Interpretable machine learning for predicting optimal surgical timing in polytrauma patients with TBI and fractures to reduce postoperative infection risk by Xing Han, Jia-Hui Zhang, Xin Zhao, Xi-Guang Sang

“…SHAP and LIME algorithms were utilized for model interpretation, elucidating the importance and predictive thresholds of the variables. …”
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Adaptive building engineering component extraction model based on DSOD by Na Lv, Xuan Yang

“…With the purpose to bring up the extraction efficiency and accuracy of building construction image component information, the dense block structure and loss function were proposed to optimize the deep supervised object detection algorithm, and an adaptive building construction component extraction model based on this algorithm was constructed. …”
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SGDO-SLAM: A Semantic RGB-D SLAM System with Coarse-to-Fine Dynamic Rejection and Static Weighted Optimization by Qiming Hu, Shuwen Wang, Nanxing Chen, Wei Li, Jiayu Yuan, Enhui Zheng, Guirong Wang, Weimin Chen

“…The method achieves accurate dynamic scene perceptions and improves the accuracy of the system’s positioning. …”
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Nondestructive detection of rape leaf chlorophyll level based on Vis/NIR spectroscopy by YAO Jian-song, YANG Hai-qing, HE Yong

“…The procedure of shaping the predictive model was as follows: firstly, prediction equation of rape leaf chlorophyll level was created with uncertain parameters; secondly, a standard genetic algorithm (GA) was designed for parameter optimization. …”
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Optimized Design and Deep Vision-Based Operation Control of a Multi-Functional Robotic Gripper for an Automatic Loading System by Yaohui Wang, Sheng Guo, Jinliang Zhang, Hongbo Ding, Bo Zhang, Ao Cao, Xiaohu Sun, Guangxin Zhang, Shihe Tian, Yongxu Chen, Jixuan Ma, Guangrong Chen

“…A deep vision-based recognition system, enhanced by an improved YOLOv5 algorithm and multi-feature fusion, was employed for real-time object detection and pose estimation. …”
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Virtual power plant to ensure reliable power supply and accident-free operation of process equipment of a mining enterprise by Telmanova E.D., Abdrakhmanov I.D.

“…The paper presents a schematic diagram and stages of building a mathematical model of BAS. Structural optimization of this algorithm, which improves the topology of the system, has been performed. …”
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A comparison study and multi-objective optimization of a DICI engine fueled with petroleum diesel and Fischer-Tropsch diesel by Panpan Cai, Zheng Jing, Chunhua Zhang, Bing Han, Gang Li, Wenlong Song

“…Subsequently, non-dominated sorting genetic algorithm (NSGA-II) is applied to realize multi-objective optimization of fuel economy and emissions. …”
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Enhancing Route Optimization in Road Transport Systems Through Machine Learning: A Case Study of the Dakhla-Paris Corridor by Najib El Karkouri, Lahcen Hassine, Younes Ledmaoui, Hasna Chaibi, Rachid Saadane, Nourddine Enneya, Mohamed El Aroussi

“…The study relies on applying advanced mathematical modeling techniques and analyzing several datasets to train various machine learning algorithms. …”
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Optimizing travel time reliability with XAI: A Virginia interstate network case using machine learning and meta-heuristics by Navid Khorshidi, Shahriar Afandizadeh Zargari, Soheil Rezashoar, Hamid Mirzahossein

“…This paper applies machine learning models to predict travel time reliability in transportation networks, using XGBoost, LightGBM, and CatBoost optimized with seven metaheuristic algorithms. …”
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Complex Working Condition Bearing Fault Diagnosis Based on Multi-Feature Fusion and Improved Weighted Balance Distribution Adaptive Approach by Jing Yang, Yanping Bai, Ting Xu, Rong Cheng, Wendong Zhang, Guojun Zhang

“…In order to improve the accuracy and generalization ability of fault diagnosis for rotating machinery bearings under complex working conditions, a new model based on multi-feature fusion and improved weighted balance distribution adaptation is proposed. …”
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Timetable Design of Metro Train Based on RegenerativeBraking Energy Utilization by HE Deqiang, WANG Heliang, TAN Wenju, MIAO Jian

“…The multiple vehicles energy-saving optimization model wasbuilt based on the use of regenerative braking energy and the design of timetable. …”
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Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

“…The applied cost functions demonstrated the high accuracy of the models in predicting system performance. A genetic algorithm was employed for single-objective optimization targeting three criteria: maximizing total efficiency, minimizing pressure drop, and maximizing the Nusselt number. …”
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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

“…We also present the Spider Wasp Optimization (SWO) algorithm, which aims to improve performance by feature selection. …”
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Discovering hierarchical process models: an approach based on events partitioning by Antonina K. Begicheva, Irina A. Lomazova, Roman A. Nesterov

“…Currently, many companies are using this technology to optimize and improve their business processes. However, a discovered process model may be too detailed, sophisticated, and difficult for experts to understand. …”
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Medical laboratory data-based models: opportunities, obstacles, and solutions by Jiaojiao Meng, Moxin Wu, Fangmin Shi, Ying Xie, Hui Wang, You Guo

“…Proposed solutions include establishing standardized data formats, utilizing deep learning frameworks, employing distributed computing, improving interpretability, and implementing techniques like federated learning and algorithm optimization to address bias and safeguard privacy. …”
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Empc-based V2G scheduling strategy for multi-attribute EVs aggregator by Haoyang Tang, Zhilu Liu, Lin Zheng, Jianfeng Zheng, Hao Hu, Jinpei Lu, Zhijian Hu

“…First, a multi-attribute EVs aggregation model is established based on Markov chains. The batteries in the battery swapping station are considered in this model Second, an economic model predictive control (EMPC) algorithm is proposed to solve the aggregation model. …”
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Optimal 5G Network Sub-Slicing Orchestration in a Fully Virtualised Smart Company Using Machine Learning by Abimbola Efunogbon, Enjie Liu, Renxie Qiu, Taiwo Efunogbon

“…The framework leverages the LazyPredict module to automatically select optimal supervised learning algorithms based on real-time network conditions and historical data. …”
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Parametric Model for Coaxial Cavity Filter with Combined KCCA and MLSSVR by Shengbiao Wu, Huaning Li, Xianpeng Chen

“…First, the low-dimensional tuning data is mapped to the high-dimensional feature space by kernel canonical correlation analysis, and the nonlinear feature vectors are fused by the kernel function; second, the multioutput least squares support vector regression algorithm is used for parametric modeling to solve the problems of low accuracy and poor prediction performance; third, the support vector of the parameter model is optimized by the differential evolution whale algorithm (DWA) to improve the convergence and generalization ability of the model in actual tuning. …”
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A novel hybrid model for predicting the bearing capacity of piles by Li Tao, Xinhua Xue

“…The main objective of this study is to propose a hybrid model coupling least squares support vector machine (LSSVM) with an improved particle swarm optimization (IPSO) algorithm for the prediction of bearing capacity of piles. …”
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Refining efficiency in standalone proton exchange membrane fuel cell systems through gross hopper optimization-based maximum power point tracking control by Nethra K., Reddy K. Jyotheeswara, Dash Ritesh, Parida Prasanta Kumar, Swain Sarat Chandra, Dhanamjayulu C., Mahapatro Abinash

“…To further improve prediction accuracy, the GHO algorithm incorporates a natural cubic-spline prediction model within its iterative mechanism, which enhances power generation predictions under dynamic conditions such as abrupt changes in fuel cell temperature and reactant partial pressure. …”
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