Research on Multi-Channel Spectral Prediction Model for Printed Matter Based on HMSSA-BP Neural Network by Dandan Fan, Hongwu Zhan, Fang Xu, Yifei Zou, Yankang Zhang

“…To overcome it, this paper proposes a multi-channel spectral prediction model for printed matter and the adaptive evaluation method based on multi-index fusion. …”
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An extension of the Spiegelhalter-Knill-Jones method for continuous covariates in clinical decision making by Bart K. M. Jacobs, Tafadzwa Maseko, Lutgarde Lynen, Aquiles Rodrigo Henriquez-Trujillo, Jozefien Buyze

“…We used area under the curve (AUC) and risk classification improvement (RCI) as metrics to evaluate the performance of resulting predictions scores and risk classifications. …”
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Novel Method of Immunoepitope Recognition, Long-Term Immunity Markers, Immunosuppressive Domens and Vaccines against COVID-19 by E. P. Kharchenko

“…Relevance of searching for computer methods with high efficiency of immunoepitopes recognition and predicting the longevity of the immunity they induce is determined primarily by the need to quickly create vaccines against newly emerging infections, especially during pandemic periods. …”
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Chemometric and meta-heuristic algorithms to find optimal wavelengths and predict ‘Red Delicious’ apples traits using Vis-NIR by Mahsa S. Razavi, Vali Rasouli Sharabiani, Mohammad Tahmasebi, Silvia Grassi, Mariusz Szymanek

“…The potential of Vis-NIR spectroscopy (540–960 nm) in quality evaluation of Red Delicious apples was investigated. …”
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EVALUATION OF THE CHARACTERISTICS AND CLINICAL RESULTS OF THE PATIENTS HOSPITALIZED WITH COVID-19 PNEUMONIA IN THE PROVINCE OF MUS: A STATE HOSPITAL EXPERIENCE by Aysun Benli, Emir Resuloğlu, İlke Karadağlı Üçüncü, Ayşe Nur Ceylan, Mustafa Taner Yeler, Gürkan Danışan, Cihan Büyüksütçü, Mehmet Balcı, Şinasi Korkmaz, Bilal Akdemir, Adil Akın Yıldıran, Cemal Yaşar

“…Multivariate logistic regression analysis was performed to evaluate the factors predicting the severity of COVID-19. …”
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Sound Quality Prediction Method of Dual-Phase Hy-Vo Chain Transmission System Based on MFCC-CNN and Fuzzy Generation by Jiabao LI, Lichi AN, Yabing CHENG, Haoxiang WANG

“…Noise acquisition tests are conducted under various working conditions, followed by subjective evaluations using the equal interval direct one-dimensional method. …”
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A Rapid Evaluation Method of Permafrost Bearing Capacity in the Tibetan Plateau Region Based on the Correlation Between CPT-CBR by Haowu Wang, Bo Tian, Lei Quan, Panpan Zhang, Lihui Li, Yitong Hou, Sen Hu

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Hyperspectral Method Integrated with Machine Learning to Predict the Acidity and Soluble Solid Content Values of Kiwi Fruit During the Storage Period by Mansourialam Amir, Rasekh Mansour, Ardabili Sina, Dadkhah Majid, Mosavi Amir

“…The evaluation of the predictive machine learning model revealed an accuracy of 95% in predicting acidity and soluble solid content (SSC) changes in kiwi fruit during storage. …”
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Classifying AI-Powered prediction models for disability progression using the Tamir-Based complex fuzzy Aczel–Alsina WASPAS method by Jabbar Ahmmad, Meraj Ali Khan, Ibrahim Aldayel, Tahir Mahmood

“…This hybrid model incorporates complex fuzzy logic to handle multidimensional uncertainty and utilizes the Aczel-Alsina function for flexible aggregation. We apply this method to evaluate and classify AI-powered predictive models used for monitoring disability progression. …”
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Corrosion resistance prediction of high-entropy alloys: framework and knowledge graph-driven method integrating composition, processing, and crystal structure by Guangxuan Song, Dongmei Fu, Yongjie Lin, Lingwei Ma, Dawei Zhang

