An Overlapping IBM-PISO Algorithm with an FFT-Based Poisson Solver for Parallel Incompressible Flow Simulations by Jiacheng Lian, Qinghe Yao, Zichao Jiang

“…This study addresses computational challenges in the immersed boundary method (IBM) with the pressure implicit with split operator (PISO) algorithm for simulating incompressible flows. We introduce a novel time-step splitting method to implement communication overlapping optimization, aiming to reduce costs dominated by the pressure Poisson solver. …”
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NVH Analysis and Optimization of Light Truck Electric Drive Axles Based on Romax by Hao Yingbo, Liu Lidong

“…In order to reduce the fluctuation of transmission error of the gear, the micro modification of the reducer gear was carried out by using genetic algorithm, thus the excitation of the electric drive axle caused by the gear meshing was reduced, and the NVH performance of the electric drive axle was further improved. …”
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An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…Currently, more and more intrusion detection systems based on machine learning and deep learning are being applied to SDN, but most have drawbacks such as complex models and low detection accuracy. This paper proposes an enhanced spider wasp optimizer (ESWO) algorithm for feature dimensionality reduction of intrusion detection datasets and constructs a new intrusion detection model (IDM), namely ESWO-IDM, for SDN. …”
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Optimization design and experiment of cam-elliptical gear combined vegetables curved surface labeling mechanism by Lei Zhang, Lei Zhang, Heng Zhou, Jianneng Chen, Jianneng Chen, Junhua Tong, Junhua Tong, Yang Liu, Xiaowei Zhang

“…In order to improve the motion performances of the cam-elliptical gear combined labeling mechanism and avoid labels damage, the NSGA-II algorithm is used to optimize the parameters of the mechanism, resulting in 80 sets of Pareto solutions. …”
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Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm by Rafiqul Islam, Md. Arif Hossain

“…This paper introduces a novel methodology for predicting Unconfined Compressive Strength (UCS) in rocks by integrating Support Vector Regression (SVR) with two cutting-edge optimization algorithms: the Seahorse Optimizer (SO) and the COOT Optimization Algorithm (COOT). …”
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A New Computer-Aided Diagnosis System for Breast Cancer Detection from Thermograms Using Metaheuristic Algorithms and Explainable AI by Hanane Dihmani, Abdelmajid Bousselham, Omar Bouattane

“…To achieve these goals, we proposed a new multi-objective optimization approach named the Hybrid Particle Swarm Optimization algorithm (HPSO) and Hybrid Spider Monkey Optimization algorithm (HSMO). …”
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Construction and Application of Agricultural Talent Training Model Based on AHP-KNN Algorithm by Shubing Qiu, Yong Liu, Xiaohong Zhou

“…To solve this problem, an improved AHP-KNN algorithm is proposed by combining the analytic hierarchy process (AHP) and the optimized K-nearest neighbor algorithm, and an agricultural talent training model is proposed based on this algorithm. …”
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Application of High Efficiency and High Precision Network Algorithm in Thermal Capacity Design of Modular Permanent Magnet Fault-Tolerant Motor by Yunlong Yi, Sheng Ma, Bo Zhang, Wei Feng

“…Aiming at the problems of low thermal analysis efficiency and high computational cost of traditional computational fluid dynamics (CFD) methods for modular fault-tolerant permanent magnet synchronous motors (MFT-PMSMs) under complex working conditions, this paper proposes a fast modeling and calculation method of motor temperature field based on a high-efficiency and high-precision network algorithm. …”
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Adaptive k-means clustering algorithm based on grid and domain centroid weight by Wei CAI, Guangyu SUN, Fei YANG, Bo YAO, Chuanxian LI

“…Furthermore, when the clustering accuracy exceeded 99％ compared to the k-means algorithm, the computational efficiency was significantly improved. …”
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PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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Optimization of Adversarial Reprogramming for Transfer Learning on Closed Box Models by Alexander Bott, Moritz Siems, Alexander Puchta, Jurgen Fleischer

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An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…Finally, the stacking situations before and after optimization were compared. Compared to the traditional stacking method used before optimization, the optimized stacking distribution scheme improved by 19.35%, 4.97%, and 62.23% under the three objectives, respectively, indicating a more significant optimization effect.ConclusionsBased on the actual demand of enterprises for optimizing automatic steel plate warehouse loading decisions, the PCDMOPSO algorithm has demonstrated good performance in the simulation test of solving the stack allocation model. …”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…The framework uses an enhanced particle swarm optimization (PSO) algorithm to reconcile competing goals, including maintaining operator safety, optimizing asset reliability, and minimizing maintenance costs. …”
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Optimizing multimodal timetable synchronization of intercity railway and metro for the first service period during holidays by Yan Liu, Quan Zhang, Xuan Li, Yang Shi

“…To solve the model, an improved artificial bee colony algorithm (ABC) is designed, incorporating adaptive neighbour search and simulated annealing techniques. …”
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Optimal Configuration of ESS in Distribution Network Considering Generation of PV-Load Time Series Scenarios by Xiaolong Xiao, Mingming Shi, Fan Wu, Yukai Wei, Bo Zhao, Fang Zhang

“…To solve the high-dimensional multi-objective functions in the model, an non-dominated sorting genetic algorithm-III (NSGA-III) was employed, and the optimal solution is selected by using the entropy weight method (EWM). …”
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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

“…Finally, an improved gray wolf optimization algorithm integrated with an extreme learning machine (IMGWO-ELM) classifies the images as either healthy or glaucomatous. …”
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Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm by Fen Yang

“…The results show that the big data integration system based on big data and dynamic decision tree algorithm has high adaptability. Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. …”
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An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System by Shengjun Wu, Qingshan Xu, Qun Li, Xiaodong Yuan, Bing Chen

“…Then, a particle swarm optimization (PSO) algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. …”
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Intelligent interference decision algorithm with prior knowledge embedded LSTM-PPO model by ZHANG Jingke, YANG Kai, LI Chao, WANG Hongyan

“…Focusing on the issues of low efficiency and effectiveness in decision-making as well as the instability of traditional reinforcement learning model-based multi-function radar (MFR) jamming decision algorithms, a prior knowledge embedded long short-term memory (LSTM) network-proximal policy optimization (PPO) model based intelligent interference decision algorithm was developed. …”
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