A Method for Predicting Coal-Mine Methane Outburst Volumes and Detecting Anomalies Based on a Fusion Model of Second-Order Decomposition and ETO-TSMixer by Qiangyu Zheng, Cunmiao Li, Bo Yang, Zhenguo Yan, Zhixin Qin

“…Variational mode decomposition (VMD) parameters are optimized via a novel exponential triangular optimization (ETO) algorithm to extract multi-scale features. Additionally, a refined TSMixer model is proposed, integrating reversible instance normalization (RevIn) to bolster the model’s generalizability and employing ETO to fine-tune model hyperparameters. …”
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Enhancing root-zone soil moisture estimation using Richards' equation and dynamic surface soil moisture data by Xizhuoma Zha, Wenbin Zhu, Yan Han, Aifeng Lv

“…The application of the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm significantly enhances the model's accuracy. …”
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Modeling of cross line operation of urban rail transit trains based on passenger travel time by LUO Qin, LIN Bin, GU Mengqi, YANG Liang, ZHANG Xiaochun

“…The model is solved by genetic algorithm. The scheme of metro Line Ⅰ of city S crossing into Line Ⅱ is used as an example to verify the feasibility of the model, and the optimal train density under different train load rates is obtained. …”
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Mathematical modeling and optimization of the active suspension system of a 6x6 electric vehicle by Berk Aydoğan, Ahmet Yildiz

“…“Bump type” and “Random type” road model scenarios as road inputs were created. In the mathematical model, simulations of models with passive and active suspension systems were carried out and system accuracy was confirmed. …”
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Positive Anchor Area Merge Algorithm: A Knowledge Distillation Algorithm for Fruit Detection Tasks Based on Yolov8 by Xiangqun Shi, Xian Zhang, Yifan Su, Xun Zhang

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Research on the Capability Maturity Evaluation of Intelligent Manufacturing Based on Firefly Algorithm, Sparrow Search Algorithm, and BP Neural Network by Li Shi, Xuehong Ding, Min Li, Yuan Liu

“…In order to overcome the shortcoming of SSA that it is easy to fall into the local optimum, the firefly disturbance strategy is introduced to improve it, a new sparrow search algorithm (FASSA) is proposed, and on this basis, an intelligent manufacturing capability maturity evaluation model based on the FASSA-BP algorithm is constructed. …”
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Wavelet Decomposition-Based AVOA-DELM Model for Prediction of Monthly Runoff Time Series and Its Applications by ZHANG Yajie

“…For the improvement in prediction accuracy of monthly runoff time series,a prediction model is proposed,which combines the wavelet decomposition (WD),African vultures optimization algorithm (AVOA),and deep extreme learning machine (DELM),and it is applied to the monthly runoff prediction of Yale Hydrological Station in Yunnan Province.Specifically,WD decomposes the time-series data of monthly runoff to obtain highly regular subsequence components,and AVOA is employed to optimize the number of neurons in the hidden layers of DELM;then,the WD-AVOA-DELM model is built to predict each subsequence component,and the prediction results are summated and reconstructed to produce the final prediction results of monthly runoff.Meanwhile,models based on the support vector machine (SVM) and BP neural networks are constructed for comparative analysis,including WD-AVOA-SVM,WD-AVOA-BP,AVOA-DELM,AVOA-SVM,and AVOA-BP models.The results reveal that the average absolute percentage error of the WD-AVOA-DELM model for the monthly runoff prediction of Yale Hydrological Station is 3.02%;the prediction error is far less than that of WD-STOA-SVM and WD-AVOA-BP models,and the prediction accuracy is more than one order of magnitude higher than that of AVOA-SVM,AVOA-SVM,and AVOA-BP models.The result indicates that the proposed model has good prediction performance.In this model,WD can scientifically reduce the complexity of runoff series and raise the prediction accuracy;AVOA can effectively optimize the key parameters of DELM and improve the performance of DELM networks.…”
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A hybrid bio-inspired augmented with hyper-parameter deep learning model for brain tumor classification by Morolake Oladayo Lawrence

“…To further improve the performance of the model, SSA was increased to select relevant features. …”
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Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model by JIANG Tao, XU Cong, JIA Shaohui, WANG Shen, ZHANG Yajian

