A Fast Fault Location Based on a New Proposed Modern Metaheuristic Optimization Algorithm by Mohammad Parpaei, Hossein Askarian-Abyaneh, Farzad Razavi

“…Moreover, a fast and accurate modern metaheuristic optimization algorithm for this cost function is proposed, which are key parameters to estimate the fault location methods based on optimization algorithms. …”
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Optimal Scheduling of Hydro-photovoltaic Complementary Systems Based on Multi-objective Moth-flame Algorithm by LI Ze-hong, YUAN Xiao-feng, XIAO Peng, ZHANG Tai-heng, QIN Hui

“…The combination of these two led to the development of a new high-performance multi-objective evolutionary algorithm: R-IMOMFO. A multi-objective optimization scheduling model for hydro-photovoltaic complementary systems was established, considering both power generation benefits and capacity benefits, and the model was solved using the R-IMOMFO algorithm. …”
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Improved empirical wavelet transform combined with particle swarm optimization-support vector machine for EEG-based depression recognition by Yongxin Wang, Longqi Xu, Hongxu Qian, Haijun Lin, Xuhui Zhang

“…Therefore, there is a pressing need to develop techniques for detecting early signs of depression to enable timely intervention and potentially improve recovery rates. In this paper, we propose an improved method for the early objective diagnosis of depression utilizing an empirical wavelet transform (EWT) technique enhanced by a particle swarm optimization-support vector machine (PSO-SVM) algorithm. …”
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Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm by Haichao Zhou, Zhen Jiang, Wenchao Li, Guolin Wang, Yongjie Tu

“…The response surface model was optimized using the simulated annealing (SA) algorithm, and the optimal key factors of the head runner were obtained. …”
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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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Sentiment analysis using long short term memory and amended dwarf mongoose optimization algorithm by Haisheng Deng, Ahmed Alkhayyat

“…To enhance the performance long short-term memory (LSTM), the model was optimized using the amended dwarf mongoose optimization (ADMO) algorithm, leading to improvements in the hyperparameters. …”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…By providing accurate and timely information on fish feeding behavior, the model can help optimize feeding strategies, reduce feed waste, and improve the overall efficiency and profitability of aquaculture operations. …”
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A Multi-Surrogate Assisted Multi-Tasking Optimization Algorithm for High-Dimensional Expensive Problems by Hongyu Li, Lei Chen, Jian Zhang, Muxi Li

“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used in the field of high-dimensional expensive 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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ACM-YOLOv10: Research on Classroom Learning Behavior Recognition Algorithm Based on Improved YOLOv10 by Beichen Qin, Haoyan Hu, Shaowen Du

“…Additionally, generalization experiments conducted on another SB dataset confirm that the improved algorithm model possesses good generalization performance.…”
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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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Nonlinear Path Optimization Algorithm for Mining Trucks Based on Two-Layer Trust Region Strategy by PENG Fan, HU Yunqing, LIU Yong, DENG Mukun, LUO Yu, LIU Xibing

“…Compared with the discrete point smoothing and multiple optimization algorithms widely applied in the industry, the algorithm exhibited an improvement in the limiting effect of curvatures and curvature change rates by about 16.36% and 28.07%, and 8.46% and 19.61%, respectively. …”
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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

“…This paper applied the horse herd optimization algorithm, a distinctive population-based and discrete metaheuristic technique, in clustering software modules. …”
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Optimizing energy forecasts at Boma for 2023 to 2053 Using machine learning techniques of the PSO algorithm by André Mampuya Nzita, Bernard Ndaye Nkanka, Guyh Dituba Ngoma, Clément N’zau Umba-di-Mbudi

“…In parallel, machine learning techniques were employed to predict energy consumption, with the Particle Swarm Optimization (PSO) algorithm used to optimize forecasts. …”
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Improved Energy Efficient Anytime Optimistic Algorithm for PEGASIS to Extend Network Lifetime in Homogeneous and Heterogeneous Networks by Tadele A. Abose, Venumadhav Tekulapally, Samuel T. Daka, Diriba C. Kejela, Alemayehu E. Duguma, Desalegn T. Degaga

“…The proposed IEE AO algorithm is compared with several existing models, including low energy adaptive clustering hierarchy (LEACH), stable election protocol (SEP), ant colony optimization (ANT), and anytime optimistic (AO) algorithms, under both MAX energy and sequential energy criteria. …”
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Achieving high-accuracy skin cancer classification with deep learning optimized by ant colony algorithm by Amany M. Sarhan, Hesham A. Ali, Shady Yasser, Mohamed Gobara, Ahmed A. Kandil, Ghada Sherif, Esraa Moustafa

“…Hyperparameter optimization is achieved using the Ant Colony Optimization algorithm. …”
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Improved method for a pedestrian detection model based on YOLO by Yanfei LI, Chengyi DONG

“…Experimental validation revealed significant performance improvements over the original YOLOv8n model. This enhanced architecture achieved 7.2% and 9.2% increases in mAP0.5 and mAP0.5:0.95 metrics respectively for dense pedestrian detection, with corresponding improvements of 7.6% and 8.7% observed in actual farmland working environments. …”
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Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network by Zhihong QIAN, Yinuo FENG, Jiani SUN, Xue WANG

“…To solve the access selection problem of heterogeneous wireless network, an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed, considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network, the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network, so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network, improve system throughput, reduce blocking rate, and reduce switching times to some extent.…”
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Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network by Zhihong QIAN, Yinuo FENG, Jiani SUN, Xue WANG

“…To solve the access selection problem of heterogeneous wireless network, an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed, considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network, the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network, so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network, improve system throughput, reduce blocking rate, and reduce switching times to some extent.…”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…Cross-scale shared convolution parameters and separated batch normalization techniques are used to optimize the detection head, achieving a lightweight design and improving the detection efficiency of the algorithm. …”
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