An intelligent object detection and classification framework for assisting visually challenged persons using deep learning and improved crow search optimization by Alaa O. Khadidos, Ayman Yafoz

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An ensemble agglomerative hierarchical clustering algorithm based on clusters clustering technique and the novel similarity measurement by Teng Li, Amin Rezaeipanah, ElSayed M. Tag El Din

“…MCEMS uses the bi-weighting policy to solve the model selection associated problem to improve ensemble clustering. …”
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An improved multiclass classification of acute lymphocytic leukemia using enhanced glowworm swarm optimization by Saranya N, Kalamani M

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An Improved Point Cloud Filtering Algorithm Applies in Complex Urban Environments by Guangyu Liang, Ximin Cui, Debao Yuan, Liuya Zhang, Renxu Yang

“…It then constructs a TIN model based on the initial ground points, incorporating the concept of the progressive TIN densification (PTD) algorithm. …”
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Algorithms and probabilistic models of parameters of operation of in-plant power supply by E. I. Gracheva, O. V. Naumov, A. N. Gorlov, Z. M. Shakurova

“…To investigate the operability of low-voltage shop networks of radial, trunk and mixed structure in optimal operating conditions of the equipment when modeling the impact of external factors, such as the root-mean-square load factor of the equipment, the temperature of the shop room and the calculated time interval on the operating parameters of the system. …”
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Analytical MPC Algorithm Using Steady-State Process Model by Piotr M. Marusak

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Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

“…In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
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Research on the optimization model of anti-breast cancer candidate drugs based on machine learning by Zhou Dong, Hong Chen, Yuchen Yang, Hairong Hao

“…Additionally, a multi-model fusion strategy and Particle Swarm Optimization (PSO) algorithm were employed to optimize both biological activity and ADMET properties, thereby improving the prediction of Caco-2, CYP3A4, hERG, HOB, and MN properties. …”
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Robust Adaptive Path Tracking Control Scheme for Safe Autonomous Driving via Predicted Interval Algorithm by Cong Phat Vo, Jungeun Lee, Jeong Hwan Jeon

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Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases by A. Naderi Beni, H. Bagherpour, J. Amiri Parian

“…Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. …”
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Optimization of Rotary Blade Wear and Tillage Resistance Based on DEM-MBD Coupling Model by Zhiqiang Mao, Yang Zhang, Keping Zhang, Jiuxin Wang, Junqian Yang, Xiaobao Zheng, Shuaikang Chen, Zhongqing Yang, Biao Luo

“…To solve the problems of high tillage resistance and the rapid wear of the rotary blade during tillage, this study employed a coupled algorithm of the discrete element method (DEM) and multi-body dynamics (MBD) with Hertz–Mindlin with JKR particle contact theory to establish a rotary blade–sandy soil model. …”
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Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms by Dongmei Yu, Zitao Wang, Chao Yue, Jianping Wang

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Research on Reactive Power Optimization Strategy under the Intelligent Improvement Model of the Distribution Network by Menglin Yu

“…In order to improve the reactive power optimization effect of the distribution network, this paper combines the multiagent deep reinforcement learning algorithm to analyze the reactive power optimization strategy of the distribution network and constructs an intelligent optimization model. …”
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Complex Environmental Geomagnetic Matching-Assisted Navigation Algorithm Based on Improved Extreme Learning Machine by Jian Huang, Zhe Hu, Wenjun Yi

“…To enhance the matching performance of the NGO-ELM algorithm, three improvements are proposed to the NGO algorithm. …”
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RESEARCH ON PARAMETRIC ANALYSIS AND MULTI-OBJECTIVE OPTIMIZATION OF CYLINDRICAL PRESSURE STRUCTURE by LIU Feng, TU ChaoHua, ZHAO YanKai

“…In order to improve the design efficiency and performance of the cylindrical pressure structure,strength and stability analysis methods were determined,the initial scheme was analyzed. the second development of Abaqus software was carried out by using Python language,Abaqus was integrated with i Sight software,the parametric analysis flow of pressure structure was designed,could realize automatic modeling and analysis of cylindrical pressure structure. the most Latin hypercube method was used to selectting the sample points,the sensitivity analysis of the design variables were carried out,The comparison of the fitting accuracy shown that the response surface model had the highest accuracy,the approximate model of the cylindrical pressure structure based on the fourth-order response surface was obtained. the multi-objective optimization model was established,The second generation of non dominated sorting genetic algorithm was used to solving the multi-objective optimization problem,the results shown that the weight of the optimization scheme was reduced,while the ultimate strength was greatly improved,improved the performance of the cylindrical pressure structure.…”
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Efficient Task Scheduling Approach in Edge-Cloud Continuum based on Flower Pollination and Improved Shuffled Frog Leaping Algorithm by Nasiru Muhammad Dankolo Dankolo, Nor Haizan Mohamed Radzi, Noorfa Haszlinna Mustaffa, Mohd Shukor Talib, Zuriahati Mohd Yunos, Danlami Gabi

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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…In order to address the issues of low accuracy and poor interpretability in existing HFMD incidence prediction models, in this paper, we propose an interpretable prediction model, namely, ARIMA–LSTM–XGBoost, which integrates multiple meteorological factors with Autoregressive integrated moving average model (ARIMA), Long short-term memory (LSTM), Extreme gradient boosting (XGBoost), Grey wolf optimizer (GWO), Genetic algorithm (GA) and Shapley additive explanations (SHAP). …”
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Multi-UAV path planning considering multiple energy consumptions via an improved bee foraging learning particle swarm optimization algorithm by Yuanhang Qi, Haoran Jiang, Gewen Huang, Liang Yang, Fujie Wang, Yunjian Xu

“…To tackle the MUAVPP-MEC, this study proposes an improved Bee Foraging Learning Particle Swarm Optimization algorithm (IBFLPSO), which integrates the bee-foraging algorithm into the particle swarm optimization framework. …”
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Metaheuristics and Large Language Models Join Forces: Toward an Integrated Optimization Approach by Camilo Chacon Sartori, Christian Blum, Filippo Bistaffa, Guillem Rodriguez Corominas

“…Since the rise of Large Language Models (LLMs) a couple of years ago, researchers in metaheuristics (MHs) have wondered how to use their power in a beneficial way within their algorithms. …”
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Efficient workflow scheduling using an improved multi-objective memetic algorithm in cloud-edge-end collaborative framework by Guangzhang Cui, Wei Zhang, Weiwei Xu, Hujun Bao

“…This paper addresses this challenge by proposing an Improved Multi-Objective Memetic Algorithm (IMOMA) that simultaneously optimizes energy consumption and makespan. …”
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