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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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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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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Research on Calibration Method of Laser Camera Sensor by LIU Shiwang, HU Yunqing, LIN Jun

“…In this paper, a laser camera sensor calibration mathematical model was established, and the process of solving the calibration model parameters by the nonlinear least square method and Gauss-Newton iterative method was analyzed, and a L-M algorithm based on maximum likelihood estimation was proposed. …”
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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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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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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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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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Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks by Jiagao Wu, Yue Ma, Linfeng Liu

“…To solve this problem, we propose an improved genetic algorithm called genetic algorithm for delivery probability and time-to-live optimization for the dynamic quota-controlled routing scheme to reduce the routing cost further. …”
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Fault classification of meta-action unit using CEEMDAN double-layer decomposition and COA-SVM by Anxiang Guo, Zhan Zhao, Jiarui Sun, Hongyu Ge

“…Third, the model is optimized by the Coati Optimization Algorithm (COA) to optimize the fault classification performance of the SVM to achieve efficient and accurate fault diagnosis of the meta-action unit of the model. …”
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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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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

“…The review also explores cost-effectiveness data, resource optimization, and challenges such as algorithmic bias and data privacy. …”
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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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Multi-dimensional constraint-based coal mining machine cutting path planning technology by Shuyang SONG, Shibo WANG, Yun WANG, Lijie WANG, Dongshuai SONG

“…NSGA-II algorithm is used to solve for the optimal cutting path. …”
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Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model by Chuansheng Zhang, Minglai Yang

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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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Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

“…To improve the difference existed in the link prediction accuracy and adaptability of different topology structure similarity based methods,a neural network-based link prediction algorithm,which fused similarity indices by neural network was proposed.The algorithm uses neural network to study the numerical characteristics of different similarity indices,and uses particle swarm optimization to optimize the neural network,and calculates the fusion index by the optimized neural network model.The experiment on the real network data set shows that the prediction accuracy of the algorithm is obviously higher than that before the fusion,and the accuracy is better than the existing methods.…”
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Design of Dual-Channel Supply Chain Network Based on the Internet of Things Under Uncertainty by Hamed Nozari, Hossein Abdi, Agnieszka Szmelter-Jarosz, Seyyed Hesamoddin Motevalli

“…In this paper, a mathematical model of a dual-channel supply chain network (DCSCN) based on the Internet of Things (IoT) under uncertainty is presented, and its solution using algorithms based on artificial intelligence such as genetic algorithm (GA), particle swarm optimization (PSO), imperialist competitive algorithm (ICA), and gray wolf optimizer (GWO). …”
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A Novel Approach to Faster Convergence and Improved Accuracy in Deep Learning-Based Electrical Energy Consumption Forecast Models for Large Consumer Groups by A. Jayanth Balaji, Binoy B. Nair, D. S. Harish Ram, Kuruvachan Kalluvelil George

“…However, the computational overhead in training models and identifying optimal training hyperparameters are challenging problems. …”
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