Based on the improved SCGM(1,1)c and WIV rainfall landslide susceptible area prediction model by Qian Zhang, Shujie Cao, Yanliang Du, MingYuan Du, Yixuan Zhao, Yaoqi Nie

“…On the basis of the single factor system cloud grey model (SCGM (1,1)c), an improved SCGM (1,1)c model is proposed based on Markov prediction theory and CS algorithm optimization to predict rainfall. …”
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Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…This study presents Cybersecurity using a Crested Porcupine Optimizer Algorithm with Hybrid Deep Learning Models (CCPOA-HDLM). …”
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Research on the Time-varying Meshing Stiffness Algorithm of Spur Gears Based on an Improved Potential Energy Method by Xu Kejun, Jiao Wei, Qin Haiqin

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Concept of Artificial Intelligence-oriented Public Health Model in Cancer Care by Ivashchuk Oleksandr, Hovornyan Serhiy

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A Salvage Target Tracking Algorithm for Unmanned Surface Vehicles Combining Improved Line-of-Sight and Key Point Guidance by Jiahe Liu, Chao Liu, Mingmei Wen, Yang Wang, Jinzhe Wang, Rencheng Zheng

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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…To address the challenges of low path planning efficiency for autonomous undersea vehicle(AUV) in multi-target environments, as well as the limitations of the traditional whale optimization algorithm(WOA) in terms of susceptibility to local optima and inadequate adaptability to three-dimensional obstacle avoidance requirements, this study proposed a collaborative planning strategy that integrated a fluid perturbation algorithm with an improved WOA. …”
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Improve the robustness of algorithm under adversarial environment by moving target defense by Kang HE, Yuefei ZHU, Long LIU, Bin LU, Bin LIU

“…Traditional machine learning models works in peace environment,assuming that training data and test data share the same distribution.However,the hypothesis does not hold in areas like malicious document detection.The enemy attacks the classification algorithm by modifying the test samples so that the well-constructed malicious samples can escape the detection by machine learning models.To improve the security of machine learning algorithms,moving target defense (MTD) based method was proposed to enhance the robustness.Experimental results show that the proposed method could effectively resist the evasion attack to detection algorithm by dynamic transformation in the stages of algorithm model,feature selection and result output.…”
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Discrete-Event Simulation Integrates an Improved NEH Algorithm for Practical Flowshop Scheduling Problems in the Satellite Industry by Guangzhen Li, Lei Zhang

“…Therefore, we propose a more practical method that integrates discrete-event simulation modelling and an improved NEH algorithm to solve a more realistic PFSP. …”
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Development and external validation of prediction algorithms to improve early diagnosis of cancer by J. Hippisley-Cox, CA Coupland

“…Abstract Cancer prediction algorithms are used in the UK to identify individuals at high probability of having a current, as yet undiagnosed cancer with the intention of improving early diagnosis and treatment. …”
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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

“…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. …”
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One-to-many vehicle-cargo matching model considering consignor satisfaction by Jingshuai YANG, Yongkang LI, Weibo YANG

“…Then, a matching satisfaction model is constructed to maximize the matching satisfaction, and an improved genetic algorithm is designed and solved using Python. …”
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THE ALGORITHMIC MODEL OF LABORATORY DIAGNOSTICS OPTIMIZATION by G. I. Nazarenko, O. V. Andropova

“…Various algorithmic models, their features and structure are reviewed. …”
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Ripe Tomato Detection Algorithm Based on Improved YOLOv9 by Yan Wang, Qianjie Rong, Chunhua Hu

“…After collecting tomato data, we used Mosaic for data augmentation, which improved model robustness and enriched experimental data. …”
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Fault Diagnosis of Power Equipment Based on Improved SVM Algorithm by Youle Song, Yuting Duan, Tong Rao

“…Therefore, this study proposes an improved support vector machine model, combined with grey wolf optimization algorithm, aimed at improving the accuracy and efficiency of power equipment fault diagnosis. …”
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Improved Field Obstacle Detection Algorithm Based on YOLOv8 by Xinying Zhou, Wenming Chen, Xinhua Wei

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An improved YOLOv8n algorithm for dense pedestrian scenarios by Wang Lili, Fan Panpan, Zhang Shiyu

“…To address the issues of insufficient recognition accuracy and inaccurate detection of traditional algorithms in dense pedestrian scenarios, an improved dense pedestrian detection model based on YOLOv8n is proposed. …”
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Improving Genetic Algorithm with Fine-Tuned Crossover and Scaled Architecture by Ajay Shrestha, Ausif Mahmood

“…Our implementation tests show that leveraging these new concepts of mtDNA and Continental Model results in relative improvement of the optimization quality of GA.…”
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Improved RSSI Positioning Algorithm for Coal Mine Underground Locomotive by Bin Ge, Kai Wang, Jianghong Han, Bao Zhao

“…Aiming at the large positioning errors of traditional coal mine underground locomotive, an improved received signal strength indication (RSSI) positioning algorithm for coal mine underground locomotive was proposed. …”
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Underwater Object Detection Algorithm Based on an Improved YOLOv8 by Fubin Zhang, Weiye Cao, Jian Gao, Shubing Liu, Chenyang Li, Kun Song, Hongwei Wang

“…This paper proposes an underwater object detection algorithm based on an improved YOLOv8 model. First, the introduction of CIB building blocks into the backbone network, along with the optimization of the C2f structure and the incorporation of large-kernel depthwise convolutions, effectively enhances the model’s receptive field. …”
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Improved Cross Entropy Algorithm for the Optimum of Charge Planning Problem by Fan Yang, Qiqiang Li

“…To solve the charge planning problem involving charges and the orders in each charge, a traveling salesman problem based charge planning model and the improved cross entropy algorithm are proposed. …”
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