“…Abstract The prediction of corrosion resistance in High-entropy alloys (HEAs) faces challenges due to previous machine learning methods not fully capturing the interdependencies between composition, processing, and crystal structure. …”
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Stock market trend prediction using deep neural network via chart analysis: a practical method or a myth? by Erfan Radfar

“…Abstract In this study, we investigate the feasibility of using deep learning for stock market prediction and technical analysis. We explore the dynamics of the stock market and prominent classical methods and deep learning-based approaches that are used to forecast prices and market trends. …”
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Improving Orbit Prediction of the Two-Line Element with Orbit Determination Using a Hybrid Algorithm of the Simplex Method and Genetic Algorithm by Jinghong Liu, Chenyun Wu, Wanting Long, Bo Yuan, Zhengyuan Zhang, Jizhang Sang

“…Compared with the results of the least-squares method and simplex method based on Monte Carlo simulation, the new algorithm demonstrated its superiorities in orbital prediction. …”
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A semi-analytical model for predicting the mechanical responses around a non-circular wellbore by using complex variable method by Wenbao Zhai, Haoze Zhang, Zixuan Yang, Zhaowei Chen, Bisheng Wu, Jiaxing Zhou, Shaoyi Cheng, Peng Tan

“…The proposed method will be useful to study the effect of the wellbore shape on the stress distribution around the wellbore and predict the evolution of wellbore breakout.…”
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A Hybrid Method Combining Variational Mode Decomposition and Deep Neural Networks for Predicting PM2.5 Concentration in China by Senlin Li, Bo Tang, Xiaowu Deng

“…To address this issue, this study introduces a hybrid parallel method (VDPS) that combines variational mode decomposition (VMD) with single deep neural networks for PM2.5 concentration prediction. …”
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Prediction of canopy mean traits in herbaceous plants by the UAV multispectral data: The quest for a better leaf-to-canopy upscaling method by Yuanqi Shan, Yunlong Yao, Lei Wang, Zhihui Wang, Huaihu Yi, Yi Fu, Weineng Li, Xuguang Zhang, Wenji Wang, Zhongwei Jing

“…The accuracy was evaluated by exploring the predictive ability for nine canopy mean traits by using high spatial resolution UAV multispectral data. …”
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Using artificial neural networks to predict indoor particulate matter and TVOC concentration in an office building: Model selection and method development by Saren Gaowa, Zhen Zhang, Jianchun Nie, Linxiao Li, Han A-ru, Zhili Yu

“…The MLNN model and the random forest (RF) classification method were further used to predict indoor TVOC concentrations. …”
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A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

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Virtual resource allocation method with the consideration of performance interference among virtual machines by Lei YANG, He-xu XING, Yu DAI, Sai XU, Hao WANG, Bin ZHANG

“…A method for allocating the virtual resource with the consideration of the performance interference among vir-tual machines was proposed.The model for evaluating the performance interference among virtual machines was formed and the method for predicting the performance interference was presented based on the workload pattern of the virtual machine.The predicted result of the performance interference among virtual machines was put into the evaluation of the resource allocation plan to be used as the basis for resource allocation.By doing this,the effectiveness of the resource al-location plan could be insured.The experiments show that the proposed virtual resource allocation method can insure the execution performance of the application deployed on the virtual machines.…”
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Evaluation of the predictors of tooth loss using artificial intelligence-based machine learning approach: A retrospective study by Amit Rajabhau Pawar, Sankari Malaiappan, Pradeep Kumar Yadalam, P R Ganesh

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Optimizing pore pressure prediction in earth dams through the integration of panel data and intelligent models by Behrang Beiranvand, Taher Rajaee, Mehdi Komasi

“…The research focuses on developing a robust pore pressure prediction system for Eyvashan Dam by integrating multiple artificial intelligence techniques—including Feed-Forward Neural Networks (FFNN), Support Vector Regression (SVR), Group Method of Data Handling (GMDH), and Ensemble Artificial Neural Networks (EANN)—with Fuzzy C-Means Clustering (FCM) methodology. …”
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