Digital education as a new pedagogical paradigm by Fatima Anzaurovna Tuguz

“…Key findings: the introduction of digital education into a university environment has been considered in two contexts: as a necessary content of education and as a means of teaching; the main features of digital education focus on consumer preferences, organization of rational user interaction, algorithmized interaction of its users, remote work with information resources, network interaction, etc.; infection for various consumer groups; the ability to operate on different means and compatibility with other applications; the prospects for digital education are the construction of an ergonomic communicative environment of an educational institution, the possession of digital competencies by all subjects of education; motivation of scientific and pedagogical personnel to work in a new educational environment, updating academic disciplines, etc.…”
Get full text

Opportunities of Digitalization of Economic Subjects in Educational Process by L. N. Babkina, O. V. Skotarenko

“…In the conditions of the accelerated development of scientific and technical progress, and, first of all, information and computer technologies in scales not only one concrete country, and all set of the developed countries which are in a stage of a post-industrial service state, creation of intercountry communications, the great value is gained by a position of the higher education. Thus, institutions of higher professional education should become so-called points of growth or locomotives of growth of the level of application of information and computer technologies, algorithms for solving economic and management problems based on the use of economic and mathematical methods and models that students master in the process of studying the relevant disciplines. …”
Get full text

Research on multi-UAV autonomous obstacle avoidance algorithm integrating improved dynamic window approach and ORCA by Xucheng Chang, Jingyu Wang, Kang Li, Xinhui Zhang, Qian Tang

“…Simulation experiments were conducted to verify the effectiveness of the proposed improved fusion algorithm. Compared with the conventional DWA algorithm, the proposed method achieved a 27.90% reduction in UAV flight path length, a 17.01% decrease in mission completion time, and a 21.5% reduction in iteration counts. …”
Get full text

Application of Genetic Algorithms to Solve MTSP Problems with Priority (Case Study at the Jakarta Street Lighting Service) by Sugih Sudharma Tjandra, Fran Setiawan, Hanoum Salsabila

“…Because, in this case, the delivery capacity is not taken into account, the priority of the lights visited is random, and the number of street light points is enormous, in this study, we use the MTSP method with priority and solve by a genetic algorithm assisted by the nearest neighbor algorithm. …”
Get full text

PSO-NMPC control strategy based path tracking control of mining LHD (scraper) by Ya Liu, Ping-an Peng, Li-guan Wang, Jia-xi Wu, Ming-yu Lei, Chao-wei Zhang, Ru Lei

Subjects: Get full text

Artificial Intellect Systems in Today’s Economic Environment by N. V. Barinova, V. R. Barinov

Subjects: Get full text

Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction by Ali Hassan, Guilherme Vieira Hollweg, Wencong Su, Xuan Zhou, Mengqi Wang

“…Compared with energy management with no consideration of degradation or demand charge reduction, this algorithm results in 71% less degradation of BESS and 57.3% demand charge reduction for the industrial consumer.…”
Get full text

A Novel Energy Consumption Prediction Model Integrating Real-Time Traffic State Recognition and Velocity Prediction of BEVs by Yue Li, Yu Jiang, Jianhua Guo, Dong Xie

“…The widespread adoption of battery electric vehicles (BEVs) has highlighted the critical importance of precise energy consumption prediction models to address the problem of range anxiety among drivers. …”
Get full text

Optimization of Business Processes in E-Commerceusing Artificial Intelligence Methods and Algorithms by E. S. Piskun, D. V. Nuansengsy, E. N. Kotsko

“…The paper discusses methods and algorithms of artificial intelligence aimed at automating and optimizing business processes in e-commerce. …”
Get full text

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study. by Michael King, Louise Marston, Igor Švab, Heidi-Ingrid Maaroos, Mirjam I Geerlings, Miguel Xavier, Vicente Benjamin, Francisco Torres-Gonzalez, Juan Angel Bellon-Saameno, Danica Rotar, Anu Aluoja, Sandra Saldivia, Bernardo Correa, Irwin Nazareth

“…<h4>Conclusions</h4>The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.…”
Get full text

Adaptive Sensor Activation Algorithm for Target Tracking in Wireless Sensor Networks by Wei Zhou, Weiren Shi, Xiaogang Wang, Kai Wang

“…In this paper, we propose an energy-efficient sensor activation protocol based on predicted region technique, called predicted region sensor activation algorithm (PRSA). …”
Get full text

Interpretable Reinforcement Learning for Sequential Strategy Prediction in Language-Based Games by Jun Zhao, Jintian Ji, Robail Yasrab, Shuxin Wang, Liang Yu, Lingzhen Zhao

“…However, existing models often struggle with poor adaptability and limited interpretability when applied to dynamic language prediction tasks such as <b>Wordle</b>. To address these challenges, this study proposes an interpretable reinforcement learning framework based on an Enhanced Deep Deterministic Policy Gradient (Enhanced-DDPG) algorithm. …”
Get full text

Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms by Farman Ullah Khan, Faridoon Khan, Parvez Ahmed Shaikh

“…Abstract The study aims at forecasting the return volatility of the cryptocurrencies using several machine learning algorithms, like neural network autoregressive (NNETAR), cubic smoothing spline (CSS), and group method of data handling neural network (GMDH-NN) algorithm. …”
Get full text

Hybrid Human and Machine Learning Algorithms to Forecast the European Stock Market by Germán G. Creamer, Yasuaki Sakamoto, Jeffrey V. Nickerson, Yong Ren

“…Additionally, this paper shows that the groups of humans, algorithms, and expert weighting algorithms have associated with them, particularly, news topics that these groups are good at making predictions from.…”
Get full text

Compression Index Regression of Fine-Grained Soils with Machine Learning Algorithms by Mintae Kim, Muharrem A. Senturk, Liang Li

“…This study employs machine learning algorithms—the random forest regressor (RFR), gradient boosting regressor (GBR), and AdaBoost regressor (ABR)—to predict the <i>C_c</i> values based on a dataset comprising 915 samples. …”
Get full text

Novel three‐dimensional ECG algorithm for reliable screening for cardiac amyloidosis by Amir A. Mahabadi, Jan Knobeloch, Viktoria Backmann, Lars Michel, Markus S. Anker, Reza Wakili, Christian Fach, Stefan D. Anker, Tienush Rassaf

“…In the derivation cohort, the AI algorithm reached a sensitivity of 85%, a specificity of 89%, a positive predictive value of 91%, and a negative predictive value of 87%. …”
Get full text

An Extended Firefly Algorithm for Enhanced Information Diffusion with Multi-Factor Considerations by Amjad Alloush, Ghaida Rebdawi:, Mohammad Saeed Abou Trab

“…Understanding and predicting how information spreads in online social networks is a crucial yet complex task, especially with the growing influence of content type, user engagement, and social dynamics. …”
Get full text

Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…Abstract Predicting agricultural commodity prices is inherently complex due to factors such as perishability, seasonality, and market volatility. …”
Get full text

Optimizing PEMFC parameter identification using improved pufferfish algorithm and CNN by Ji Li, Changiz Bastani

“…In this research, a novel approach has been proposed for enhancing the accuracy of proton exchange membrane fuel cell (PEMFC) models based on convolutional neural networks (CNNs) and an improved optimization method (called the improved pufferfish optimization algorithm). This method has been suggested to improve the predictive performance of the model by optimizing the estimation of PEMFC parameters. …”
Get full text

The Improvement Based on the DV-Hop Localization Algorithm for Wireless Sensor Networks by DONG Jing-wei, YANG Guang, LIU Yang, Zhang Tian-qi

Get full text