A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…The P-BTLBO method combines probabilistic modeling with a bi-level optimization framework to make feature selection better. …”
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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 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

“…The relationship between the task arrival rate and server load is established based on the queueing theory model, and the token fill rate of the token bucket is adjusted adaptively according to resource load evaluation, so as to optimize the task processing flow. …”
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Doubly Constrained Robust Blind Beamforming Algorithm by Xin Song, Jingguo Ren, Qiuming Li

“…In contrast to the linearly constrained LSCMA, the proposed algorithm provides better robustness against the signal steering vector mismatches, yields higher signal captive performance, improves greater array output SINR, and has a lower computational cost. …”
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Porosity prediction of tight reservoir rock using well logging data and machine learning by Yawen He, Hongjun Zhang, Zhiyu Wu, Hongbo Zhang, Xin Zhang, Xiaojing Zhuo, Xiaoli Song, Sha Dai, Wei Dang

“…These models are further optimized with the particle swarm optimization (PSO) algorithm to enhance their predictive accuracy. …”
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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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A novel prediction of the PV system output current based on integration of optimized hyperparameters of multi-layer neural networks and polynomial regression models by Hussein Mohammed Ridha, Hashim Hizam, Seyedali Mirjalili, Mohammad Lutfi Othman, Mohammad Effendy Ya’acob, Noor Izzri Bin Abdul Wahab, Masoud Ahmadipour

“…The proposed IMGOMFFNN model is ultimately combined with Polynomial regression model to improve the predictability of the PV system. …”
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Transmit Power Optimization for Simultaneous Wireless Information and Power Transfer-Assisted IoT Networks with Integrated Sensing and Communication and Nonlinear Energy Harvesting... by Chengrui Zhou, Xinru Wang, Yanfei Dou, Xiaomin Chen

“…A two-layer algorithm based on semi-definite relaxation is proposed to tackle the complexity issue of the non-convex optimization problem. …”
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Medium- and Long-term Runoff Prediction Based on SMA-LSSVM by TIAN Jinghuan, LI Congxin, LI Ang

“…Medium-and long-term runoff prediction is extremely important for flood control,disaster reduction and the utilization efficiency improvement of water resources.To avoid the influence of prediction model parameters on prediction accuracy,this paper proposes a medium-and long-term runoff prediction model based on least squares support vector machine (LSSVM) optimized by the slime mold algorithm (SMA).Firstly,five standard test functions are selected to compare the simulation results of SMA and particle swarm optimization (PSO) algorithms in different dimensions.Secondly,SMA is used to optimize the penalty parameters and kernel parameters of LSSVM,and the comparison models of LSSVM and PSO-LSSVM are constructed.Finally,the models are verified with the monthly runoff of Manwan Hydropower Station Reservoir and Yingluoxia Hydrological Station as prediction examples.The results show that the mean square error of the SMA-LSSVM model is 29.26% and 7.42% lower than those of the LSSVM and PSO-LSSVM models,respectively,in the monthly runoff prediction of the Manwan station,and 32.61% and 6.61% lower,respectively,in the monthly runoff prediction of the Yingluoxia station.The proposed SMA-LSSVM model has better comprehensive prediction performance and also provides a new method for medium- and long-term runoff prediction.…”
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Magnetic Actuation for Wireless Capsule Endoscopy in a Large Workspace Using a Mobile-Coil System by Xiao Li, Detian Zeng, Han Xu, Qi Zhang, Bin Liao

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Synthetic Ensemble Forecasts: Operations‐Based Evaluation and Inter‐Model Comparison for Reservoir Systems Across California by Zachary P. Brodeur, William Taylor, Jonathan D. Herman, Scott Steinschneider

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Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets by Zahraa Ahmed, Mesut Çevik

“…To alleviate such an effect, this study proposes a gene selection approach based on the parameter-free and large-scale manta ray foraging optimization algorithm. Given the dimensional disparities and statistical relationship distributions of the six investigated datasets, in addition to four evaluated machine learning classifiers; the proposed Sign Random Mutation and Best Rank enhancements that substantially improved MRFO’s exploration and exploitation contributed to efficient identification of relevant genes and to machine learning improved prediction accuracy.…”
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Advanced machine learning techniques for predicting compressive strength and ultrasonic pulse velocity of concrete incorporating industrial by-products by Ehsan Mohsennia, Alireza Javid, Vahab Toufigh

“…A robust dataset, comprising 162 structured IBP concrete samples and 524 data points from existing literature, enabled rigorous training and validation of sophisticated ML models. Among the models tested, the CatBoost (CB) algorithm, optimized with the Whale Optimization Algorithm (WOA), exhibited outstanding predictive performance. …”
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Binocular Vision-Based Target Detection Algorithm by Huiguo Zhang

“…In the field of target detection, algorithms are challenged with multi-objective optimization problems in identifying detection targets, and it is also crucial to improve the recognition of small and insignificant targets. …”
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An Optimized Maximum Second-Order Cyclostationary Blind Deconvolution and Bidirectional Long Short-Term Memory Network Model for Rolling Bearing Fault Diagnosis by Jixin Liu, Liwei Deng, Yue Cao, Chenglin Wen, Zhihuan Song, Mei Liu, Xiaowei Cui

“…Initially, an adaptive golden jackal optimization (GJO) algorithm is employed to refine important CYCBD parameters. …”
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Integrating Multilayer Perceptron and Support Vector Regression for Enhanced State of Health Estimation in Lithium-Ion Batteries by Sadiqa Jafari, Jisoo Kim, Wonil Choi, Yung-Cheol Byun

“…In order to improve the accuracy of our predictions, we combined these models into a stacked ensemble using a Random Forest (RF) meta-model. …”
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Precise Assimilation Prediction of Short-Term and Long-Term Maize Irrigation Water Based on EnKF-DSSAT and Fuzzy Optimization-DSSAT Models by Yanshu Yu, Youxi Luo, Xinhang Wang, Xinran Wang, Chaozhu Hu

“…We also introduce a Boltzmann machine-based fusion algorithm to improve the model convergence speed and prediction accuracy. …”
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Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
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Enhancing Global Optimization through the Integration of Multiverse Optimizer with Opposition-Based Learning by Vu Hong Son Pham, Nghiep Trinh Nguyen Dang, Van Nam Nguyen

“…The effectiveness of iMVO is assessed through a series of tests involving both classical and IEEE CEC 2021 benchmark functions, demonstrating competitive performance against established algorithms. Moreover, the applicability of iMVO to real-world challenges is validated through its successful deployment in civil engineering tasks, particularly in optimizing truss designs and managing time-cost tradeoffs. …”
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An effective and efficient hierarchical -means clustering algorithm by Jianpeng Qi, Yanwei Yu, Lihong Wang, Jinglei Liu, Yingjie Wang

“…Second, we propose an “optimized update principle” that leverages moved points updating incrementally instead of recalculating mean and SSE of cluster in k -means iteration to minimize computation cost. …”
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