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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Robust Adversarial Example Detection Algorithm Based on High-Level Feature Differences by Hua Mu, Chenggang Li, Anjie Peng, Yangyang Wang, Zhenyu Liang

“…To address these challenges, this paper introduces a novel adversarial example detection algorithm based on high-level feature differences (HFDs), which is specifically designed to improve robustness against both attacks and preprocessing operations. …”
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Service clustering method based on description context feature words and improved GSDMM model by Qiang HU, Jiaji SHEN, Guanghui JING, Junwei DU

“…To address the problem that current service clustering methods usually faced low quality of service representation vectors, a service clustering method based on description context feature words and improved GSDMM model was proposed.Firstly, a feature word extraction method based on context weight was constructed.The words that fit well with the context of service description were extracted as the set of feature words for each service.Then, an improved GSDMM model with topic distribution probability correction factor was established to generate service representation vectors and achieve distribution probability correction for non-critical topic items.Finally, K-means++ algorithm was employed to cluster Web services based on these service representation vectors.Experiments were conducted on real Web services in Web site of Programmable Web.Experiment results show that the quality of service representation vectors generated by the proposed method is higher than of other topic models.Further, the performance of our clustering method is significantly better than other service clustering methods.…”
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FAULT DIAGNOSIS METHOD OF SUBMERSIBLE SEWAGE PUMP BASED ON IMPROVED HOPFIELD NEURAL NETWORK by WANG Hui, LI NanQi, YANG ZhiPeng, ZHAO GuoChao, TIAN LiYong

“…The connection weights of HNN neural network were optimized by particle swarm optimization（PSO） algorithm to improve the global convergence ability of the improved neural network, and the improved HNN neural network model was obtained. …”
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Algorithm for Constructing the Hazard Function of the Extended Cox Model and its Application to the Prostate Cancer Patient Database by I. I. Mikulik, G. M. Zharinov, A. Yu. Kneev

“…The quality of training of the Cox model was assessed by C-index.Results. A metaheuristic algorithm for ant pollinator optimizing was proposed, providing for the construction of hazard functions of the extended Cox model. …”
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Research on Springback Compensation Method of Roll Forming Based on Improved Fuzzy PID Control by Tengqiang Wang, Yingping Qian, Wengkang Fang, Dongqiao Zhang, Huanqi Weng, Yiran Jiang

“…To enhance the forming accuracy of circular rolling, this paper proposes a control strategy for compensating the springback of sheet metals by altering the rolling angle. A kinematic model for circular rolling springback compensation is established to monitor the forming radian of the sheet metal in real time. …”
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The Application of Self-adaption Kalman Filtering Algorithm Based on the Current Statistic Model in the Tram’s GPS Positioning by Shan ZHANG, Hui LI, Haizhou TANG

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Improving Modularity Regularization Techniques for Estimating Structures in Complex Network by Samaa F. Ibraheem, Basad Al-Sarray

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Convolution neural network algorithm-based fouling organisms classification model of seawater circulation cooling system by ZHANG Yi

“…In this paper, the convolution neural network algorithm was used to establish the classification and recognition model of fouling organisms, and to realize the automatic classification and recognition of common fouling organisms. …”
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A Hybrid Algorithm with a Data Augmentation Method to Enhance the Performance of the Zero-Inflated Bernoulli Model by Chih-Jen Su, I-Fei Chen, Tzong-Ru Tsai, Yuhlong Lio

“…This zero-inflated structure significantly contributes to data imbalance. To improve the ZIBer model’s ability to accurately identify minority classes, we explore the use of momentum and Nesterov’s gradient descent methods, particle swarm optimization, and a novel hybrid algorithm combining particle swarm optimization with Nesterov’s accelerated gradient techniques. …”
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A novel time difference of arrival localization algorithm using a neural network ensemble model by Zhenkai Zhang, Feng Jiang, Boyuan Li, Bing Zhang

“…The simulation results show that the proposed algorithm is efficient in improving the generalization ability and localization precision of the neural network ensemble model.…”
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Automatic Generation Technology of Safety Measures for Digital Substation Based on Improved Support Vector Machine by Yabing YAN, Xu CHU, Haolong XIAO, Wenwu LIANG, Hui LI, Zhenxing XIA

“…Firstly, construct a secondary circuit model and equipment model based on adjacency matrix, and further integrate the secondary security measure rule library to form a sample dataset; Secondly, support vector machines were used to classify secondary security measures, and bacterial foraging algorithms were introduced to optimize penalty factors and kernel parameters, effectively improving the training effectiveness of the automatic generation model for security measures; Finally, the effectiveness of the proposed method was verified through numerical examples.…”
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RS-DETR: An Improved Remote Sensing Object Detection Model Based on RT-DETR by Hao Zhang, Zheng Ma, Xiang Li

“…Experimental results on the satellite imagery multi-vehicles dataset (SIMD) and the high-resolution remote sensing object detection (TGRS-HRRSD) dataset show that the improved algorithm achieved mean average precision (mAP) of 78.2% and 91.6% at an intersection over union threshold of 0.5, respectively, which is an improvement of 2.0% and 1.5% over the baseline model. …”
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An improved pricing scheme for water rights trading based on the eBay auction model by LIN Lan, ZHAO Siyuan, CHEN Jing, DAI Xiaoping

“…【Method】We proposed an innovative pricing mechanism and a specific algorithm for determining transaction prices, based on a second-price auction, with modifications inspired by eBay’s auction model. …”
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Breast mass lesion area detection method based on an improved YOLOv8 model by Yihua Lan, Yingjie Lv, Jiashu Xu, Yingqi Zhang, Yanhong Zhang

“…This paper proposes the YOLOv8-GHOST-P2 model by combining the above two improvements. Experiments conducted on the MIAS and DDSM datasets show that the new models achieved significantly improved computational efficiency while maintaining high detection accuracy. …”
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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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A Deep Learning Algorithm of Neural Network for the Parameterization of Typhoon‐Ocean Feedback in Typhoon Forecast Models by Guo‐Qing Jiang, Jing Xu, Jun Wei

“…Abstract Two algorithms based on machine learning neural networks are proposed—the shallow learning (S‐L) and deep learning (D‐L) algorithms—that can potentially be used in atmosphere‐only typhoon forecast models to provide flow‐dependent typhoon‐induced sea surface temperature cooling (SSTC) for improving typhoon predictions. …”
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Advances to IoT security using a GRU-CNN deep learning model trained on SUCMO algorithm by Amit Sagu, Nasib Singh Gill, Preeti Gulia, Noha Alduaiji, Piyush Kumar Shukla, Mohd Asif Shah

“…The SUCMO algorithm fine-tunes the deep learning model’s hyperparameters to improve classification accuracy. …”
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Short-Term Power Load Forecasting Using an Improved Model Integrating GCN and Transformer by Man Wu, Wanyi Feng, Xinya Li, Yunan Liu, Chuxin Cao

“…Therefore, in order to improve prediction accuracy, this study designs a short-term power load forecasting model integrating multi-scale GCN and the improved Transformer, as well as the prediction method based on this model. …”
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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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