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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Reduced-Complexity and Robust Surface Water Path Delineation for Large Real-World Terrain Using Boundary Element Method by Ajalawit Chantaveerod, Kampol Woradit, Andrew Seagar, Thunyawat Limpiti

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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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Cost-effectiveness of FIT and a FIT-based model to optimise symptomatic diagnosis of colorectal cancer: health economic modelling for the COLOFIT project by Linda Sharp, Sarah Bailey, Colin Rees, Willie Hamilton, Dawn Craig, Joe West, David Humes, Gary Abel, James Turvill, Brian Nicholson, Chloe Thomas, Jim Chilcott, Colin Crooks, Olena Mandrik, John Whelpton

“…We assessed the cost-effectiveness of COLOFIT compared with FIT and investigated optimal risk thresholds.Methods An individual patient-level simulation model was developed, with synthetic populations constructed from data used to validate COLOFIT. …”
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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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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…Hyper-parameter tuning using any HPO algorithm/sampler improved model discrimination (AUC=0.84), resulted in models with near perfect calibration, and consistently identified features predictive of high-need high-cost health care users. …”
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Optimization design of an acoustic cover layer for a cylindrical cavity based on porous materials by Bohan ZHANG, Jili RONG, Xiuyan CHENG

“…In this study, a comprehensive investigation into the parameter fitting and acoustic performance optimization of porous materials is conducted, utilizing advanced physical models, multifluid impedance transfer theory, and particle swarm optimization algorithms. …”
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Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience by Tzu-Chien Wang, Ruey-Shan Guo, Chialin Chen, Chia-Kai Li

“…Empirical validation using Taiwanese financial institution data shows a 15% improvement in predictive accuracy compared to traditional machine-learning models, significantly enhancing customer lifetime value (CLV) predictions and multi-channel resource allocation. …”
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Geometric Optimization of Coanda Jet Chamber Fins via Response Surface Methodology by Hui Zhang, Kai Yue, Yiming Zhang

“…The optimization procedure markedly improves flow separation in the compressor, leading to a considerable decrease in the volume of low-energy fluid on the blade’s suction surface, particularly in the corner area. …”
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Multi-Time-Scale Layered Energy Management Strategy for Integrated Production, Storage, and Supply Hydrogen Refueling Stations Based on Flexible Hydrogen Load Characteristics of Po... by Zhuoyu Jiang, Rujie Liu, Weiwei Guan, Lei Xiong, Changli Shi, Jingyuan Yin

“…Compared with traditional optimization algorithms, it can effectively improve the ability to search for the optimal solution. …”
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Tone mapping based on variational model in gradient domain by IZhi-hong X, Lan-fei ZHAO, Chi ZHANG, Zhong-min ZHANG

“…Due to the low dynamic range image which was generated by the gradient domain high dynamic range compression algorithm contain the artificial boundaries and local detail distortions,a variational model in gradient domain was proposed to improve the performance of the traditional algorithm.First of all,a variational model in gradient domain was introduced to compress dynamic range,meanwhile details and edges were preserved simultaneously.Afterwards,the rate of convergence was improved by introducing the ideology of Gibbs sampler.Eventually,the improved method was employed to obtain the optimal solution of the variational model.Experimental results demonstrate that proposed algorithm reduces the degree of artificial boundaries,meanwhile low dynamic range image represents excellent capacity of detail preservation.Moreover,the real-time performance is guaranteed by the improved steepest descent method.…”
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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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Multi-objective optimization design of the cam linkage mechanism of the automatic welding device by SONG Zhicheng, YU Feng, DENG Yuanchao, CAI Yufei

“…Then a kinematic model of the mechanism was established. Secondly, based on the NSGA-II algorithm, taking the transmission performance of the mechanism and the overall size of the mechanism as the optimization goals, a multi-objective optimization design of the connecting rod length was carried out under limited conditions, and the entropy weight method was used to select the optimal connecting rod length from the Pareto non-inferior solution set. …”
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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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Tone mapping based on variational model in gradient domain by IZhi-hong X, Lan-fei ZHAO, Chi ZHANG, Zhong-min ZHANG

“…Due to the low dynamic range image which was generated by the gradient domain high dynamic range compression algorithm contain the artificial boundaries and local detail distortions,a variational model in gradient domain was proposed to improve the performance of the traditional algorithm.First of all,a variational model in gradient domain was introduced to compress dynamic range,meanwhile details and edges were preserved simultaneously.Afterwards,the rate of convergence was improved by introducing the ideology of Gibbs sampler.Eventually,the improved method was employed to obtain the optimal solution of the variational model.Experimental results demonstrate that proposed algorithm reduces the degree of artificial boundaries,meanwhile low dynamic range image represents excellent capacity of detail preservation.Moreover,the real-time performance is guaranteed by the improved steepest descent method.…”
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Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

“…A load flow and short circuit analysis is performed on the designed transmission system for a number of critical scenarios. The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
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Crack-Detection Algorithm Integrating Multi-Scale Information Gain with Global–Local Tight–Loose Coupling by Yun Bai, Zhiyao Li, Runqi Liu, Jiayi Feng, Biao Li

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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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Research on Optimal Design of Ultra-High-Speed Motors Based on Multi-Physical Field Coupling Under Mechanical Boundary Constraints by Jianguo Bu, Xudong Lan, Weifeng Zhang, Yan Yu, Hailong Pang, Wei Lei

“…Using a MaxPro experimental design, initial samples are obtained and fitted using a Kriging surrogate model. The NSGA-2 algorithm is then applied for optimization, with Relative Maximum Absolute Error (RMAE) and Relative Average Absolute Error (RAAE) employed for accuracy evaluation. …”
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Optimization of delivery routes for takeout under time-varying road networks by Jiaci Wang, Liang Huang, Yuanqiao Wen, Yamin Huang, Man Zhu

“…The proposed model is solved using a taboo search algorithm. The effectiveness of the delivery model and algorithm is validated through simulations that compare the performance of the delivery route model under different weather conditions and road obstacle coefficients. …”
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