…To avoid stagnation problems in skilled optimization algorithm (SOA), three strategies such as fitness‐distance balance selection, mutation, and gorilla troops‐based approaches are utilized to improve overall strength of SOA. …”
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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…The proposed model builds upon the UNET3 + architecture and integrates multi-scale feature extraction with enhanced optimization strategies to improve segmentation accuracy while significantly reducing computational complexity. …”
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Explainable Artificial Intelligence in Malignant Lymphoma Classification: Optimized DenseNet121 Deep Learning Approach With Particle Swarm Optimization and Genetic Algorithm by Haitham ELwahsh, Ali Bakhiet, Omar Ibrahim Alirr, Tarek Khalifa, Maazen Alsabaan, Mohamed I. Ibrahem, Engy El-Shafeiy

“…It is recommended that the combined application of PSO for feature reduction and GA for model optimization can be successfully used for improving accuracy rate of such algorithms while reducing computation time. …”
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Adaptive Reconfigurable Learning Algorithm for Robust Optimal Longitudinal Motion Control of Unmanned Aerial Vehicles by Omer Saleem, Aliha Tanveer, Jamshed Iqbal

“…This study presents the formulation and verification of a novel online adaptive reconfigurable learning control algorithm (RLCA) for improved longitudinal motion control and disturbance compensation in Unmanned Aerial Vehicles (UAVs). …”
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Optimization of the Hollow Rectification Sill in the Forebay of the Pump Station Based on the PSO-GP Collaborative Algorithm by Wang Xi, Weigang Lu, Chuan Wang, Bo Xu

“…The layout of the pump station is easily affected by topography, site, and other factors, resulting in poor inlet flow patterns in the forebay, which seriously affect the normal operation of the pump station. To optimize its inlet flow pattern, the size of the hollow rectification sill has been continuously improved through physical model tests to meet the requirements of the required pump station inlet flow field. …”
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Management of large energy storage power plants: optimization of charging and discharging with cuckoo search algorithm by Behnam Motalebinejad, Majid Hosseina, Mojtaba Vahedi, Mahmoud Samiei Moghaddam

“…This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. …”
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Hybrid-driven modeling using a BiLSTM–AdaBoost algorithm for diameter prediction in the constant diameter stage of Czochralski silicon single crystals by Yu-Yu Liu, Ding Liu, Shi-Hai Wu, Yi-Ming Jing

“…In this paper, a hybrid-driven modeling method integrating Bidirectional Long Short-Term Memory network (BiLSTM) and Adaptive Boosting (AdaBoost) algorithm is proposed, aiming to improve the accuracy and stability of crystal diameter prediction in the medium diameter stage of the SSC growth by the Czochralski (CZ) method. …”
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Long-distance target localization optimization algorithm based on single robot moving path planning by Yourong Chen, Ke Wu, Yidan Guo, Kehua Zhao, Liyuan Liu

“…This approach solves the optimization model and obtains the optimal target positions and path trajectories, thereby improving the positioning accuracy for long-distance targets. …”
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An Optimal Allocation Strategy for Multienergy Networks Based on Double-Layer Nondominated Sorting Genetic Algorithms by Min Mou, Da Lin, Yuhao Zhou, Wenguang Zheng, Jiongming Ruan, Dongdong Ke

“…Aiming at the problems of complex structures, variable loads, and fluctuation of power outputs of multienergy networks, this paper proposes an optimal allocation strategy of multienergy networks based on the double-layer nondominated sorting genetic algorithm, which can optimize the allocation of distributed generation (DG) and then improve the system economy. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…Findings: The optimized LightGBM model showed significant improvement in early CHD detection. …”
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COMQ: A Backpropagation-Free Algorithm for Post-Training Quantization by Aozhong Zhang, Zi Yang, Naigang Wang, Yingyong Qi, Jack Xin, Xin Li, Penghang Yin

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Multi-Objective Optimal Scheduling of Water Transmission and Distribution Channel Gate Groups Based on Machine Learning by Yiying Du, Chaoyue Zhang, Rong Wei, Li Cao, Tiantian Zhao, Wene Wang, Xiaotao Hu

“…This study develops a synergistic optimization method of multiple gates integrating hydrodynamic simulation and data-driven methods, with the goal of improving the accuracy of water distribution and regulation efficiency. …”
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DGA-ACO: Enhanced Dynamic Genetic Algorithm—Ant Colony Optimization Path Planning for Agribots by Zhenpeng Zhang, Pengyu Li, Shanglei Chai, Yukang Cui, Yibin Tian

“…It integrates a 2D risk-penalty mapping model with dynamic obstacle avoidance mechanisms, improves max–min ant system pheromone allocation through adaptive crossover-mutation operators, and incorporates a hidden Markov model for accurately forecasting obstacle trajectories. …”
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Research on fault diagnosis of amorphous alloy transformers by using vibration signals and a PSO-optimized full-process WPT-SVM model by Daosheng Liu, Wentao Yang, Longsheng Liu, Zhe Zhao

“…Overall, the full-process optimization significantly improves AMT fault diagnosis efficiency compared with single-aspect optimization.…”
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LIGHTWEIGHT DESIGN OF THE BASE FOR RECIPROCATING PISTON DIAPHRAGM PUMP BASE ON MULTI-OBJECTIVE OPTIMIZATION ALGORITHM by MA WenSheng, FENG ZhiWei, SHEN Yan, SUN ZhongZhi, NIU PeiYu, LIU ChunChuan, LI FangZhong, CHEN Tao

“…The lightweight design of diaphragm pump base structure has an important impact on the processing and production of diaphragm pump.Based on the research of the frame structure of a certain type of diaphragm pump,the equivalent model was established for the actual working environment and the finite element analysis was carried out.The design variables were defined according to analysis results to improve the calculation efficiency.The uniform test design method was adopted for the test design,and the relationship between the design variables and the stress and deformation was calculated through simulation fitting.The lightweight optimization mathematical model was established for the diaphragm pump base structure by using the multi-objective optimization algorithm.On the premise of meeting the performance requirements,some materials were reasonably configured,and the stress,deformation and natural frequency of the diaphragm pump base structure were as small as possible.The frame structure after the lightweight optimization design was simulated and analyzed,and compared with the structure before optimization.The results show that the structural properties of the engine base remain unchanged after lightweight,and the weight is reduced from 25372 kg to 24582 kg,with a weight reduction of 790 kg.The weight reduction effect is good,the maximum stress value is reduced by 45.1%,and the maximum deformation is reduced by 12.3%.The optimization effect is remarkable,which provides a basic support for the finite element analysis and lightweight optimization design of the new diaphragm pump structure.…”
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A Modified Horse Herd Optimization Algorithm and Its Application in the Program Source Code Clustering by Bahman Arasteh, Peri Gunes, Asgarali Bouyer, Farhad Soleimanian Gharehchopogh, Hamed Alipour Banaei, Reza Ghanbarzadeh

“…Software module clustering is considered a tremendous reverse engineering technique for constructing structural design models from the program source code. The main objectives of clustering modules are to reduce the quantity of connections between clusters, increase connections within clusters, and improve the quality of clustering. …”
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