Leveraging IGOOSE-XGBoost for the Early Detection of Subclinical Mastitis in Dairy Cows by Rui Guo, Yongqiang Dai

“…Subclinical mastitis in dairy cows poses a significant challenge to the dairy industry, leading to reduced milk yield, altered milk composition, compromised animal health, and substantial economic losses for dairy farmers. A model based on the XGBoost algorithm, optimized with an Improved GOOSE Optimization Algorithm (IGOOSE), is presented in this work as an innovative approach for predicting subclinical mastitis in order to overcome these problems. …”
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Using Cuckoo Search Algorithm to Predict Corporate Financial Risks and Alleviate Economic Uncertainty by Muqiao Cai

“…Advanced forecasting models must be combined with robust optimization methods to address these challenges effectively. …”
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An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus by Di-Wen Kang, Shao-Qiang Ye, Sharifah Zarith Rahmah Syed Ahmad, Li-Ping Mo, Feng Qin, Pan Zhou

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Data-driven parameter optimization for bead geometry in wire arc additive manufacturing of 17-4 PH stainless steel by Muhammad Irfan, Yun-Fei Fu, Shalini Singh, Sajid Ullah Butt, Abul Fazal Arif, Osezua Ibhadode, Ahmed Qureshi

“…Moreover, a genetic algorithm (GA) optimizes for bead uniformity and deposition efficiency. …”
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Influence of Modal Decomposition Algorithms on Nonlinear Time Series Machine Learning Prediction Models in Engineering: A Case Study of Subway Tunnel Settlement by Qingmeng Shen, Yuming Wu, Limin Wan, Qian Chen, Yue Li, Zichao Liao, Wenbo Wang, Feng Li, Tao Li, Jiajun Shu

“…The results show that the prediction model with the integrated decomposition algorithm reduces the RMSE and MAE by 33% and 37%, respectively, which significantly improves the prediction accuracy and generalization ability of the neural network to meet the demand of practical engineering prediction and simultaneously enhances the risk warning ability of the model.…”
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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

“…While the baseline model achieves 88% accuracy on Data1 and 97.6% on Data2, the proposed ALS-IOAP-DNN4 model attains perfect accuracy (100%) on both datasets, demonstrating the effectiveness of ALS and advanced optimization techniques. …”
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A real-time 3D modeling method for buildings driven by IMU and RGB-D fusion by Yuhan Gao, Chao Dang, Jun Zhu, Yakun Xie, Ya Hu, Chunli Yan, Kun Yi, Chuan Yi, Xue Li

“…The method incorporates an adaptive sampling strategy for RGB-D cameras based on IMU data calibration, introduces a pose estimation optimization algorithm that combines dynamic feature point cluster centroid prediction with bias detection, establishes a progressive 3D modeling approach constrained by structural features, and develops a prototype system for in-depth case study analysis. …”
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A hybrid deep learning-based intrusion detection system for EV and UAV charging stations by Rosebell Paul, Mercy Paul Selvan

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Development of a Self-Updating System for the Prediction of Steel Mechanical Properties in a Steel Company by Machine Learning Procedures by Valerio Zippo, Elisa Robotti, Daniele Maestri, Pietro Fossati, David Valenza, Stefano Maggi, Gennaro Papallo, Masho Hilawie Belay, Simone Cerruti, Giorgio Porcu, Emilio Marengo

“…The integration of this model into the production process allows a large-scale steel industry to predict steel properties with heightened accuracy, optimizing the manufacturing process for minimal waste and improved consistency. …”
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Dimensionless analysis and novel configuration for enhanced natural convection cooling in lithium-ion batteries by Congyu Mao, Min Liang Wang, Kewei Gao, Hongdi Jin, Woo Young Cho, Hernando Leon-Rodriguez, Kootaek Hong, Seunghwoi Han, Jihoon Jeong, Hyun Wook Kang

“…A dimensionless analysis framework was developed and coupled with response surface models and a multi-objective genetic algorithm to optimize battery layouts for heat dissipation and temperature uniformity. …”
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Artificial liver classifier: a new alternative to conventional machine learning models by Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

