Functional Aggregate Model of Logical Controlling System of Electric Drives in Technological Complex by A. A. Goncharov

“…This model is considered as a basic initial stage for constructing models of the next hierarchic levels and modeling algorithms. …”
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Chemical Composition-Driven Machine Learning Models for Predicting Ionic Conductivity in Lithium-Containing Oxides by Yudai IWAMIZU, Kota SUZUKI, Michiyo KAMIYA, Naoki MATSUI, Kuniharu NOMOTO, Satoshi HORI, Masaaki HIRAYAMA, Ryoji KANNO

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New non-primitive codes formed from primitive BCH and Hamming codes and their norm evaluation by V. K. Konopelko, V. A. Lipnitski

“…Integrated studies completion of BCH codes of different lengths is devoted. …”
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Problems of optimizing the energy consumption of households in the tasks of improving the energy efficiency of the housing sector by G. G. Grebenuk, S. M. Nikishov, A. A. Krygin, L. A. Sereda

“…A number of  algorithms for determining some input indicators that are easy to use in households have also been proposed. …”
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Prediction of Thermal and Optical Properties of Oxyfluoride Glasses Based on Interpretable Machine Learning by Yuhao Xie, Xiangfu Wang

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Data asset valuation model based on generative artificial intelligence. by Yungang Tang, Yaoqian Liu, Daxin Liu

“…The model integrates data feature extraction, value generation algorithms, and market adaptability evaluations to address the shortcomings of traditional valuation methods in dynamic market environments. …”
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Online Purchase Behavior Prediction Model Based on Recurrent Neural Network and Naive Bayes by Chaohui Zhang, Jiyuan Liu, Shichen Zhang

“…The contributions of this paper are as follows: (1) By constructing an online purchasing behavior model RNN-NB, which integrates the N vs 1 structure Recurrent Neural Network and naive Bayesian model, the validity limitations of some single-architecture recommendation algorithms are solved. (2) Based on the existing naive Bayesian model, the prediction accuracy of online purchasing behavior is further improved. (3) The analysis based on the features of the time series provides new ideas for the research of later scholars and new guidance for the marketing of platform merchants.…”
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A Prototype Unit of a Distributed Sensor System for Ecological Monitoring by E. A. Sevryukova, E. A. Volkova, V. A. Doroshenko, A. V. Solodkov

“…A prototype of the system was constructed, and algorithms for receiving and transmitting signals were simulated.Aim. …”
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An efficient cost calculation method for disparity estimation of stereo matching considering shadow occlusion by Hongjun Sha, Wei Yuan, Xunping Wang, Xiuliu Yuan, Shunichi Koshimura

“…To verify the optimization ability and transferability of MCSP, the MCSP cost is integrated into three classical disparity estimation algorithms respectively. …”
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Deep learning in next-generation vaccine development for infectious diseases by Manojit Bhattacharya, Yi-Hao Lo, Srijan Chatterjee, Arpita Das, Zhi-Hong Wen, Chiranjib Chakraborty

“…Deep learning (DL), a subset of AI, is used in the landscape of vaccine development in terms of its algorithms, tools, and technologies. This review article discussed the developmental history of the modern era of vaccine development strategies using both immunoinformatics with DL models, identification strategies of T cell epitopes and B cell epitopes through immunoinformatics and DL models, vaccine constructs development strategies using linker and adjuvant, and characterization strategies of vaccine construct using bioinformatics and immunoinformatics. …”
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A Bernstein polynomial approach of the robust regression by Sihem Semmar, Omar Fetitah, Mohammed Kadi Attouch, Salah Khardani, Ibrahim M. Almanjahie

“…Some simulations are performed to illustrate that our robust estimator has the lowest average integrated squared error ($ \overline{AISE} $). In the end, real data is utilized to assess the performance of conventional and newly presented robust regression algorithms regarding their ability to handle sensitivity to outliers. …”
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Automatic Generation Technology of Safety Measures for Digital Substation Based on Improved Support Vector Machine by Yabing YAN, Xu CHU, Haolong XIAO, Wenwu LIANG, Hui LI, Zhenxing XIA

