An Adaptive Obstacle Avoidance Model for Autonomous Robots Based on Dual-Coupling Grouped Aggregation and Transformer Optimization by Yuhu Tang, Ying Bai, Qiang Chen

“…The Harris hawk optimization (HHO) algorithm is used for hyperparameter tuning, further improving model performance. …”
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Multi-objective Optimization Design of Component Cooling System in HPR1000 by ZHAO Weiguang1, 2, YU Pei1, 3, ZENG Xiaobo1, 2, FAN Guangming1, 2, YAN Changqi1, 2

“…Each variable possesses a specific range of values, which is critical for the optimization process. The theoretical model and the final optimization results demonstrate that the proposed evaluation model and optimization algorithm effectively assess the RRI’s performance in multi-objective optimization calculations, allowing for a substantial degree of RRI optimization. …”
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A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity by Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng

“…To evaluate the applicability of these methods, we chose one representative inversion algorithm from each category, namely the Improved Butterfly Optimization Algorithm (IBOA) for simulation optimization, the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) for data assimilation, and the DiffeRential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM(ZS)) for Bayesian inference. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…Next, k-means clustering is applied with the optimal k-value to initialize the parameters of the Gaussian Mixture Model, which are then refined and trained through the Expectation-Maximization algorithm. …”
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Toward improving precision and complexity of transformer-based cost-sensitive learning models for plant disease detection by Manh-Tuan Do, Manh-Hung Ha, Duc-Chinh Nguyen, Oscal Tzyh-Chiang Chen, Oscal Tzyh-Chiang Chen

“…To optimize a model to a lightweight version, we integrated the proposed transformer model with the Ghost module. …”
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Improvement of physics-based and data-driven model simulations based on multi-source soil moisture datasets by Xiao Liang, Haiting Gu, Yue-Ping Xu, Lu Wang, Yuxue Guo, Li Liu

“…The physics-based Distributed-Hydrological-Soil-Vegetable Model (DHSVM), coupled with the multi-objective genetic algorithm ε-NSGA-II, and data-driven Informer model, are chosen and applied to the study area. …”
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Behavior-aware energy management in microgrids using quantum-classical hybrid algorithms under social and demand dynamics by Liu Minghong, Fu Gaoshan, Wang Pengchao, Yuan Xin, Li Qing, Tengfei Hou, Zhang Shuo

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A metaheuristic approach to model the effect of temperature on urban electricity need utilizing XGBoost and modified boxing match algorithm by Nihuan Liao, Zhihong Hu, Davud Magami

“…The XGBoost model’s hyperparameters are optimized using MBM to achieve the best possible solution. …”
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Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm by Manzhi Yang, Hao Ren, Shijia Liu, Bin Feng, Juan Wei, Hongyu Ge, Bin Zhang

“…Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. …”
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SC-PA: A spot-checking model based on Stackelberg game theory for improving peer assessment by Jia Xu, Panyuan Yang, Teng Xiao, Pin Lv, Minghe Yu, Ge Yu

“…To this end, this paper proposes a novel spot-checking based peer assessment model, named SC-PA, to improve students’ motivation in peer assessment. …”
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Enhanced detection of accounting fraud using a CNN-LSTM-Attention model optimized by Sparrow search by Peifeng Wu, Yaqiang Chen

“…This paper proposes an enhanced approach to fraud detection by integrating convolutional neural networks (CNN) and long short-term memory (LSTM) networks, complemented by an attention mechanism to prioritize relevant features. To further improve the model’s performance, the sparrow search algorithm (SSA) is employed for parameter optimization, ensuring the best configuration of the CNN-LSTM-Attention framework. …”
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Optimization of emergency material distribution routes in flood disaster with truck‐speedboat‐drone coordination by Ying Gong, Weili Wang, Yufeng Zhou, Jiahao Cheng

“…To solve this optimization problem, we introduce an improved adaptive large neighborhood search (IALNS) algorithm, which builds on the traditional ALNS framework through refined tuning of deletion and insertion operators. …”
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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

“…For the optimal subset of features, the spotted hyena optimization algorithm (SHOA) model is used. …”
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Optimized Model Torque Prediction Control Strategy for BLDCM Torque Error and Speed Error Reduction System by Ye Yuan, Cheng Liu, Siyu Chen, Zhenxiong Zhou

“…This paper presents an improved whale optimization algorithm (IWOA) for optimizing the model predictive torque control (MPTC) of brushless DC motor (BLDCM) to further reduce the problems of strong torque pulsation and high ripple caused by the special structure of BLDCM. …”
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Optimal energy management of distributed generation resources in a microgrid under various load and solar irradiance conditions using the artificial bee colony algorithm by Tareq Hamadneh, Omar Alsayyed, Belal Batiha, El Manaa Barhoumi, Mehrdad Ahmadi Kamarposhti, Hassan Haghighi, Phatiphat Thounthong, Ilhami Colak

“…The results demonstrate that the proposed algorithm consistently achieves superior performance in minimizing the total operation cost compared to traditional bio-inspired optimization techniques such as genetic algorithms, particle swarm optimization, and a modified bat algorithm. …”
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A Hybrid Approach Incorporating WSO-HO and the Newton-Raphson Method to Enhancing Photovoltaic Solar Model Parameters Optimisation by Jeridi Ahmed, Moulahi Mohamed Hedi, Khaterchi Hechmi, Zaafouri Abderrahmen

“…This study introduces a novel hybrid approach, WSO-HO, which integrates the strengths of the war strategy optimization (WSO) and Hippopotamus Optimization (HO) algorithms, enhanced by the Newton-Raphson (NR) method, to achieve precise parameter estimation for PV models. …”
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Research on multi-objective energy optimization design for multi-story residential buildings in Suzhou region based on artificial neural networks by Zhongcheng Duan, Leilei Wang, Binhao Li, Gang Yao

“…To address the issues of high energy consumption, low thermal comfort, and excessive greenhouse gas emissions in residential buildings, this study optimizes multi-story residential buildings in the Suzhou region using a multi-objective Non-dominated Sorting Genetic Algorithm III (NSGA-III) coupled with an Artificial Neural Network (ANN). …”
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Performance Optimization Method of Steam Generator Liquid Level Control Based on Hybrid Iterative Model Reconstruction by Xiaoyu Li, Xiangsong Kong, Changqing Shi, Jinguang Shi, Zean Yang

“…After that, the particle swarm optimization algorithm is used to calculate the optimal point of the current valid model, and the optimization process is controlled by establishing the iteration termination judgment based on the historical iteration data. …”
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Research on highway road condition intelligent assessment and optimization system based on deep learning and internet of things by Tingquan He, Changhai Wang, Riyan Lan, Haiyu Luo

“…Experimental verification shows that the model significantly improves prediction performance. …”
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RIME optimization with dynamic multi-dimensional random mechanism and Nelder–Mead simplex for photovoltaic parameter estimation by Yuanping Zheng, Fangjun Kuang, Ali Asghar Heidari, Lipei Yuan, Siyang Zhang, Huiling Chen

“…Abstract Solar photovoltaic technology is efficient and clean, but extracting photovoltaic cell parameters is challenging due to various influencing factors. The rime optimization algorithm (RIME) is a recently proposed metaheuristic algorithm (MAs). …”
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