Parameter optimization of ship anti-roll gyro control system based on genetic algorithm by Tongtong QIE, Jianyong ZHENG, Lei ZHANG, Zhichu LEI, Xutao HE

“…ObjectiveIn order to improve the performance of the anti-roll gyro, a passive control parameter optimization method based on a genetic algorithm is proposed. …”
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Radial Basis Function Neural Network Based on an Improved Exponential Decreasing Inertia Weight-Particle Swarm Optimization Algorithm for AQI Prediction by Jinna Lu, Hongping Hu, Yanping Bai

“…This paper proposed a novel radial basis function (RBF) neural network model optimized by exponential decreasing inertia weight particle swarm optimization (EDIW-PSO). …”
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A new type of sustainable operation method for urban rail transit: Joint optimization of train route planning and timetabling by Guorong Fan, Chao Li, Xinyun Shao, Fangzheng Zhen, Yao Huang

“…A linearization method for the model is proposed. To solve large-scale problems, an improved adaptive large neighborhood search algorithm (ALNS) is designed accordingly. …”
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Optimization of deep learning architecture based on multi-path convolutional neural network algorithm by Chuan Zhou, Yan Liu, Xinghan An, Xiyao Xu, Hao Wang

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An Ensemble Model for Predicting Cardiovascular Disease utilizing Nature Inspired Optimization by Annwesha Banerjee Majumder, Somsubhra Gupta, Sourav Majumder, Dharmpal Singh

“… This paper represents an efficient model for heart disease prediction model utilizing an ensemble mechanism optimized through BAT algorithm. …”
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Optimization design of urban rainwater and flood drainage system based on SWMM by Cao Xihan

“…Traditional drainage system design methods are no longer able to meet the complex needs of modern cities. To improve the overall performance of urban rainwater and flood drainage system, a coupling model of multiobjective optimization algorithm and rainstorm management model is constructed. …”
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Urban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye by Enes Gul

“…By applying advanced boosting algorithms—specifically, XGBoost, GradientBoost, and CatBoost—along with hyperparameter optimization through the Fick’s law algorithm (FLA), this research introduces an innovative methodology aimed at improving the reliability and accuracy of flood hazard assessments in Ankara’s urban landscape. …”
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CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…Due to the slow convergence speed and the tendency to fall into local optimal solutions of the Hippopotamus Optimization Algorithm (HO), an improved Hippopotamus Optimization (IHO) algorithm-optimized Support Vector Machine (SVM) model for valve leakage diagnosis is introduced to further enhance the accuracy of valve leakage diagnosis. …”
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Dynamic Modeling and Parameter Optimization of Potato Harvester Under Multi-Source Excitation by Jianguo Meng, Zhipeng Li, Zheng Li, Yanzhou Li, Wenxia Xie

“…On this basis, the Bayesian optimization algorithm was used to obtain optimal connection parameters. …”
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Alzheimer’s Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models by Sameer Abbas, Mustafa Yeniad, Javad Rahebi

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Air quality prediction enhanced by a CNN-LSTM-Attention model optimized with an advanced dung beetle algorithm by Xiaojie Zhou, Majid Khan Majahar Ali, Farah Aini Abdullah, Lili Wu, Ying Tian, Tao Li, Kaihui Li

“…This study proposes a hybrid CNN-LSTM-Attention model optimized with an improved Dung Beetle Optimization (IDBO) algorithm to enhance predictive performance. …”
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Implementation of Taguchi and Genetic Algorithm Techniques for Prediction of Optimal Part Dimensions for Polymeric Biocomposites in Fused Deposition Modeling by Raman Kumar, Jasgurpreet Singh Chohan, Sandeep Singh, Shubham Sharma, Yadvinder Singh, S. Rajkumar

“…Maximum weightage was given to width of FDM polymeric biocomposite parts which may play critical role in biomedical and aerospace applications. The advanced optimization and production techniques have yielded promising results which have been validated by advanced algorithms. …”
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A Short-Term Solar Photovoltaic Power Optimized Prediction Interval Model Based on FOS-ELM Algorithm by G. Ramkumar, Satyajeet Sahoo, T. M. Amirthalakshmi, S. Ramesh, R. Thandaiah Prabu, Kasipandian Kasirajan, Antony V. Samrot, A. Ranjith

“…This approach can replace existing knowledge with new information on a continuous basis. The variance of model uncertainty is computed in the first stage by using a learning algorithm to provide predictable PV power estimations. …”
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Assessing carbon–neutral supercapacitors in renewable energy systems with self-improving agent-based molecular fuzzy intelligent algorithms by Oscar Castillo, Hasan Dinçer, Serkan Yüksel, Serkan Eti

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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Network Security Situational Awareness Based on Improved Particle Swarm Algorithm and Bidirectional Long Short-Term Memory Modeling by Peng Zheng, Yun Cheng, Wei Zhu, Bo Liu, Shuhong Liu, Shijie Wang, Jinyin Bai

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Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm by Qichun Bing, Dayi Qu, Xiufeng Chen, Fuquan Pan, Jinli Wei

“…Because of the uncertainty and nonlinearity, short-term traffic flow forecasting remains a challenging task. In order to improve the accuracy of short-term traffic flow forecasting, a short-term traffic flow forecasting method based on LSSVM model optimized by GA-PSO hybrid algorithm is put forward. …”
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Optimizing Personalized Recommender Systems for Teachers’ Digital Learning Models Using Deep Learning Algorithms by Jun Zhong, Wenjuan Zhang

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Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms by Sawsan Akram Hassan, Mahir M. Hason, Ammar N. Hanoon, Ali A. Abdulhameed

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The Impact of Different Parallel Strategies on the Performance of Kriging-Based Efficient Global Optimization Algorithms by Hang Fu, Qingyu Wang, Takuji Nakashima, Rahul Bale, Makoto Tsubokura

“…A parallel efficient global optimization (EGO) algorithm with a pseudo expected improvement (PEI) multi-point sampling criterion, proposed in recent years, is developed to adapt the capabilities of modern parallel computing power. …”
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