Handling method for GPS outages based on PSO-LSTM and fading adaptive Kalman filtering by Xiaoming Li, Xianchen Wang, Can Pei

“…The PSO algorithm is utilized to optimize two hyperparameters, neuron count and learning rate, which are essential to improve the training efficiency and prediction accuracy in the LSTM model. …”
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Adaptive lift chiller units fault diagnosis model based on machine learning. by Yang Guo, Zengrui Tian, Hong Wang, Mengyao Chen, Pan Chu, Yingjie Sheng

“…In this paper, a fault diagnosis model of Chiller is designed by combining least squares support vector machine (LSSVM) optimized by hybrid improved northern goshawk optimization algorithm (HINGO) and improved IAdaBoost ensemble learning algorithm. …”
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Deep learning-based artificial intelligence for assisting diagnosis, assessment and treatment in soft tissue sarcomas by Ruiling Xu, Jinxin Tang, Chenbei Li, Hua Wang, Lan Li, Yu He, Chao Tu, Zhihong Li

“…It is worth noting that high-quality data with accurate annotations, as well as optimized algorithmic performance are pivotal in the clinical application of DL in STSs.…”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Furthermore, the predictive models typically lack interpretability. To address these issues, this study proposes a hybrid prediction model for the residual strength of defective pipelines based on Bayesian optimization (BO) and eXtreme Gradient Boosting (XGBoost). …”
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An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images by Kiran Jabeen, Muhammad Attique Khan, Ameer Hamza, Hussain Mobarak Albarakati, Shrooq Alsenan, Usman Tariq, Isaac Ofori

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Research on Efficient Coordination Control System of Virtual Coupling for Urban Rail Train by SHI Ke, WANG Yue, ZHANG Zhengfang, ZHOU Zhiwen, BAI Jinglei, LUO Qinyang

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Optimized Two-Stage Anomaly Detection and Recovery in Smart Grid Data Using Enhanced DeBERTa-v3 Verification System by Xiao Liao, Wei Cui, Min Zhang, Aiwu Zhang, Pan Hu

“…The first stage employs an optimized increment-based detection algorithm achieving 95.0% for recall and 54.8% for precision through multidimensional analysis. …”
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THEORETICAL AND METHODOLOGICAL PRINCIPLES OF APPLICATION OF AGENT-ORIENTED APPROACH TO MODELING PROCESSES OF LOCAL HROMADAS by Yevgen Kotukh, Maryna Riabokin

“…The article also outlines a multi-step algorithm for modeling decision-making and coordination processes within the decentralized budget structure. …”
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Advance path loss model for LoRaWAN coverage estimation by Van Lic Tran, Tran Dang Khoa Phan, Tran Thi Minh Hanh, Vu Van Thanh, Thai Van Tien, Thai Vu Hien, Tran Anh Kiet

“…This paper demonstrates that, using multiple data points around each gateway allows for the creation of accurate coverage heat maps by using a proposed LoRaWAN coverage estimation algorithm. This method effectively identifies areas with varying signal strength across Da Nang City, highlighting where additional gateways are needed to improve network reliability. …”
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An Empirical Taxonomy of Video Summarization Model From a Statistical Perspective by Sai Babu Veesam, Aravapalli Rama Satish

“…Some of the notable techniques include the SVS_MCO method using DBSCAN clustering optimized by the Artificial Algae Algorithm and the KDAN framework, which leverages knowledge distillation for supervised summarization. …”
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A bearing fault diagnosis method based on hybrid artificial intelligence models. by Lijie Sun, Xin Tao, Yanping Lu

“…The process employs Maximum Second-order Cyclostationary Blind Deconvolution (CYCBD) to filter out noise from the vibration signals emitted by bearings; secondly, considering the issue with the conventional Harris Hawks Optimization (HHO) algorithm which tends to prematurely converge to local optima, the differential evolution mutation operator is introduced and the escape energy factor is improved from linear to nonlinear in IHHO; then, a double-layer network model based on DBN-ELM is proposed, to avoid the number of hidden layer nodes of DBN from human experience interference, and IHHO is used to optimize DBN structure, which is denoted as IHHO-DBN-ELM method; with the optimal structure is obtained by using a combined IHHO optimized DBN and ELM; in conclusion, the proposed IHHO-DBN-ELM approach is applied to the bearing fault detection using the Western Reserve University's bearing fault dataset. …”
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Development of a manipulator kinematic model using Abb Robot Studio by Артем Бронніков, Марія Бендеберя

