Assembly Accuracy Analysis Method Based on Multi‐Stage Linearized Contact by Wenbin Tang, Yadong Li, Tong Yan, Min Zhang

“…By employing homogeneous coordinate transformation (HCT), the prediction of the part's pose during the assembly process with the rigid body assumption is achieved. …”
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Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading by Shangkun Deng, Akito Sakurai

“…The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.…”
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Transformer-based short-term traffic forecasting model considering traffic spatiotemporal correlation by Ande Chang, Yuting Ji, Yiming Bie

“…By incorporating road network topology, a spatial mask filters out noise and irrelevant interactions, improving prediction accuracy. Finally, traffic speed is predicted using another multilayer perceptron. …”
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An Improved Sequential Recommendation Algorithm based on Short-Sequence Enhancement and Temporal Self-Attention Mechanism by Jianjun Ni, Guangyi Tang, Tong Shen, Yu Cai, Weidong Cao

“…Sequential recommendation algorithm can predict the next action of a user by modeling the user’s interaction sequence with an item. …”
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Unleashing the Power of Artificial Intelligence-Driven Drug Discovery in Streptomyces by Wei-Shan Ang, Jodi Woan-Fei Law, Yatinesh Kumari, Vengadesh Letchumanan, Loh Teng-Hern Tan

“…Overall, the ML model is trained using input data and generates outcomes based on prediction output. This review discusses the continued potential of Streptomyces sp. as a source of novel NPs, along with the application of ML throughout the NP drug discovery pipeline involving genome mining, biological activities prediction, and optimization compound production in Streptomyces microbial systems. …”
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Perception Analysis and Early Warning of Home-Based Care Health Information Based on the Internet of Things by Yi Mao, Lei Zhang, Xin Wu

“…Finally, this paper analyses the prediction algorithm theory of the disease prediction module in the health monitoring software of the home care system. …”
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Numerical Research on Effects of Splitter Blades to the Influence of Pump as Turbine by Yang Sun-Sheng, Kong Fan-Yu, Fu Jian-Hui, Xue Ling

“…CFD can be used in the performance prediction and optimization of PAT.…”
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Experimental Study on Viscoplastic Property of Unsaturated Reticulate Red Clay Used as an Engineered Barrier by Chuang Zhang, Jian-Zhong Li, Yong He

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Comparative Analysis of Deep Learning Techniques for Load Forecasting in Power Systems Using Single-Layer and Hybrid Models by Jiyeon Jang, Beopsoo Kim, Insu Kim

“…In addition, this study included weather factors that may affect the load to improve the prediction performance. The prediction process is performed on the Python platform, and the model that showed the highest accuracy was LSTM-CNN, a hybrid combination of LSTM and CNN models. …”
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Research on Urban Traffic Industrial Management under Big Data: Taking Traffic Congestion as an Example by Yi Zhang, Shuwang Yang, Hang Zhang

“…This paper establishes a prediction model of traffic flow, where three cycle dependent components are used to model three characteristics of traffic data, respectively. …”
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Modified STARIMA model for space-time data by Laura Šaltytė

“…Comparison between proposed model which can be considered as modified STARIMA model and general STARIMA model developed by Pfeifer and Deutch is presented. Mean square prediction error (MSPE) for proposed procedure of prediction is presented. …”
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A Comparative Study of VMD-Based Hybrid Forecasting Model for Nonstationary Daily Streamflow Time Series by Hui Hu, Jianfeng Zhang, Tao Li

“…This study proposes a new data-driven model that combined the variational mode decomposition (VMD) and the prediction models for daily streamflow forecasting. …”
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The Influence of Vertical Resolution on Internal Tide Energetics and Subsequent Effects on Underwater Acoustic Propagation by L. Hiron, M. C. Schönau, K. J. Raja, E. P. Chassignet, M. C. Buijsman, B. K. Arbic, A. Bozec, E. F. Coelho, M. S. Solano

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Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning by Nanding Li, Naoshi Kondo, Yuichi Ogawa, Keiichiro Shiraga, Mizuki Shibasaki, Daniele Pinna, Moriyuki Fukushima, Shinichi Nagaoka, Tateshi Fujiura, Xuehong De, Tetsuhito Suzuki

“…But previous endeavours cannot realise real-time monitoring and their prediction accuracy still need improvement in a practical sense. …”
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A Vegetable-Price Forecasting Method Based on Mixture of Experts by Chenyun Zhao, Xiaodong Wang, Anping Zhao, Yunpeng Cui, Ting Wang, Juan Liu, Ying Hou, Mo Wang, Li Chen, Huan Li, Jinming Wu, Tan Sun

“…Different from the traditional single model prediction method, VPF-MoE can dynamically adapt to the characteristics of different vegetable types, dynamically select the best prediction method, and significantly improve the accuracy and robustness of the prediction. …”
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Feasibility Study on the Use of a Portable NIR Spectrometer and Multivariate Data Analysis to Discriminate and Quantify Adulteration in Fertilizer by Ernest Teye, Charles L. Y. Amuah, Kofi Atiah, Ransford Opoku Darko, Kwadwo Kusi Amoah, Emmanuel Afutu, Rebecca Owusu

“…The models were evaluated according to identification rate (Rt), coefficient of correlation in prediction (Rpre2), and root mean square error of prediction (RMSEP). …”
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Implementation of the Human-Like Lane Changing Driver Model Based on Bi-LSTM by Junyu Cai, Haobin Jiang, Junyan Wang

“…This paper uses four neural network models to compare the prediction on the test set, then uses different input types to compare the prediction accuracy of the model, and finally verifies the generalization ability of the model on the verification set. …”
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Integrated Multiscale Latent Variable Regression and Application to Distillation Columns by Muddu Madakyaru, Mohamed N. Nounou, Hazem N. Nounou

“…Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. …”
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Grain Consumption Forecasting: One Modified MLR Model Combined with Time Series Forecasting Theory by Chunhua Zhu, Jiaojiao Wang, Jiake Tian

“…In the classical multivariate prediction model, most research studies focused on the selection of relevant behaviour factors and the stability of historical data for improving the predicting accuracy of the main behaviour factor, and the historical data of the main behaviour factor have never been considered as one relevant behaviour factor, which in fact can be the first key impact factor; besides, the historical data can directly predict the main behaviour in the time series forecasting model, such as the ARIMA model. …”
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Selective Screening Strategies for Gestational Diabetes: A Prospective Cohort Observational Study by Sumaiya Adam, Paul Rheeder

“…We aimed to develop a prediction model for the diagnosis of gestational diabetes and to evaluate the performance of published prediction tools on our population. …”
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