Research on linear solvability of network coding based cooperative recovery scheme by Jun YIN, Xueqi SHA, Lei WANG, Dengyin ZHANG, Yuwang YANG

“…The linear solvability of network coding based cooperative recovery/repair (CR) scheme was studied.Specifically, the solvability analysis model for network coding based CR scheme was established, the upper and lower bounds of the probability for any receiver to decode all original information under arbitrary order of Galois coding field were proposed and proved, and an on-line solvability judgement algorithm was designed by improvement of Gauss-Jordan algorithm.Numerical results validate the compactness of the proposed upper and lower bounds as well as the short-time decoding waiting delay of the improved Gauss-Jordan algorithm.Node deployment experiments show that the decoding complexity of the improved Gauss Jordan algorithm is reduced by 35% compared with the traditional Gauss algorithm.…”
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Research on Cold Chain Logistics Joint Distribution Vehicle Routing Optimization Based on Uncertainty Entropy and Time-Varying Network by Huaixia Shi, Yu Hong, Qinglei Zhang, Jiyun Qin

“…The solution combines simulated annealing strategies with genetic algorithms. It also uses the entropy mechanism to optimize uncertainties, improving global search performance. …”
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Improved gated recurrent unit-based osteosarcoma prediction on histology images: a meta-heuristic-oriented optimization concept by S. Prabakaran, S. Mary Praveena

“…These extracted features undergo the final prediction phase that is accomplished by the novel improved recurrent gated recurrent unit (IGRU), in which the parameter tuning of GRU is accomplished by the osprey optimization algorithm (OOA) with the consideration of error minimization as the major objective function. …”
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Lightweight malicious domain name detection model based on separable convolution by Luhui YANG, Huiwen BAI, Guangjie LIU, Yuewei DAI

“…The application of artificial intelligence in the detection of malicious domain names needs to consider both accuracy and calculation speed,which can make it closer to the actual application.Based on the above considerations,a lightweight malicious domain name detection model based on separable convolution was proposed.The model uses a separable convolution structure.It first applies depthwise convolution on every input channel,and then performs pointwise convolution on all output channels.This can effectively reduce the parameters of convolution process without impacting the effectiveness of convolution feature extraction,and realize faster convolution process while keeping high accuracy.To improve the detection accuracy considering the imbalance of the number and difficulty of positive and negative samples,a focal loss function was introduced in the training process of the model.The proposed algorithm was compared with three typical deep-learning-based detection models on a public data set.Experimental results denote that the proposed algorithm achieves detection accuracy close to the state-of-the-art model,and can significantly improve model inference speed on CPU.…”
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Parameter identification of unmanned surface vehicle MMG model based on an improved extended Kalman filter by Pengbo SUN, Zaopeng DONG, Wei LIU, Jinliang SHENG, Zhihao LI

“…ObjectivesTo construct an accurate MMG （mathematical model group） model for a water-jet propulsion unmanned surface vehicle, the traditional extended Kalman filter algorithm and improved extended Kalman filter algorithm are combined with the real-world boat data for parameter identification. …”
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Rice disease and pest identification integrating albert pre-trained language model and improved BILSTM by Zhigui Dong, Tianyi Yang, Yanchao Wang

“…At the same time, a bidirectional long short-term memory network is introduced for further recognition, and the model is optimized using conditional random fields to design a fusion algorithm for rice disease and pest recognition. …”
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Improving the Accuracy of Neural Network Pattern Recognition by Fractional Gradient Descent by Ruslan I. Abdulkadirov, Pavel A. Lyakhov, Valentina A. Baboshina, Nikolay N. Nagornov

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Modelling and optimization of well hole cleaning using artificial intelligence techniques by Nageswara Rao Lakkimsetty, Hassan Rashid Ali Al Araimi, G. Kavitha

“…This study aims to improve the accuracy and practicality of hole cleaning assessment by applying Artificial Intelligence (AI) techniques, specifically Artificial Neural Networks (ANN) and Genetic Algorithms (GA), to predict downhole parameters and optimize drilling processes. …”
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An Improved Phase Space Reconstruction Method-Based Hybrid Model for Chaotic Traffic Flow Prediction by Yue Hou, Da Li, Di Zhang, Zhiyuan Deng