“…A digital substation safety measure automatic generation technology based on improved support vector machine is proposed to address the low efficiency of secondary maintenance safety measures in digital substations. Firstly, construct a secondary circuit model and equipment model based on adjacency matrix, and further integrate the secondary security measure rule library to form a sample dataset; Secondly, support vector machines were used to classify secondary security measures, and bacterial foraging algorithms were introduced to optimize penalty factors and kernel parameters, effectively improving the training effectiveness of the automatic generation model for security measures; Finally, the effectiveness of the proposed method was verified through numerical examples.…”
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Networks in Coronary Heart Disease Genetics As a Step towards Systems Epidemiology. by Fotios Drenos, Enzo Grossi, Massimo Buscema, Steve E Humphries

“…Using a sample of 252 middle-aged men, of which 102 had a CHD event in 10 years follow-up, we applied machine learning algorithms for the selection of CHD intermediate phenotypes, established markers, risk factors, and their previously associated genetic polymorphisms, and constructed a map of relationships between the selected variables. …”
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Will Central Bank Digital Currencies (CBDC) and blockchain cryptocurrencies coexist in the post quantum era? by Abraham Itzhak Weinberg, Pythagoras Petratos, Alessio Faccia

“…Furthermore, it features discussions of the influence of anticipated advances in quantum computing on algorithms and their applications. The paper renders the judicious conclusion that long-term coexistence is viable provided challenges are constructively addressed through ongoing collaborative efforts to validate solutions and guide evolving policies.…”
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Invariant Characteristics of Forced Oscillations of a Beam with Longitudinal Compression by Sergey D. Glyzin, Mikhail Vladimirovich Lokhanin, Dmitry Mikhailovich Sirotin

“…Based on the developed algorithms the dependence of β- statentropy on the frequency of the external action is constructed. …”
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Development of Non-Invasive Continuous Blood Pressure Measurement System Based on Multiple Feature Parameters by Mingyue LI, Zhiying YUAN, Ruowei LI, Jieying SHAN, Jilun YE, Xu ZHANG, Hui YU, Xiaoyu WU

“…A PC-based human-computer interaction software platform was constructed, and continuous blood pressure measurement-related algorithms were integrated. …”
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A comparative analysis of variants of machine learning and time series models in predicting women’s participation in the labor force by Rasha Elstohy, Nevein Aneis, Eman Mounir Ali

“…Various machine learning (ML) algorithms, such as support vector machine (SVM), neural network, K-nearest neighbor (KNN), linear regression, random forest, and AdaBoost, in addition to popular time series algorithms, including autoregressive integrated moving average (ARIMA) and vector autoregressive (VAR) models, have been applied to an actual dataset from the public sector. …”
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Soft Schemes for Earthquake-Geotechnical Dilemmas by Silvia García

“…Considering the strengths and weaknesses of the algorithms, in this work a criterion to leverage the best features to develop efficient hybrid models is presented. …”
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Deep Learning Applications in Ionospheric Modeling: Progress, Challenges, and Opportunities by Renzhong Zhang, Haorui Li, Yunxiao Shen, Jiayi Yang, Wang Li, Dongsheng Zhao, Andong Hu

“…Looking ahead, research will focus on developing hybrid models that integrate physical modeling with deep learning, exploring adaptive learning algorithms and multi-modal data fusion techniques to enhance long-term predictive capabilities, particularly in addressing the impact of climate change on the ionosphere. …”
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Identification and validation of pyroptosis-related genes in Alzheimer’s disease based on multi-transcriptome and machine learning by Yuntai Wang, Yuntai Wang, Yilin Li, Lu Zhou, Yihuan Yuan, Chuanfei Liu, Zimeng Zeng, Yuanqi Chen, Qi He, Zhuoze Wu

“…Machine learning algorithms and comprehensive bioinformatics analysis (including immune infiltration and receiver operating characteristic (ROC)) were applied to identify the hub genes. …”
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