Vertebra CT Image Segmentation Method Based on Improved U-Net Model by LIU Xia, YU Hong-bo, LI Bing, WANG Bo

“…Firstly，it was improved and optimized on the basis of the classic u-net model. …”
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Analysis of optimal configuration of energy storage in wind-solar micro-grid based on improved gray wolf optimization by Huang Qian, Huang Dengke, Cai Li, Xu Qingshan

“…The mathematical model of the improved gray wolf optimization is constructed, and the typical landscape resource data of a residential district. …”
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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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Optimization of Mixed-Integer Non-Linear Electricity Generation Expansion Planning Problem Based on Newly Improved Gravitational Search Algorithm by F .J. Ardakani, M. M. Ardehali

“…This study aims to examine the applicability ofGravitational Search Algorithm (GSA) and the newly improved GSA (IGSA) for optimization of themixed-integer non-linear electricity generation expansion planning (GEP) problem. …”
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3D Deployment Optimization of Wireless Sensor Networks for Heterogeneous Functional Nodes by Zean Lu, Chengqun Wang, Peng Wang, Weiqiang Xu

“…To address this, an improved Secretary Bird Optimization Algorithm (ISBOA) is proposed, incorporating Gaussian Cuckoo Mutation and a smooth exploitation mechanism. …”
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Prediction of Mechanical Properties of Cotton Fibers by a BP Neural Network Model Optimized by Genetic Algorithm by Junyang Wang, Limin Zhang, Xiang Liu, Jinchan Zhang, Wanxin Wang, Hong Xu

“…The first 850 items of this dataset were then utilized to train the designed BP, and the remaining 28 items were evaluated for error. Next, the model is parameterized using a genetic algorithm to reduce the overall network size, thus optimizing the fit. …”
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A Water Quality Prediction Model Based on Long Short-Term Memory Networks and Optimization Algorithms by Aihua Yu, Qingjie Xiao

“…In comparison with the previous prediction models such as SVR, LSTM, CNN-LSTM and CNN-GRU, obviously, the prediction effect of AWPSO-LSTMAT is significantly improved by means of modifying and optimizing the original algorithm. …”
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Optimizing anomaly detection models for edge IIoT with an enhanced firefly algorithm-based hyperparameter tuning strategy by Mohemmed Yousuf Rahamathulla, Mangayarkarasi Ramaiah

“…This work presents an Enhanced Firefly Algorithm (EFA) for optimizing the hyperparameters of ML models to enable effective and accurate threat detection in resource-constrained IIoT contexts, so addressing these challenges. …”
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First-principle modeling of parallel-flow regenerative kilns and their optimization with genetic algorithm and gradient-based method by Michael Kreitmeir, Bruno Villela Pedras Lago, Ladislaus Schoenfeld, Sebastian Rehfeldt, Harald Klein

“…Finally, we use a genetic algorithm to optimize the feed mass flows such that the conversion and the fuel efficiency are improved in a Pareto-optimal manner. …”
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Leveraging retinanet based object detection model for assisting visually impaired individuals with metaheuristic optimization algorithm by Alaa O. Khadidos, Ayman Yafoz

“…This paper proposes a novel Object Detection Model for Visually Impaired Individuals with a Metaheuristic Optimization Algorithm (ODMVII-MOA) technique. …”
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Behavioral Modeling of SiC MOSFET Static and Dynamic Characteristics Based on Particle Swarm Optimization Algorithm by Zhibo Zhu, Yang Zhao, Wei Yan

“…This study proposes a SiC MOSFET behavioral model with parasitic parameters based on the particle swarm optimization (PSO) algorithm. …”
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Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model by Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

“…The optimal amount of data was determined to be between three and seven days, with an average model r² of 0.8811 and an RMSE of 2.056 for the gated recurrent unit algorithm. …”
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Optimization of social security patrol strategy based on graph theory and GGC algorithm by Jian Wang

“…The policy set and payoff function are defined, and a generalized geometric coverage algorithm is designed to solve the policy set of both parties in the model, thereby obtaining the optimal patrol strategy for intelligent patrol agents. …”
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Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm by Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb

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Optimal Temperature Calculation for Multicriteria Optimization of the Hydrogenation of Polycyclic Aromatic Hydrocarbons by NSGA-II Method by A. A. Alexandrova, S. N. Koledin

“…Introduction. Multicriteria optimization, taking into account contradicting criteria, is used to improve production efficiency, reduce costs, improve product quality and environmental safety of processes. …”
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Enhanced genetic algorithm for indoor low-illumination stereo matching energy function optimization by Zhang Hongjin, Wei Hui

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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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Research and application of optimization of physical education training model based on multi-objective differential evolutionary algorithm by Man Wu

“…In order to study the application of the multi-objective differential evolution algorithm in the field of sports transportation. Based on the improvement of multi-objective differential evolution algorithm, this paper proposes the training model of PE education, and compares the prediction results and the actual results. …”
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Cultural Heritage Color Regeneration: Interactive Genetic Algorithm Optimization Based on Color Network and Harmony Models by Zhonghua Jiang, Qianlong Xia, Zhizhou Wang, Kaiwei Zhu, Qianyu Su, Jiajun Wang, Yirui Huang, Bo Wu, Yan Hong

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Early detection of monkeypox: Analysis and optimization of pretrained deep learning models using the Sparrow Search Algorithm by Amna Bamaqa, Waleed M. Bahgat, Yousry AbdulAzeem, Hossam Magdy Balaha, Mahmoud Badawy, Mostafa A. Elhosseini

“…The novelty lies in using SpaSA to optimize pre-trained CNNs' performance. The Xception model achieves 97.66% accuracy without optimization. …”
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