“…The proposed PDRGA optimization algorithm is a lightweight improvement of the traditional genetic algorithm (GA) and solves the problem that the model tends to fall into a local optimum by optimizing the initial weights of CDBN. …”
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Offline visual aid system for the blind based on image captioning by Yue CHEN, Yu GUO, Yuanyan XIE, Zhenqiang MI

“…In view of the inconveniences of existing visual aid systems for the blind, the method of running the image captioning model on portable mobile devices based on model pruning was discussed.Model pruning techniques and image captioning models were reviewed.An improved model pruning algorithm for image captioning model was proposed.Experimental results show that, on the premise of ensuring accuracy, the image captioning model after pruning can greatly reduce processing time and power consumption capacity, and can quickly and accurately describe environmental information and voice broadcast anytime and anywhere.…”
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Assimilating Satellite-Based Biophysical Variables Data into AquaCrop Model for Silage Maize Yield Estimation Using Water Cycle Algorithm by Elahe Akbari, Ali Darvishi Boloorani, Jochem Verrelst, Stefano Pignatti

“…To address this issue, assimilation of satellite vegetation products into these models can account for spatial variations in the land and improve estimation accuracy. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“… In view of the difficulty of snow leopard detection and recognition in infrared camera images, a snow leopard detection algorithm is proposed based on EfficientDet, which combines domain migration and new attention mechanism.Firstly, the algorithm adopts image enhancement to expand the training sample and adds non-snow leopard images to optimize the dataset structure to improve the robustness of the model. …”
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Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: application of a multi-objective parallel genetic algorithm. by Jaspreet Kaur, Anders Nygren, Edward J Vigmond

“…Fitting parameter sets of non-linear equations in cardiac single cell ionic models to reproduce experimental behavior is a time consuming process. …”
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The electromagnetic transient simulation acceleration algorithm based on delay mitigation of dynamic critical paths by Qi Guo, Yuanhong Lu, Jie Zhang, Jingyue Zhang, Libin Huang, Haiping Guo, Tianyu Guo, Liang Tu

“…By incorporating the proportion of task transmission delay as a guiding metric in the optimization process, processors can be prioritized for tasks with high latency, thereby improving computational efficiency. We first validate the theoretical feasibility of the algorithm using a theoretical case study and illustrate the algorithmic effectiveness using two real case studies, direct current (DC) model and alternating current (AC) model respectively. …”
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Bridge Deformation Monitoring Combining 3D Laser Scanning with Multi-Scale Algorithms by Dongmei Tan, Wenjie Li, Yu Tao, Baifeng Ji

“…To address the inefficiencies and limited spatial resolution of traditional single-point monitoring techniques, this study proposes a multi-scale analysis method that integrates the Multi-Scale Model-to-Model Cloud Comparison (M3C2) algorithm with least-squares plane fitting. …”
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Improved sub-band JND model with textural decomposition and its application in perceptual image coding by Ming-kui ZHENG, Kai-xiong SU, Wei-xing WANG, Cheng-dong LAN, Xiu-zhi YANG

“…In order to improve the accuracy of the just noticeable difference (JND) model in transform domain, an en-hanced JND model with a new method for contrast masking factor estimation was proposed. …”
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A new adaptive grey prediction model and its application by Jianming Jiang, Ming Zhang, Zhongyong Huang

“…Specifically, the Marine Predators Optimization algorithm is introduced to facilitate the model’s solution process. …”
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Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model by Lokesh Selvaraj, Balakrishnan Ganesan

“…In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. …”
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Air quality prediction enhanced by a CNN-LSTM-Attention model optimized with an advanced dung beetle algorithm by Xiaojie Zhou, Majid Khan Majahar Ali, Farah Aini Abdullah, Lili Wu, Ying Tian, Tao Li, Kaihui Li

“…This study proposes a hybrid CNN-LSTM-Attention model optimized with an improved Dung Beetle Optimization (IDBO) algorithm to enhance predictive performance. …”
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Physical fitness characteristics and comprehensive physical fitness evaluation model of basketball players based on association rule algorithm. by Yongkang Ding

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