A Method of Modal Parameter Identification for Wind Turbine Blade Based on Binocular Dynamic Photogrammetry by Wenyun Wang, Xuejun Li, Anhua Chen

“…The data-driven stochastic subspace identification (SSI-Data) method based on the Kalman filter prediction sequence is explored to extract modal parameters from vibration response under unknown excitation. …”
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A general two-group constants estimator for 17x17 PWR assembly configurations using artificial neural networks by Gökhan Pediz, M. Alim Kırışık

“…The prediction measures show that ANNs can consistently estimate two-group constants for the test data assemblies. …”
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UAV Path Planning for Precision Multi-Target Localization by Mahsa Mohammadi, Michael W. Shafer

“…At each designated waypoint, the UAV obtains bearing measurements to tagged animals, considering the associated uncertainty. The algorithm then intelligently recommends subsequent locations that minimize predicted localization uncertainty while accounting for constraints related to mission time, keeping the UAV within signal range, and maintaining a suitable distance from targets to avoid disturbing the wildlife. …”
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Application of DE-RF and Fuzzy Model in Camber Control of Hot Rolled Strip by WEI Zhipeng, CUI Guimei, PI Lixiang, LI Tianhao

“… In order to solve the problem of slab bending affecting strip quality in 2250mm hot strip rolling process, a method based on data fusion and expert experience is proposed to apply to slab bending control system.Firstly, the differential evolution algorithm is established to optimize the stochastic forest regression model to solve the problem of insufficient accuracy of slab detection lag prediction.The model can effectively predict the bending value of the slab at the exit of the third pass roughing mill, and the estimated error is 96.3% of the slab within the allowable range.Then a fuzzy model is established according to the expert experience and data to solve the manual operation uncertainty problem.The model gets the roll slit tilt value twice respectively, and the experimental results show that the calculated value of the fuzzy model has a small error compared to the actual value and it can provide the roll gap tilt value reliably.Finally, the two roll gap tilt values are added together as the second roll gap tilt value. …”
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A cost-effective adaptive repair strategy to mitigate DDoS-capable IoT botnets. by Jiamin Hu, Xiaofan Yang

“…On this basis, we model the ARS problem as a data-driven optimal control problem, aiming to realize both learning and prediction of propagation parameters based on network traffic data observed at multiple discrete time slots and control of IoT botware propagation to a desired infection level. …”
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Creating Worlds that Create Audiences: Theorising Personal Data Markets in the Age of Communicative Capitalism by Vassilis Charitsis, Detlev Zwick, Alan Bradshaw

“…Echoing recent theorisations of data (as) derivatives, Zuboff’s key claim about surveillance capitalism is that data representations open up opportunities for the enhanced market control of life through the algorithmic monitoring, prediction and modification of human behaviour. …”
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Cultural intelligence and inclusive leadership in a diverse IT sector: a framework for effective collaboration by Камрун Нахар, Омар Фарук, Захир Райхан

“…Based on a mixed-methods study with 600 participants from worldwide IT businesses, the paper proposes CQL-IncluNet, a prediction algorithm to model and evaluate collaboration.  …”
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Secure IoV communications for smart fleet systems empowered with ASCON by Bhuvaneshwari A J, P. Kaythry

“…Integration of a deep learning model that is suited for real-time anomaly detection and breach prediction. The novelty of this study is the hybrid framework that uses lightweight cryptographic methods coupled with deep learning-based threat protection. …”
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Detection of change in vegetation cover using multi-spectral and multi-temporal information for District Sargodha, Pakistan / Detecção de alteração na cobertura vegetal com uso de... by Farooq Ahmad

“…The results can be utilized as a temporal landuse change model for Punjab province of Pakistan to quantify the extent and nature of change and assist in future prediction studies. This will support environmental planning to develop sustainable landuse practices.…”
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Improving classifier decision boundaries and interpretability using nearest neighbors by Johannes Schneider, Arianna Casanova

“…To address this issue, we propose a simple algorithm that performs a weighted average of a sample’s prediction and those of its nearest neighbors (computed in latent space), leading to minor but favorable outcomes across a variety of important performance measures for neural networks. …”
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SC-PREC4SA: A serially complete daily precipitation dataset for South America by Adrian Huerta, Roberto Serrano-Notivoli, Stefan Brönnimann

“…Gap-filling achieved a mean accuracy of 70 % (60 %) in the prediction on wet/dry days (wet-day magnitude). These metrics highlight the reliability of the gap-filling process, particularly in mixed climates, where station networks are sparse. …”
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Online determination of state of charge in lithium-ion batteries: influence of the state of health by Carlos Armenta-Deu

“…The proposed model applies to all lithium-ion batteries and validates for a wide range of battery state-of-health, up to 50%, and with accurate prediction, higher than 90%.…”
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Deep knowledge tracing and cognitive load estimation for personalized learning path generation using neural network architecture by Chunyan Tong, Changhong Ren

“…Experimental evaluations across multiple educational domains demonstrate that our approach outperforms existing methods in prediction accuracy (87.5%), path quality (4.4/5), and learning efficiency (24.6% improvement). …”
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Research on Online Defect Detection Method of Solar Cell Component Based on Lightweight Convolutional Neural Network by Huaiguang Liu, Wancheng Ding, Qianwen Huang, Li Fang

“…Secondly, in order to detect the defects with small size or weak edges in the silicon wafer, an improved lightweight CNN model with deep backbone feature extraction network structure was proposed, as the enhancing feature fusion layer and the three-scale feature prediction layer; the model provided more feature detail. …”
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Optimization and Benefit Assessment of LID Layout Based on the MCDA Approach at a Campus Scale by Zexin Lei, Lijun Li, Yanrou Wei, Wenzheng Zhang, Junjie Luo, Xuqiang Zhao

“…SWMM simulations revealed that permeable paving achieved the highest runoff reduction (up to 19.4% at 65% coverage) and strong cost-effectiveness (0.013 USD per % reduction). …”
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INFO-RF-based fault diagnosis and analysis method for busbars by Chen Xue, Jian Zhu, Haiou Cao, Yan Gu, Siyu Chen

“…The RF model is then used to predict fault types and fault resistance, with the INFO algorithm iteratively optimizing the hyperparameters of the RF model to further improve prediction accuracy. …”
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Application of Artificial Intelligence Technology in Martial Arts Education Governance by Weiwu Ye, Shihong Li, Shuaibing Liu, Yuan Zhou

“…At the same time, this paper uses the pose estimation algorithm of coordinate regression to predict the key points of the human body from the global perspective of the human body and then locates the key points of the human body from the features. …”
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Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…After the chemometrics related to hyperspectral imaging had been examined, the least square-support vector regression models based on the feature bands, which were selected by the shuffled frog leaping algorithm, showed the best performance, and the determination coefficients of prediction (R2P) for cherry sugar content and acidity reached 0.976 and 0.906, respectively. …”
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Machine-Learning-Based Optimal Feed Rate Determination in Machining: Integrating GA-Calibrated Cutting Force Modeling and Vibration Analysis by Yu-Peng Yeh, Han-Hao Tsai, Jen-Yuan Chang

“…Surface quality evaluations showed that the model-predicted feed rates consistently resulted in better surface finish and reduced chatter effects compared to conventional settings. …”
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“Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

“…This study employs the K-means clustering algorithm to partition warm-season precipitation in Zhejiang Province into distinct regions. …”
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