“…Conclusions: a model and software module were developed for the adaptive execution of the production process as part of the virtual model of the ABB IRB 1200 robot, which allows to increase the efficiency of the roduction process, reduce downtime, and improve product quality. …”
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Joint beamforming design for distributed IRS assisted millimeter wave MU-MISO system by Zhongjie LI, Jiyuan XIONG, Wei GAO, Jinying WEI

“…A joint beamforming design scheme for distributed intelligent reflecting surface (IRS) assisted multi-user communication was proposed to solve the reliable communication problem in the downlink of millimeter-wave multi user-multiple input single output (MU-MISO) system in non line of sight scenarios.Considering the power and constant-mode constraints, the active beamforming of the base station and passive beamforming of multiple IRS were modeled as a joint non-convex optimization problem with the objective of user weighting and sum rate maximization.A closed-form fractional programming technique was used to decouple this joint optimization problem into an easily solvable equivalent problem.A non-convex block coordinate descent algorithm was used to alternately optimize the active beamforming and passive beamforming matrices according to the prox-linear rule and the distributed successive convex approximation rule.The convergence proof and complexity analysis of the proposed algorithm were also given.The simulation results demonstrate that the algorithm can converge fast, and can effectively improve the system transmission rate with reduced complexity compared with the two baseline algorithms.…”
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Computational Linguistics Applications in AI-Based Investment and Cost Structuring Models by Miralieva Dilafruz, Ramatov Jumaniyoz, Azimova Lola, Khusamiddinova Malika, Alimbaeva Shahlo, Omonova Laylo

“…AI-enabled linguistics modeling promotes scalable optimization and context-aware applications of financial analytics, and realizes cost transparency improvements in automated investment systems. …”
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Construction and analysis of yarn tension model in the process of electromagnetic weft insertion by Zhang Chengjun, Wang Yi, Liu Pengwei, Li Chengyuan, Xu Chuqiao, Zuo Xiaoyan, Zhou Xiangyang

“…When constructing the yarn tension model, the Levenberg–Marquardt algorithm in ORIGIN software is used for data fitting. …”
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Collaborative multiview time series modeling for vehicle maintenance demand prediction by Fanghua Chen, Deguang Shang, Gang Zhou, Ke Ye, Fujie Ren, Guofang Wu

“…To enhance the interaction between distinct time points and temporal dependencies, we developed a dependency-aware learning algorithm that effectively integrates and weighs the information and dependencies at each time step, thereby improving the model’s ability to capture the complex relationships among maintenance projects over time. …”
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Adaptive sliding mode control based on maximum power point tracking for boost converter of photovoltaic system under reference voltage optimizer by Borhen Torchani, Ahmad Taher Azar, Ahmad Taher Azar, Ahmad Taher Azar, Anis Sellami, Saim Ahmed, Saim Ahmed, Ibrahim A. Hameed, Ibraheem Kasim Ibraheem, Moamin Ibrahim Jameel Al-Obaidi

“…A PI controller calculates the reference current based on this power. The APISMC control modeling utilizes all its reference variables to synthesize the sliding surface and duty cycle for optimal boost converter control. …”
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Efficient distributed model sharing strategy for data privacy protection in Internet of vehicles by Zijia MO, Zhipeng GAO, Yang YANG, Yijing LIN, Shan SUN, Chen ZHAO

“…Aiming at the efficiency problem of privacy data sharing in the Internet of vehicles (IoV), an efficient distributed model sharing strategy based on blockchain was proposed.In response to the data sharing requirements among multiple entities and roles in the IoV, a master-slave chain architecture was built between vehicles, roadside units, and base stations to achieve secure sharing of distributed models.An asynchronous federated learning algorithm based on motivate mechanism was proposed to encourage vehicles and roadside units to participate in the optimization process.An improved DPoS consensus algorithm with hybrid PBFT was constructed to reduce communication costs and improve consensus efficiency.Experimental analysis shows that the proposed mechanism can improve the efficiency of data sharing and has certain scalability.…”
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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. …”
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Enhancing surface detection: A comprehensive analysis of various YOLO models by G. Deepti Raj, B. Prabadevi

“…This study presents an improved YOLOv5 detection model, exploiting the efficient channel attention (ECA) and coordinated attention (CoordAtt) mechanisms. …”
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