Novel CP model and CP-assisted meta-heuristic algorithm for flexible job shop scheduling with preventive maintenance by Lixin Zhao, Leilei Meng, Weiyao Cheng, Yaping Ren, Biao Zhang, Hongyan Sang

“…Finally, the experimental evaluation on benchmark instances validates the capability of the CP model and CVNSQ-CP. Specifically, compared with existing mathematical models, the proposed CP model proves 3 new optimal solutions and improves 11 current best-known solutions for FJSP-FPM, and it improves 13 current best-known solutions for FJSP-PPM. …”
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Modeling of biodiesel production using optimization designs from literature: aiming to reduce the laboratory workload by Iver Bergh Hvidsten, Kristian Hovde Liland, Oliver Tomic, Jorge Mario Marchetti

“…This study explores non-linear tree-based learning algorithms for modeling biodiesel reactions. A dataset of 3038 reaction samples from 111 published studies was compiled, each optimizing distinct biodiesel reaction systems. …”
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Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment by Eunmok Yang, Sooyong Jeong, Changho Seo

“…Besides, the feature pruning process is performed using an improved pelican optimization algorithm (IPOA), which enables the choice of an optimal subset of features. …”
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Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

“…To accurately predict the erosion rate of coiled tubing, this study studied the influence law of erosion rate through experiments, screened the main influencing factors of erosion rate by grey relational analysis (GRA), and established a back-propagation neural network (BPNN) model optimized by the sparrow search algorithm (SSA) to predict the erosion rate. …”
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Predictive Model for Diagnosis of Gestational Diabetes in the Kurdistan Region by a Combination of Clustering and Classification Algorithms: An Ensemble Approach by Rasool Jader, Sadegh Aminifar

“…The suggested model uses the clustering KMeans technique for data reduction and the elbow method to find the optimal k value and the Mahalanobis distance method to find more related cluster to new samples, and the classification methods such as decision tree, random forest, SVM, KNN, logistic regression, and Naïve Bayes are used for prediction. …”
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Action Recognition, Tracking, and Optimization Analysis of Training Process Based on SVR Model and Multimedia Technology by Xuejiao Zhong

“…In order to explore the action recognition, tracking, and optimization analysis of the training process based on the SVR model and multimedia technology, the author proposes based on the radial basis function model, researching a new surrogate model technology-support vector regression (SVR). …”
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A Two-Stage Optimization Model for Airport Stand Allocation and Ground Support Vehicle Scheduling by Mengyun Yao, Minghua Hu, Jianan Yin, Jiaming Su, Mengxuan Yin

“…The NSGA-II algorithm, combining local search strategies (LS-NSGA-II), is used to solve the model. …”
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An Efficient Parametric Modeling, Evaluation and Optimization Strategy for Aerodynamic Configuration Design of eVTOL Aircraft by Yiming Du, Zehao Liu, Meizhu Shen, Jiang Wu, Kexin Zhang, Chuanye Jiang, Jiale Zhong

“…A phased collaborative aerodynamic design strategy for eVTOL aircraft was established, by combining the OpenVSP platform for rapid parametric modeling and evaluation, a Kriging surrogate framework with an improved differential evolution algorithm for optimization, and the SUAVE platform for propeller reverse design. …”
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Research on adverse event classification algorithm of da Vinci surgical robot based on Bert-BiLSTM model by Tianchun Li, Wanting Zhu, Wenke Xia, Li Wang, Weiqi Li, Peiming Zhang

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Improving distributed systems failure prediction via multi-objective feature selection and deep forest by Zhidan Yuan, Yikai Zhang, Yingqi Yu, Taizhi Lv, Tao Huang

“…This optimization process is achieved through the NSGA-III algorithm. …”
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Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model by Heng Cao, Qianhui Gao

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Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm by Xiaole Tang, Hao Lu, Yanting Kang, Wenjun Zhao

