RSS Tracking Control for AVs Under Bayesian-Network-Based Intelligent Learning Scheme by Kun Zhang, Kezhen Han, Nanbin Zhao

“…Additionally, a critic learning optimal control algorithm is developed to determine the control law. …”
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An interpretable fault diagnosis method for aeroengine bearings based on belief rule based with a dynamic power set by Jinyuan Li, Wei He, Hailong Zhu

“…Moreover, the models can suffer from local ignorance in the prediction process. These problems can lead to a decrease in the prediction accuracy of the model. …”
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Dynamic Water Scheduling in the Northwest River Delta Basin Based on Minimum Discharge Flow Control in Cross-section by WU Di, FANG Chunyan, SHANG Yunfei

“…The whale optimization algorithm was used to find the optimal water allocation plan. …”
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Epistolution: a new principle necessary to a learning-first theory of life by Charlie Munford

“…But what if these views confuse cause with effect? Perhaps a learning algorithm is required for any phenotype at all to arise. …”
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Optimization of Communication Signal Adversarial Examples by Selectively Preserving Low-Frequency Components of Perturbations by Yi Zhang, Lulu Wang, Xiaolei Wang, Dianxi Shi, Jiajun Bai

“…By utilizing the binary search algorithm, which considers the inconsistency in the model’s predictions as a constraint, LFCP can be effectively identified, and the aim of minimizing perturbed distortion while maintaining ASR can be achieved. …”
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Twin Support Vector Regression Model Based on Heteroscedastic Gaussian Noise and Its Application by Shiguang Zhang, Ge Feng, Feng Yuan, Shuangle Guo

“…The experimental results show that TSVR-HGN has better prediction accuracy.…”
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Lithium-ion battery state-of-charge estimation based on a dual extended Kalman filter and BPNN correction by Likun Xing, Liuyi Ling, Xianyuan Wu

“…A novel model-based method, using a Dual Extended Kalman Filtering algorithm (DEKF) and Back Propagation Neural Network (BPNN), is proposed to estimate and correct lithium-ion batteries. …”
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Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review by Mohammad Hossein Salemi, Elham Foroozandeh, Molouk Khademi Ashkzari

“…Personalized medicine, powered by AI, predicts individual medication responses, minimizing side effects and optimizing outcomes. …”
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A non-linear procedure for the numerical analysis of crack development in beams failing in shear by P. Bernardi, R. Cerioni, E. Michelini, A. Sirico

“…In more details, a constitutive model originally proposed by Ottosen and based on non-linear elasticity has been here incorporated into 2D-PARC in order to improve the numerical efficiency of the adopted algorithm, providing at the same time an accurate prediction of the structural response. …”
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Analytical approach for modelling of thread crimp in jacquard woven two-dimensional fabrics by Brigita Kolcavová Sirková, Iva Mertová

“…The theoretical predicted values of thread crimp in jacquard fabrics were compared with experimentally obtained values. …”
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Opportunities and challenges of AI-systems in political decision-making contexts by Max Tretter

“…Furthermore, some of them have the power to carry out in-depth simulations with varying parameters, predicting the consequences of various political decisions, and thereby providing new certainties. …”
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The System Research and Implementation for Autorecognition of the Ship Draft via the UAV by Wei Zhan, Shengbing Hong, Yong Sun, Chenguang Zhu

“…In order to solve the above problems, this paper introduces the computer image processing technology based on deep learning, and the specific process is divided into three steps: first, the video sampling is carried out by the UAV to obtain a large number of pictures of the ship draft reading face, and the images are preprocessed; then, the deep learning target detection algorithm of improved YOLOv3 is used to process the images to predict the position of the waterline and identify the draft characters; finally, the prediction results are analyzed and processed to obtain the final reading results. …”
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Forecasting the Directions of the State Policy of the Region on the Basis of Cluster Analysis of Indicators of Socio-Economic Development of Its Municipalities by S. N. Borodin

“…The advantage of the proposed approach is that it identifies and predicts the problems of socio-economic development of the region, which may be hidden in the medium-term forecast of the socio-economic region. …”
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Modelling flame-to-fuel heat transfer by deep learning and fire images by Caiyi Xiong, Zilong Wang, Xinyan Huang

“…Results show that the proposed AI algorithm trained by flame images can predict both the convective and radiative heat flux distributions on the condensed fuel surface with a relative error below 20%, based on the input of real-time flame morphology that can be captured by a larger grid size. …”
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Detection of Water Content of Watermelon Seeds Based on Hyperspectral Reflection Combined with Transmission Imaging by Siyi Ouyang, Siwei Lv, Bin Li

“…The intermediate data fusion of the feature spectral data of reflectance and transmittance selected by the CARS algorithm improves the prediction effect of the model more obviously, in which the model with the best prediction accuracy is Raw-CRAS-LSSVR, whose <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msubsup><mi>R</mi><mi>P</mi><mn>2</mn></msubsup></semantics></math></inline-formula> and RMSEP are 0.9149 and 0.0144, respectively, which improves the prediction effect of the model built by a single full-spectrum datum by 5.72%. …”
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Clinical decision support system based on artificial intelligence for adjusting insulin pump parameters in children with type 1 diabetes mellitus by D. Yu. Sorokin, E. S. Trufanova, O. Yu. Rebrova, O. B. Bezlepkina, D. N. Laptev

“…We constructed recurrent neural network (RNN) to predict glucose concentration for 30-120 minutes, an algorithm for optimizing IP settings using prediction results. …”
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Research on Road Crack Detection Based on RGB-LPC-GPR Data Fusion by Z. Wang, D. Qiu, R. Wu, R. Wu, Y. Shi, W. Niu

“…By leveraging Deep Mapping 2.0 and the RAFT algorithm, the alignment accuracy between RGB and LiDAR data was significantly improved, reducing registration error to 2.3 mm. …”
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Impact of foam-mat drying conditions of “Gấc” aril on drying rate and bioactive compounds: Optimization by novel statistical approaches by Nguyen Minh Thuy, Vo Quoc Tien, Tran Ngoc Giau, Hong Van Hao, Vo Quang Minh, Ngo Van Tai

“…ANN model of 3–10–3 showed more accuracy and faster prediction capacity than RSM model did. ANN-GA model predicted the optimal conditions to be 13.31 % EA, 0.26 % xanthan gum and drying temperature of 73.1 °C, with the drying rate of 1.89 g-water/g-dry matter/min, β-carotene content of 395.88 μg/g, TPC of 1.68 mgGAE/g. …”
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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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Application of the SARIMA-LSTM model to evaluate the effectiveness of interventions for Visceral Leishmaniasis by Mengchen Han, Chongqi Hao, Zhiyang Zhao, Peijun Zhang, Bin Wu, Lixia Qiu

“…A paired samples t-test revealed a statistically significant difference between predicted and actual case counts (t = -4.058, p < 0.001), indicating that the actual number of cases was lower than predicted. …”
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