A Bi-Objective Model for the Location and Optimization Configuration of Kitchen Waste Transfer Stations by Ming Wan, Ting Qu, George Q. Huang, Ruoheng Chen, Manna Huang, Yanghua Pan, Duxian Nie, Junrong Chen

“…An improved non-dominated sorting genetic algorithm with an elite strategy (NSGA-II) is used to solve the problem, resulting in a Pareto-optimal solution set that includes several non-dominated solutions, thereby providing diversified choices for decision-makers. …”
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Optimizing Photovoltaic Grid‐Connected Power Systems Through Artificial Intelligence and Robust Nonlinear Control by Collins Ngong Sang, Harrison Ambe, Arnaud flanclair Tchouani Njomo, Zeric Tabekoueng Njitacke, Wulfran Fendzi Mbasso, Pradeep Jangir, Aseel Smerat

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An improved artificial fish swarm algorithm and its application on system identification with a time-delay system by CAO Fa-ru, FENG Mao-lin

“…To remedy the low convergence rate and low optimization accuracy of the artificial fish swarm algorithm (AFSA), an improved artificial fish swarm algorithm (IAFSA) was proposed. …”
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Attack resilient IoT security framework using multi head attention based representation learning with improved white shark optimization algorithm by Jawhara Aljabri

“…This paper presents a multi-head attention-driven intrusion detection with improved white shark optimization algorithm (MHAID-IWSOA) methodology in IoT networks. …”
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Risk assessment and hybrid algorithm transportation path optimization model for road transport of dangerous goods by Qiankun Jiang, Haiyan Wang

“…After experimental verification, the improved hybrid algorithm has optimized the path transportation time by 13.9 % compared to a single algorithm model. …”
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Site Selection Optimization Strategy for Independent Secondary Device Integrated Center Based on Improved Artificial Bee Colony Algorithm by Xiaoping XIONG, Shaolei HAO, Di SUN, Guangyang LIN, Hang LI

“…Taking the simple topology of a substation in a city’s urban area as an example, the effectiveness of the model is proved. Firstly, the possible interval of the optimal solution is calculated with the improved artificial bee colony algorithm; and then the ISDIC site node that is most suitable for the center is obtained through precise calculations; and finally the practical engineering significance of the model and the superiority of the method are fully illustrated through analyzing the indexes of the optimal node.…”
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Collaborative Optimization on Both Weight and Fatigue Life of Fifth Wheel Based on Hybrid Random Forest with Improved BP Algorithm by Huan Xue, Chang Guo, Xiaojian Peng, Saiqing Xu, Kaixian Li, Jianwen Li

“…We proposed a prediction model combining a random forest algorithm with an optimized back propagation (BP) neural network. …”
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Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms by Dhiaa Halboot Muhsen, Haider Tarish Haider, Yaarob Al-Nidawi

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Multiobjective optimization of buffer capacity allocation in multiproduct unreliable production lines using improved adaptive NSGA-II algorithm by jianguo duan, nan xie, Haochen Li, Qinglei Zhang

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Optimized Grasshopper Optimisation Algorithm enabled DETR (DEtection TRansformer) model for skin disease classification. by Shakti Kundu, Yogesh Kumar Sharma, Khan Vajid Nabilal, Gopalsamy Venkatesan Samkumar, Sultan Mesfer Aldossary, Shanu Kuttan Rakesh, Nasratullah Nuristani, Arshad Hashmi

“…Hyperparameter tuning using GOA optimizes the critical parameters of the proposed model to improve classification accuracy. …”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Among the available methods, partial transmit sequence (PTS) is an efficient PAPR reduction method but can be computationally expensive while deter-mining optimal phase factors (OPFs). Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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Research on Assembly Sequence Planning of Large Cruise Ship Cabins Based on Improved Genetic Algorithm by Liyang Ju, Xiaoyuan Wu, Yixi Zhao, Jianfeng Liu, Kun Liu

“…A fitness function is designed and a mathematical model is established. On this basis, a genetic greedy combination algorithm is proposed to solve the optimal assembly sequence. …”
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Enhancing Surgery Scheduling in Health Care Settings With Metaheuristic Optimization Models: Algorithm Validation Study by João Lopes, Tiago Guimarães, Júlio Duarte, Manuel Santos

“…By implementing these AI-driven strategies, hospitals can minimize patient wait times, maximize resource use, and enhance surgical outcomes through improved planning. This development highlights how AI algorithms can effectively adapt to changing health care environments, having a transformative impact.…”
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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples by Abdullahi G. Usman, Sagiru Mati, Hanita Daud, Ahmad Abubakar Suleiman, Sani I. Abba, Hijaz Ahmad, Taha Radwan

“…This study proposed the use of a support vector regression (SVR) predictive model improved by two metaheuristic algorithms used for optimization namely, Harris Hawks Optimization (HHO) and Particle Swarm Optimization (PSO) to predict chromatographic retention time of various food mycotoxin groups. …”
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Automated weed and crop recognition and classification model using deep transfer learning with optimization algorithm by K. Gopalakrishnan, R. Sivaraj, M. Vijayakumar

“…The extensive outcome highlighted the improvements of the developed AWRC-DLMLO technique with other existing models.…”
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Anomaly Detection and Performance Analysis With Exponential Smoothing Model Powered by Genetic Algorithms and Meta Optimization by Ali Kerem Guler, Huseyin Fuat Alsan, Taner Arsan

“…This study employs a genetic algorithm to optimize the parameters of the Third Order Exponential Smoothing model for predicting on the real-time traffic datasets of the Numenta Anomaly Benchmark (NAB). …”
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Enhancing the decision optimization of interaction design in sustainable healthcare with improved artificial bee colony algorithm and generative artificial intelligence. by Shuhui Yu, Xin Guan, Xiaoyan Peng, Yanzhao Zeng, Zeyu Wang, Xinyi Liang, Tianqiao Qin, Xiang Zhou

“…This study proposes an improved Artificial Bee Colony (ABC) algorithm aimed at optimizing decision-making models in the field of digital health. …”
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Application of Improved LSTM Model in Runoff Simulation in Arid Region of Northwest China: A Case Study of the Zuli River by SONG Haiping, TANG Yiran, DANG Wentao, WANG Yibo

“…The results indicate that: ① The improved LSTM model demonstrates superior performance in simulating the Zuli River, validating the adaptability of the improved strategies for complex hydrological processes. ② The GWO algorithm significantly enhances the model's prediction accuracy in the basin, confirming the effectiveness of optimization algorithms in parameter calibration. ③The GWO-LSTM-Attention model requires further validation and optimization for future daily-scale simulations and monthly runoff reconstruction.…”
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Intelligent irrigation strategy model for farmland using dung beetle optimization-random forest algorithms by Wenwen Hu, Yong Liu, Jun An, Shipu Xu, Zhiwen Zhou, Mingming An, Xiaokun Guo, Xiang Ma, Wenfei Jiang, Yunsheng Wang

“…This study proposes an optimized machine learning prediction model using the Dung Beetle Optimization-Random Forest (DBO-RF) algorithm, thus improving irrigation predictability. …”
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Models and Algorithms of Conflict Detection and Scheduling Optimization for High-Speed Train Operations Based on MPC by Zhihui Wang, Yonghua Zhou, Deng Liu

“…Compared with the general-speed railway transportation, the high-speed railway transportation requires a timely and automatic adjustment capability in the centralized traffic control (CTC) system. In order to improve the capability, this paper mainly explores the models and algorithms of conflict detection and scheduling optimization of high-speed train operations. …”
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