IPO: An Improved Parrot Optimizer for Global Optimization and Multilayer Perceptron Classification Problems by Fang Li, Congteng Dai, Abdelazim G. Hussien, Rong Zheng

“…The Parrot Optimizer (PO) is a new optimization algorithm based on the behaviors of trained Pyrrhura Molinae parrots. …”
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Mixed Production Line Optimization of Industrialized Building Based on Ant Colony Optimization Algorithm by Xiaobo Chen, Fangfang Yu, Hengyu Zhou, Zhengdao Li, Kuo-Jui Wu, Xikun Qian

“…In order to optimize the large random orders in the prefabricated components production process, this research proposes a model to minimize variance of the production capacity utilization of prefabricated components in the production cycle, and the ant colony optimization algorithm is introduced to solve the mixed production line sequencing optimization problem. …”
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The prediction of karst-collapse susceptibility levels based on the ISSA-ELM integrated model by Jiaxin Wang, Ying Yang, Xian Yang, Yulong Lu, Yang Liu, Da Hu, Yongjia Hu

“…To address the limitations of conventional prediction methods, in this study, we introduce an enhanced predictive model, the improved sparrow search algorithm-optimized extreme learning machine (ISSA-ELM), for accurate karst-collapse susceptibility assessment. …”
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Adaptive crayfish optimization algorithm for multi-objective scheduling optimization in distributed production workshops by Xin Yang, Xiaoying Yang, Jinhao Du

“…Furthermore, an improved crowding distance calculation enhances the algorithm’s performance in multi-objective optimization by improving solution distribution. …”
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Optimization of Sorghum Spike Recognition Algorithm and Yield Estimation by Mengyao Han, Jian Gao, Cuiqing Wu, Qingliang Cui, Xiangyang Yuan, Shujin Qiu

“…By integrating the GOLD module’s dual-branch multi-scale feature fusion and the LSKA attention mechanism, a lightweight detection model is developed. The improved DeepSort algorithm enhances tracking robustness in occlusion scenarios by optimizing the confidence threshold filtering (0.46), frame-skipping count, and cascading matching strategy (n = 3, max_age = 40). …”
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PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
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PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

“…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
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Based on the improved SCGM(1,1)c and WIV rainfall landslide susceptible area prediction model by Qian Zhang, Shujie Cao, Yanliang Du, MingYuan Du, Yixuan Zhao, Yaoqi Nie

“…On the basis of the single factor system cloud grey model (SCGM (1,1)c), an improved SCGM (1,1)c model is proposed based on Markov prediction theory and CS algorithm optimization to predict rainfall. …”
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An efficient Quantum Approximate Optimization Algorithm with fixed linear ramp schedule for truss structure optimization by Junsen Xiao, Naruethep Sukulthanasorn, Reika Nomura, Shuji Moriguchi, Kenjiro Terada

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A New Stochastic Model to Improve Positioning Accuracy of the Recursive Least Squares Method by Nerjes Rahemi, Kurosh Zarrinnegar, Mohammad Reza Mosavi

“…In determining position using GPS, due to local effects, pseudo-range errors cannot be mitigated by methods such as the use of reference stations or mathematical models; however, by using precise carrier phase observations and deploying a statistically optimal filter such as Phase-Adjusted Pseudo-range (PAPR) algorithm, the error can be significantly reduced. …”
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The PSO-IFAH optimization algorithm for transient electromagnetic inversion. by Zhengyu Xu, Guofeng Zhao, Xian Liao, Nengyi Fu

“…And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. …”
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MQHOA algorithm with energy level stabilizing process by Peng WANG, Yan HUANG

“…An improved multi-scale quantum harmonic oscillator algorithm (MQHOA) with energy level stabilizing process was proposed analogizing to quantum harmonic oscillator's wave function. …”
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Modeling Analysis and Simulation Verification for Drive Tooth Stress of Rubber Track Wheel by Zihan Zhao, Xihui Mu, Fengpo Du, Jianhua Guo

“…Firstly，based on structure parameters and transmission principle，the drive tooth profile equation is established and determining mapping parameters by the improved Powell algorithm. The optimization results show that the accuracy of the mapping tooth profile obtained by this method is 0.12%，which effectively improves the mapping accuracy. …”
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Network heterogeneous information integrated management system based on improved RNN multi-source fusion algorithm by LI Lin, WANG Wei

“…The article adopted the wild horse optimizer (WHO) algorithm to improve the recurrent neural network (RNN) and designed a multi-source heterogeneous data fusion model. …”
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Multi-Objective Ore Blending Optimization for Polymetallic Open-Pit Mines Based on Improved Matter-Element Extension Model and NSGA-II by Jun Xiang, Jianhong Chen, Aishu Zhang, Xing Zhao, Shengyuan Zhuo, Shan Yang

“…This study constructs a multi-objective ore blending optimization system for complex polymetallic open-pit mines based on the improved matter-element extension model and NSGA-II algorithm. …”
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Increasing integration of wind energy through the joint operation of electric vehicles and the grid using the intelligent spider monkey algorithm by Han Xiaoming, Qian Jingjing

“…A significant innovation involves demonstrating that prohibitive constraints on simultaneous charging and discharging can, under specific conditions, be relaxed without compromising system stability, thereby simplifying the optimization process. The optimization problem is formulated as a single objective problem and solved using an improved spider monkey optimization algorithm. …”
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Sustainable soil organic carbon prediction using machine learning and the ninja optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy

“…To address these challenges, we propose a novel integration of the Ninja Optimization Algorithm (NiOA) for simultaneous feature selection and hyperparameter optimization, aimed at enhancing both predictive accuracy and computational efficiency. …”
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Research on optimal selection of runoff prediction models based on coupled machine learning methods by Xing Wei, Mengen Chen, Yulin Zhou, Jianhua Zou, Libo Ran, Ruibo Shi

“…Employing a “decomposition-reconstruction” strategy combined with robust optimization algorithms enhances the performance of machine learning prediction models, thereby significantly improving the runoff prediction capabilities in watershed hydrological models.…”
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Diesel Engine Urea Injection Optimization Based on the Crested Porcupine Optimizer and Genetic Algorithm by Xu Chen, Changhai Ma, Quanli Dou, Shuzhan Bai, Ke Sun, Zhenguo Li

“…In this study, test data were obtained from an engine test stand and a Support Vector Machine (SVM) was developed using the test data to predict NOx conversion efficiency and NH₃ slip. The SVM model was optimized using the Crested Porcupine Optimizer (CPO) to improve its prediction accuracy and was made to replace the mathematical model to save computational time. …”
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Research on Gearbox Fault Diagnosis based on Improved LMD Algorithm by Haibo Xing, Yue Chen, Jinghao Li

“…Aiming at the fault diagnosis of gearbox，an Improved Local Mean Decomposition （ILMD） algorithm is proposed and applied to the extraction of fault features of gearbox. …”
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