A hybrid deep learning and differential evolution approach for accurate fake news detection by Shailendra Pratap Singh, Naween Kumar, Gyanendra Kumar, Ahamed Shafeeq B.M.

“…Experimental results on benchmark datasets demonstrate that the hybrid approach achieves superior accuracy, precision, recall, and F1-score compared to existing methods such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and standalone deep learning models. …”
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A Hybrid Multi-Strategy Differential Creative Search Optimization Algorithm and Its Applications by Yuanyuan Zhang, Longquan Yong, Yijia Chen, Jintao Yang, Mengnan Zhang

“…The comparison includes both recent state-of-the-art algorithms and improved optimization methods. Simulation results demonstrate that the incorporation of the refined set and clustering process, along with the table reinforcement learning model (double Q-learning model) mechanism, leads to superior convergence speed and higher optimization precision.…”
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Intelligent decision-making for mine airflow on demand based on the improved artificial bee colony algorithm by ZHANG Lang, LEI Shuang, LI Wei, LIU Yanqing

“…To address the issue of slow convergence speed in solving the unconstrained optimization mathematical model of mine airflow control using existing metaheuristic algorithms, an intelligent decision-making method for mine airflow on demand based on an improved Artificial Bee Colony (ABC) algorithm was proposed. …”
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An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Eventually, the modified pelican optimization algorithm (MPOA) is utilized to fine-tune the optimal hyperparameter of ensemble model parameters to achieve high predictive performance. …”
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A Novel Fruit Fly Optimization Algorithm with Evolution Strategy for Magnetotelluric Data Inversion by Bin Yin, Jie Yang, Yue Li

“…After the benchmark function test, the improved algorithm has better optimization ability. …”
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A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

“…However, the nonlinear relationships between deformation and time-varying environmental factors pose significant challenges, often limiting the accuracy of conventional and deep learning models. To address these issues, this study aimed to improve the predictive accuracy and interpretability in dam deformation modeling by proposing a novel LSTM seq2seq model that integrates a chaos-based arithmetic optimization algorithm (AOA) and an attention mechanism. …”
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Presenting a multi-objective decision-making model for cost-time trade-off considering the time value of money and solving it using particle swarm optimization by Mohammadreza Shahriari

“…The model is then solved using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm to analyze the effects of time compression and activity delays on the outcomes.Findings:  The proposed model's results demonstrate its ability to optimize project resource usage by considering current constraints and capacities. …”
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Two-Stage Global–Local Aerodynamic/Stealth Optimization Method Based on Space Decomposition by Wei Zhang, Lin Zhou, Bowen Shu, Xian Chen, Zhenghong Gao, Jiangtao Huang

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Research on Investment Estimation of Prefabricated Buildings Based on Genetic Algorithm Optimization Neural Network by Jin Gao, Wanhua Zhao

“…Starting from the investment decision-making stage of construction projects, this paper analyses the characteristics of prefabricated investment estimation and the relevant literature on the characteristics of prefabricated construction projects, uses the rough set attribute reduction algorithm to screen the key engineering characteristic factors, and establishes a BP neural network model optimized by genetic algorithm to estimate and analyze the investment of completed prefabricated construction projects. …”
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Improved War Strategy Optimization with Extreme Learning Machine for Health Data Classification by İbrahim Berkan Aydilek, Arzu Uslu, Cengiz Kına

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Improved genetic algorithm based on greedy and simulated annealing ideas for vascular robot ordering strategy. by Zixi Wang, Yubo Huang, Yukai Zhang, Yifei Sheng, Xin Lai, Peng Lu

“…Traditional heuristic methods, though intuitive, often fail to achieve global optimization. To address these challenges, this research introduces a novel strategy, combining mathematical modeling, a hybrid genetic algorithm, and ARIMA time series forecasting. …”
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Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

“…To overcome this limitation, we present an enhancement to the RetinaNet model to improve its ability to handle variations in objects across different domains. …”
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Optimized Rate Control Algorithm of High-Efficiency Video Coding Based on Region of Interest by Renjie Song, Yuandong Zhang

“…Firstly, the algorithm extracts the region of interest of video frames based on time and space domains by using the improved Itti model. …”
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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. by Afnan M Alhassan, Nouf I Altmami

“…Furthermore, we have established an innovative selection mechanism by the hybrid of Jellyfish Search Optimizer (JSO) and Walrus Optimization Algorithm (WOA) to maximize the momentum of the model. …”
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Productivity Improvement of Garments Industry by Implementing Line Balancing Algorithms—A Case Study by Mst. Anjuman Ara, Nafisa Anjum, Dilir Ahbab, Mushfica Takia Sidiika, Risat Rimi Chowdhury

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A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…To address the current issue of large computations and the difficulty in balancing model complexity and detection accuracy in pavement defect detection models, a lightweight pavement defect detection algorithm, PGS-YOLO, is proposed based on YOLOv8, which integrates perception enhancement and feature optimization. …”
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Residential Building Energy Usage Prediction Using Bayesian-Based Optimized XGBoost Algorithm by Nabaa Riyadh Baqer, Parviz Rashidi-Khazaee

“…To enhance the performance of XGB and improve prediction reliability, we propose a novel Bayesian optimization approach using the Tree-Structured Parzen Estimator (TPE), leading to the development of the TPE-XGB model for HL and CL estimation. …”
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Development and optimization of an electrohydrodynamic dehydrator using ANN-GA for improved energy performance by Chakrit Suvanjumrat, Klar Kongsarai, Piyamon Phong-arom, Namnguen Chumphong, Machimontorn Promtong, Jetsadaporn Priyadumkol

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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…In terms of the robustness of the algorithm and the overall performance comparison of different methods,the proposed algorithm can extract the formant robustly from order 9 to 22, and the model algorithm shows the optimal performance when the formant is extracted from order 18. …”
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Research on Optimized Algorithm for Deep Learning Based Recognition of Sediment Particles in Turbulent Flow by WANG Hao, YANG Feiqi, ZHANG Lei, WU Wei, XIE Haonan, ZHAO Lin

“…This enhanced performance in practical detection surpasses that of the original YOLOv5 model. The number of observed particle chains increases following optimization by integrating the improved YOLOv5 model with the grayscale subtraction technique for detecting particle motion. …”
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