“…Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. …”
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Robust Bi-Objective Optimization and Dynamic Modeling of Hydropneumatic Suspension Unit Considering Real Gas Effects by Di Sun, Moonsuk Chang, Jinho Kim

“…The optimized design based on a metamodel and a hybrid metaheuristic algorithm resulted in an 81.4% reduction in peak lateral forces and a 53.3% improvement in acceleration robustness, which marks a significant increase in suspension system durability. …”
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Model Predictive Control of Electric Water Heaters in Individual Dwellings Equipped with Grid-Connected Photovoltaic Systems by Oumaima Laguili, Julien Eynard, Marion Podesta, Stéphane Grieu

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Improving agricultural commodity allocation and market regulation: a novel hybrid model based on dual decomposition and enhanced BiLSTM for price prediction by Lihua Zhang, Fushun Wang, Fushun Wang, Kejian Wang, Kejian Wang, Zhenxue He, Zhenxue He, Chen Chen, Chen Chen, Jiahao Liu, Jiahao Liu, Chao Wang, Chao Wang, Zhe Wang

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An Adaptive Task Traffic Shaping Method for Highly Concurrent Geographic Information System Services with Limited Resources by Zheng Wu, Hongyun Zhou, Zezhao Wang, Pengda Wu, Zhaoting Ma

“…This paper proposes an adaptive task traffic shaping method to improve the utilization efficiency of server resources, reduce task processing delay, and improve service stability and response speed by monitoring the system load in real time and dynamically adjusting the processing rate of GIS task traffic. …”
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A Rectangular Toroidal Current-Based Approach for Lung Biopsy Needle Tracking by Hongliang Pei, Qingwen Fan, Yixiang Duan, Lang Xiao

“…An alternating electromagnetic field (~70 kHz) is modeled based on the Biot–Savart law. Induced voltages from multiple transmitting coils are processed using Fourier transform algorithms to separate frequencies, enabling the independent extraction of each coil’s signal. …”
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Research and Modeling of Commercial Location Selection Based on Geographic Big Data and Mobile Signaling Data—A Case Study of the Central Urban Area of Beijing by Jin Zou, Xun Zhang, Yangxiao Cong, Zhentong Gao, Jinlian Shi

“…This study utilizes mobile phone signaling data from Beijing combined with point-of-interest (POI) data from within the Sixth Ring Road of Beijing to identify user behaviors using algorithms. Through a combination of BiLSTM-RF and reinforcement learning algorithms, a population location prediction algorithm is constructed to address the issues of inaccurate and outdated population flow data in commercial site selection. …”
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Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments by Amin Wen, Tonghua Wu, Xiaofan Zhu, Jie Chen, Jianzong Shi, Peiqing Lou, Dong Wang, Xin Ma, Xiaodong Wu

“…The results show that (i) the lowest <i>t</i> value (0°) captured the microtopograhy of the troughs, while the larger <i>L</i> values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. …”
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Improved Asynchronous Federated Learning for Data Injection Pollution by Aiyou Li, Huoyou Li, Yanfang Liu, Guoli Ji

“…In view of the problems of data pollution, incomplete feature extraction, and poor multi-network parameter sharing and transmission under the federated learning framework of deep learning, this article proposes an improved asynchronous federated learning algorithm of multi-model fusion based on data injection pollution. …”
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Improving the efficiency of adsorption filters with a short diffuser by improving their flow part by A. S. Korneeva, N. Yu. Filkin

“…The numerical studies cover various options for backfilling the adsorbent, including layer profiling and the use of adsorbent with different porosity, which allows us to assess the impact of these factors on the aerodynamic resistance and overall efficiency of the filter. A design algorithm is also proposed that ensures optimal compliance between the adsorbent layer thickness and the local flow velocity, which helps to increase the protective action time of the filter and improve the quality of cleaning.…”
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An Algorithm of l1-Norm and l0-Norm Regularization Algorithm for CT Image Reconstruction from Limited Projection by Xiezhang Li, Guocan Feng, Jiehua Zhu

“…Numerical experiments indicate that this new algorithm makes much improvement by involving l0-norm regularization.…”
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Optimization of shielded metal arc welding process parameters on weld bead geometry using Jaya algorithm and Firefly algorithm by Pushp Kumar Baghel

“…This shows the accuracy and refinement of results using algorithms. The real world verification is done from the regression model. …”
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