“…The substantial volatility of photovoltaic (PV) power output presents challenges to the stable operation of power grids. To improve the accuracy and stability of PV power prediction, this study proposes a PV power prediction system based on a dual-layer decomposition strategy and a dynamic grouping multi-objective Coati optimization algorithm (DGMOCOA). …”
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An improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor and its application for predicting molten iron temperature in the blast furnace by Zhendong Liu, Yiming Fang, Le Liu, Shuidong Ma

“…Abstract In response to the problem of poor search performance and difficulty in escaping from the local optimum in the Harris hawks optimizer, an improved Harris hawks optimizer with enhanced logarithmic spiral and dynamic factor (IHHO‐ELSDF) is proposed in this paper. …”
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Advancing Dynamic Emergency Route Optimization with a Composite Network Deep Reinforcement Learning Model by Jin Zhang, Hao Xu, Ding Liu, Qi Yu

“…This method utilizes the actor–critic framework, combined with attention mechanisms, pointer networks, and long short-term memory neural networks, to determine effective disaster relief path, and it compares the obtained scheduling scheme with the results obtained from the DRL algorithm based on the single-network model and ant colony optimization (ACO) algorithm. …”
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Enhancing E-Nose Performance via Metal-Oxide Based MEMS Sensor Arrays Optimization and Feature Alignment for Drug Classification by Ruiwen Kong, Wenfeng Shen, Yang Gao, Dawu Lv, Ling Ai, Weijie Song, Ruiqin Tan

“…This article introduces a novel approach to improve electronic nose classification accuracy by optimizing sensor arrays and aligning features. …”
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Methods and Algorithms for Decision-Making in Agro-Industrial Environmental Management by Olga Ivashchuk, Vyacheslav Fedorov, Zhanat Kenzhebayeva, Oleg Ivashchuk, Moldir Allaniyazova, Kaiyrbek Makulov, Gulnar Kaziyeva

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Enhancing Neural Network Training Through Neuroevolutionary Models: A Hybrid Approach to Classification Optimization by Hyasseliny A. Hurtado-Mora, Luis A. Herrera-Barajas, Luis J. González-del-Ángel, Roberto Pichardo-Ramírez, Alejandro H. García-Ruiz, Katea E. Lira-García

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A Hybrid Deep Learning and Improved SVM Framework for Real-Time Railroad Construction Personnel Detection with Multi-Scale Feature Optimization by Jianqiu Chen, Huan Xiong, Shixuan Zhou, Xiang Wang, Benxiao Lou, Longtang Ning, Qingwei Hu, Yang Tang, Guobin Gu

“…Finally, an SVM classification algorithm is employed for personnel detection. To process small sample categories, data enhancement techniques (e.g., random flip and rotation) and K-fold cross-validation are applied to optimize the model parameters. …”
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An integrated optimization model of network behavior victimization identification based on association rule feature extraction by Shengli ZHOU, Linqi RUAN, Rui XU, Xikang ZHANG, Quanzhe ZHAO, Yuanbo LIAN

“…The identification of the risk of network behavior victimization was of great significance for the prevention and warning of telecom network fraud.Insufficient mining of network behavior features and difficulty in determining relationships, an integrated optimization model for network behavior victimization identification based on association rule feature extraction was proposed.The interactive traffic data packets generated when users accessed websites were captured by the model, and the implicit and explicit behavior features in network traffic were extracted.Then, the association rules between features were mined, and the feature sequences were reconstructed using the FP-Growth algorithm.Finally, an analysis model of telecom network fraud victimization based on network traffic analysis was established, combined with the stochastic forest algorithm of particle swarm optimization.The experiments show that compared with general binary classification models, the proposed model has better precision and recall rates and can effectively improve the accuracy of network fraud victimization identification.…”
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The Spatial Distribution and Driving Mechanism of Soil Organic Matter in Hilly Basin Areas Based on Genetic Algorithm Variable Combination Optimization and Shapley Additive Explana... by He Huang, Yaolin Liu, Yanfang Liu, Zhaomin Tong, Zhouqiao Ren, Yifan Xie

“…Based on the genetic algorithm, 47 environmental variables are combined and optimized to construct a random forest (RF) model and an improved version—a random forest model based on genetic algorithm variable combination optimization (RF-GA). …”
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