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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Estimating the Aboveground Biomass of an Evergreen Broadleaf Forest in Xuan Lien Nature Reserve, Thanh Hoa, Vietnam, Using SPOT-6 Data and the Random Forest Algorithm by The Dung Nguyen, Martin Kappas

“…Adding texture features into the predictor variables did not improve the model performance. In addition, the SPOT-6 sensor has the potential to predict forest AGB using the RF algorithm.…”
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A multi task learning framework using DeBERTa and BWO optimization for enhancing long term english vocabulary memory by Jiasheng Zhu

“…This study shows that the BWO-optimized DeBERTa multi-task learning model can effectively improve the long-term memory retention of English words and has stronger anti-interference ability in complex memory environments.…”
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Implementation of YOLOv7 Model for Human Detection in Difficult Conditions by Arijal B, Andi Sunyoto, M. Hanafi

“…These findings not only demonstrate the relevance of YOLOv7 as a reliable human detection algorithm, but also provide a basis for further optimization of YOLOv7-based human detection systems, both through improving the model architecture and adapting to more specific datasets. …”
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Diagnosis Method for High-Speed Train Axle Box Bearing Slight Faults Based on Improved SAE and Temperature-Vibration Fusion by XU Xiao, SONG Dongli, WANG Zifan

“…［Method］ First, an AE (auto encoder) driven bearing temperature feature extraction method is designed to obtain the abnormal bearing temperature features, and EMD (empirical modal decomposition) method is used to process the vibration signal，so as to obtain the statistical features of the effective vibration IMF (intrinsic modal function). Then, by optimizing the dimensionality reduction algorithm based on SAE (stacked auto encoder), an effective fusion method of temperature-vibration features is proposed to achieve nonlinear fusion and dimensionality reduction of temperature and vibration features. …”
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Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression by Hui Xu, Hui Xie, Guangxian Li

“…To address these challenges, this paper presents an innovative tool wear prediction method that integrates a nonlinear mean function and a multi-kernel function-optimized GPR model combined with an LSTM-enhanced particle filter algorithm. …”
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Detection of egg appreance based on Fasternet and YOLOv5 model by WEI Jingxin, CHEN Zhongju, XU Haoran

“…Compared with YOLOv7-tiny and YOLOv8 models, the improved model has significant advantages.ConclusionThe experimental method can optimize the detection percision and reduces the parameters in the detection of egg' appreance, so as to achieve the purpose of identifying defected eggs in the automatic production. …”
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Improving Soil Heavy Metal Lead Inversion Through Combined Band Selection Methods: A Case Study in Gejiu City, China by Ping He, Xianfeng Cheng, Xingping Wen, Yi Cao, Yu Chen

“…To construct a preliminary Pb content prediction model, the initial selection of spectral bands utilized methods including CARS (Competitive Adaptive Reweighted Sampling), GA (Genetic Algorithm), MI (mutual information), SPA (Successive Projections Algorithm), and WOA (Whale Optimization Algorithm). …”
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A Fusion Model for Predicting the Vibration Trends of Hydropower Units by Dong Liu, Youchun Pi, Zhengyang Tang, Hongpeng Hua, Xiaopeng Wang

“…The fusion model first employed a waveform matching extension method based on parameter ergodic optimization to extend the original signal. …”
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Prediction of peripheral lymph node metastasis (LNM) in thyroid cancer using delta radiomics derived from enhanced CT combined with multiple machine learning algorithms by Wenzhi Wang, Feng Jin, Lina Song, Jinfang Yang, Yingjian Ye, Junjie Liu, Lei Xu, Peng An

“…Abstract Objectives This study aimed to develop a model for predicting peripheral lymph node metastasis (LNM) in thyroid cancer patients by combining enhanced CT radiomic features with machine learning algorithms. …”
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Stiffness Optimization for Hybrid Electric Vehicle Powertrain Mounting System in the Context of NSGA II for Vibration Decoupling and Dynamic Reaction Minimization by Zhanpeng Fang, Qihang Li, Lei Yao, Xiaojuan Hu

“…A 6-DOF dynamic model was established to analyze the decoupling rate and frequency distribution in its inherent characteristics, calculate the dynamic reaction of the suspension system, set the decoupling rate and the dynamic reaction of the suspension as optimization objectives, and use the NSGA II (Non-dominated Sorting Genetic Algorithm II) optimization algorithm to optimize the stiffness of the suspension. …”
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Optimizing Electric Cold-Chain Vehicle Scheduling for Sustainable Urban Logistics: A Novel Framework Balancing Freshness and Vehicle Charging by Zhenkun Gan, Peiwu Dong, Zhengtang Fu, Yanbing Ju, Yajun Shen

“…Subsequently, we develop a mixed-integer programming model to optimize freshness preservation. Additionally, we design a state-of-the-art algorithm based on an improved genetic algorithm to solve the scheduling model effectively. …”
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Two-stage strategic optimal planning of distributed generators and energy storage systems considering demand response program and network reconfiguration by Saleh Ba-swaimi, Renuga Verayiah, Vigna K. Ramachandaramurthy, Ahmad K. ALAhmad, Sanjeevikumar Padmanaban

“…This work presents a stochastic two-stage mixed-integer nonlinear programming (MINLP) optimization model for the long-term planning of a distribution system (DS) to improve renewable energy integration over a ten-year period. …”
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