“…The ALC is characterized by its simplicity, speed, capability to reduce overfitting, and effectiveness in addressing multi-class classification problems through straightforward mathematical operations. To optimize the ALC's parameters, an improved FOX optimization algorithm (IFOX) is employed during training.ResultsWe evaluate the proposed ALC on five benchmark datasets: Iris Flower, Breast Cancer Wisconsin, Wine, Voice Gender, and MNIST. …”
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Vehicle routing problem in waste collection: a case study in Son Tra, Da Nang by Le Hoang Son, Truong Nguyen Song Ha, Nguyen Ngoc Phuong, Phan Bao An

“…By employing the Dijkstra algorithm, route optimization resulted in a significant reduction in average route length, from 12.94 ± 3.5 km to 9.42 ± 2.67 km, representing a 9-42% improvement. …”
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A novel interval prediction method in wind speed based on deep learning and combination prediction by XueJun Chen, Tao Han, Peng Cheng, Xuanfang Da

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ACO-NM hybrid optimization calculation method for transit time of oxygen activation logging in CO2 injection profile by WANG Zhengyan, CHEN Meng, YANG Guofeng, LIU Guoquan, PEI Yang, CHEN Qiang

“…Through the preliminary optimization of the spectral lines, a reasonable initial solution was provided for the NM algorithm, thereby improving the stability of the transit time calculation results and enabling high-precision quantitative computation of the transit time in the oxygen activation injection profile logging. …”
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An advanced direct torque control for doubly fed induction motor using evolutionary computational techniques by Said Mahfoud, Najib El Ouanjli, Aziz Derouich, Abderrahman El Idrissi, Elmostafa Chetouani, Azeddine Loulijat, Shimaa A. Hussien, Mohamed I. Mosaad

“…This paper presents a methodology that integrates DTC-based PID controller with two optimization algorithms, with either Genetic algorithm (GA) or ant colony optimization (ACO). …”
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Light-GBM based minority oversampling model using biomedical data analysis for breast cancer classification by Mukesh Soni, Mohammed Wasim Bhatt, Paul Ofori-Amanfo

“…In the Sparrow Search Algorithm (SSA), piecewise linear chaotic map (PWLCM), novel inertia weights, and a new longitudinal-lateral crossover algorithm are introduced for improvement, followed by the application of the improved SSA algorithm for automatic parameter optimization of Light-GBM. …”
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Reinforcement Learning for Optimizing Renewable Energy Utilization in Buildings: A Review on Applications and Innovations by Panagiotis Michailidis, Iakovos Michailidis, Elias Kosmatopoulos

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Binary Secretary Bird Optimization Clustering by Novel Fitness Function Based on Voronoi Diagram in Wireless Sensor Networks by Mohammed Abdulkareem, Hadi S. Aghdasi, Pedram Salehpour, Mina Zolfy

“…To address these limitations, we propose the binary secretary bird optimization clustering (BSBOC) method. BSBOC introduces a binary variant of the secretary bird optimization algorithm (SBOA) to handle the discrete nature of CH selection. …”
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Robust Tracking Control of Piezoelectric Actuators Using Super-Twisting Sliding Mode With Bouc-Wen Hysteresis Model-Based Enhanced Jaya Algorithm by Nguyen Thi Thu Hang, Nguyen Ngoc Son

“…The Bouc-Wen model, which captures the nonlinear hysteretic behavior of the PZT actuator, is estimated using a modified Jaya algorithm enhanced with Lévy flight distribution (called LeJaya). …”
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A multi-objective optimization approach for the virtual coupling train set driving strategy by Junting Lin, Maolin Li, Xiaohui Qiu

“…Furthermore, the particle swarm optimization (PSO)-based model predictive control (MPC) algorithm has also demonstrated tracking accuracy and further improved safety during VCTS operation, with an average increase of 37.7% in tracking accuracy compared to the traditional MPC algorithm.…”
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