Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique by Md Moktarul Alam, Richard Perdriau, Mohammed Ramdani, Mohsen Koohestani

“…This paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. …”
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Intelligent anti-jamming decision algorithm of bivariate frequency hopping pattern based on ET-PPO by Yibo CHEN, Zhijin ZHAO

“…In order to further improve its anti-interference ability in complex electromagnetic environment, a PPO algorithm based on weighted importance sampling and eligibility traces (ET-PPO) was proposed.On the basis of the traditional frequency hopping pattern, time-varying parameters were introduced, and the bivariate frequency hopping pattern decision problem was modeled as a Markov decision problem through the construction of the state-action-reward triple.Aiming at the high variance problem of the sample update method of an actor network of the PPO algorithm, weighted importance sampling was introduced to reduce the variance, and the action selection strategy of Beta distribution was used to enhance the stability of the learning stage.Aiming at the problem of slow convergence speed of the evaluator network, the eligibility trace method was introduced, which better balanced the convergence speed and the global optimal solution.The algorithm comparison simulation results in different electromagnetic interference environments show that ET-PPO has better adaptability and stability, and has better performance against obstruction interference and sweep frequency interference.…”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…This approach improved the accuracy and robustness of structural parameter identification while maintaining computational efficiency.MethodsMOMDBA is an enhanced version of the Directional Bat Algorithm （DBA）， a swarm intelligence optimization technique inspired by the echolocation behavior of bats. …”
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Tomato Yield Estimation Using an Improved Lightweight YOLO11n Network and an Optimized Region Tracking-Counting Method by Aichen Wang, Yuanzhi Xu, Dong Hu, Liyuan Zhang, Ao Li, Qingzhen Zhu, Jizhan Liu

“…The particle swarm optimization (PSO) algorithm was used to optimize the detection region, thus enhancing the counting accuracy. …”
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A New Method for Spectral Wavelength Selection Based on Multiple Linear Regression Combined with Ant Colony Optimization and Genetic Algorithm by Qing Huang, Heru Xue, Jiangping Liu, Xinhua Jiang

“…Wavelength selection is one of the key steps in quantitative spectral analysis, which reduces the computation time while also improving the prediction accuracy of the model. In this paper, we propose a wavelength selection algorithm based on the ant colony optimization (ACO), in which the absolute value of the regression coefficient of the multiple linear regression (MLR) model is used as the basis for evaluating the importance of wavelengths, and the absolute value of the regression coefficient after full wavelength MLR modeling is used as the initial pheromone value of the ant colony optimization (MLR-ACO). …”
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Real-Time Optimal Control Strategy for Multienergy Complementary Microgrid System Based on Double-Layer Nondominated Sorting Genetic Algorithm by Min Mou, Yuhao Zhou, Wenguang Zheng, Zhongping Zhang, Da Lin, Dongdong Ke

“…In this paper, a typical model of energy input-output is established. This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.…”
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Artificial Neural Network - Multi-Objective Genetic Algorithm based optimization for the enhanced pigment accumulation in Synechocystis sp. PCC 6803 by Namrata Bhagat, Guddu Kumar Gupta, Amritpreet Kaur Minhas, Deepak Chhabra, Pratyoosh Shukla

“…Furthermore, these machine learning tools can be used as a model to improve and optimize the yields for other metabolites production. …”
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Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm by M. H. Zhang, X. Feng, M. Bano, C. Liu, Q. Liu, X. Wang

“…Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. …”
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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…The results demonstrate that swarm intelligence optimization algorithms (SIOA) significantly enhance the prediction accuracy and stability of the LSTM model. …”
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Inversion of permeability coefficient based on adaptive differential hybrid butterfly particle algorithm by Zhao YANG, Donglin DONG, Yuqi CHEN, Rong WANG

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Optimum design of double tuned mass dampers using multiple metaheuristic multi-objective optimization algorithms under seismic excitation by Fateme Zamani, Sayyed Hadi Alavi, Mohammadreza Mashayekhi, Ehsan Noroozinejad Farsangi, Ataallah Sadeghi-Movahhed, Ali Majdi

“…The tuning process is carried out using a combination of Pareto front derived from seven multi-objective metaheuristic optimization algorithms with two objectives. The proposed methodology is applied to a 10-floor case study, using ground acceleration time histories to evaluate its seismic performance. …”
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Study on Energy-saving Control of Large Central Air-conditioning System Based on BAS-PSO by Chen Yang, Yao Ye

“…The experimental test results show that the optimization algorithm can achieve a 14.6% energy saving rate, saving 153.15 kW of energy, which proves that the optimal control model and optimization algorithm have reliable application prospects.…”
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Optimizing CNC turning of AISI D3 tool steel using Al₂O₃/graphene nanofluid and machine learning algorithms by Leta Daba Gemechu, Dame Alemayehu Efa, Robsan Abebe

“…The Response Surface Methodology (RSM), Back Propagation (BP) neural networks, and Genetic Algorithms (GA) will be utilized to model and predict optimal turning parameters to enhance surface quality and manage tool tip temperature. …”
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Encoding local label correlations in multi-instance multi-label learning with an improved multi-objective particle swarm optimization by Xiang Bao, Fei Han, Qinghua Ling

“…In this paper, a MIML algorithm encoded with local label correlations with an improved Multi-Objective Particle Swarm Optimization (MIML-MOPSO-LLC) is proposed to address the above problems. …”
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Identification of maize kernel varieties based on interpretable ensemble algorithms by Chunguang Bi, Chunguang Bi, Xinhua Bi, Jinjing Liu, Hao Xie, Shuo Zhang, He Chen, Mohan Wang, Lei Shi, Lei Shi, Shaozhong Song

“…IntroductionMaize kernel variety identification is crucial for reducing storage losses and ensuring food security. Traditional single models show limitations in processing large-scale multimodal data.MethodsThis study constructed an interpretable ensemble learning model for maize seed variety identification through improved differential evolutionary algorithm and multimodal data fusion. …”
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Classification algorithm for imbalance data of ECG based on PSOFS and TSK fuzzy system by Xinhui LI, Qing SHEN, Xiongtao ZHANG

“…A new classification model of electrocardiogram (ECG) signal based on particle swarm optimization feature selection (PSOFS) and TSK (Takagi-Sugeno-Kang) fuzzy system was proposed, i.e., parallel ensemble fuzzy neural network based on PSOFS and TSK (PE-PT-FN), which was used for ECG prediction.Each class sample in the training set was randomly sampled, and the samples obtained by randomly sampled were added.Then, the feature selection method PSOFS was carried out independently and parallelly.In PSOFS, particles that were random initial positions represent different feature subsets and converge to the optimal positions after many iterations.Each subset had a corresponding feature subset.Several groups of TSK fuzzy neural network (TSK-FNN) were trained by each feature subset in parallel.Medical researchers could effectively find the correlation between ECG signal data and different types of disease through the interpretability of the fuzzy system and the feature subsets by the PSOFS algorithm.Experiments prove that PE-PT-FN greatly improves the macro-R to 92.35% while retaining interpretability.…”
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Optimizing Vehicle Routing for Perishable Products with Time Window Constraints: by Rifqi Fauzi, Adi Priansyah, Paskalis Krisna Puspadewa, Syifa Maulvi Zainun Awal, Huu Tho Nguyen, Achmad Pratama Rifai

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Design of optimized single-switch capacitor cell balancing for EV battery management by Anjan N. Padmasali, Savitha G. Kini, Arun P. Parameswaran

“…However, there are possible modifications to them that may lead to algorithms with improved results. Two algorithms are explored for a four-series connected Li-ion cell battery system. …”
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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer by Xiaoyu Li, Xiangye Zeng, Jingyi Wang, Qi Li, Baoshuo Fan, Qi Zeng

“…A transfer function model of the USV heading system is established using voyage data, with ISWO optimizing its parameters, achieving a 5.67% reduction in mean squared error (MSE) compared to the original Spider Wasp Optimizer and outperforming classical algorithms like Arithmetic Optimization Algorithm (AOA), Crayfish Optimization Algorithm (COA), and Marine Predators Algorithm (MPA). …”
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Improved double DQN with deep reinforcement learning for UAV indoor autonomous obstacle avoidance by Ruiqi Yu, Qingdang Li, Jiewei Ji, Tingting Wu, Jian Mao, Shun Liu, Zhen Sun

“…The algorithm enhances the perception and learning capabilities by optimizing the network model and employs a dynamic exploration strategy that encourages exploration in the early stage and reduces it later to accelerate convergence and improve efficiency. …”
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