In recent years, there are many problems in the study of intelligent simulation of children's psychological path selection, among which the main problem is to ignore the factors of children's psychological path selection. Based on this, this paper studies the application of chaotic neural network algorithm in children's mental path selection. First, an intelligent simulation model for children's mental path selection based on chaotic neural network algorithm is established; second, it will combine the network based on different types of visual analysis strategies. The model is used to analyze the influencing factors of children in different regions in the choice of psychological paths. Finally, experiments are designed to verify the actual application effect of the simulation model. The results show that compared with the current mainstream intelligent simulation methods with iterative loop algorithms as the core, it adopts the intelligent simulation model based on the chaotic neural network algorithm has a good classification effect. It can effectively select the optimal psychological path according to the differences in children's personality and can adaptively classify children in different regions, and the experimental results are accurate. Compared with the traditional method, it is improved by at least 37%.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494551 | PMC |
| http://dx.doi.org/10.1155/2021/5321153 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Bioelectronic osteosynthesis plate to monitor the fracture bone healing using electric capacitive variations.
J Orthop Surg Res
January 2025
Department of Mechanical Engineering, Centre for Mechanical Technology & Automation (TEMA), University of Aveiro, Aveiro, 3810-193, Portugal.
Background: Bone fractures represent a global public health issue. Over the past few decades, a sustained increase in the number of incidents and prevalent cases have been reported, as well as in the years lived with disability. Current monitoring techniques predominantly rely on imaging methods, which can result in subjective assessments, and expose patients to unnecessary cumulative doses of radiation.
View Article and Find Full Text PDFStudy of the mechanical compression properties of Rosa sterilis S.D. Shi based on FEM.
Sci Rep
January 2025
School of Mechanical & Electrical Engineering, Guizhou Normal University, Guiyang, China.
Understanding the mechanical properties of Rosa sterilis S.D. Shi is important for the design and improvement of related mechanical equipment for planting, picking, processing, and transporting Rosa sterilis S.
View Article and Find Full Text PDFDynamic simulation of breast behaviour during different activities based on finite element modelling of multiple components of breast.
Sci Rep
January 2025
School of Fashion and Textiles, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China.
This study presents an advanced dynamic finite element (FE) model of multiple components of the breast to examine the biomechanical impact of different types of physical activities and activity intensity on the breast tissues. Using 4D scanning and motion capture technologies, dynamic data are collected during different activities. The accuracy of the FE model is verified based on relative mean absolute error (RMAE), and optimal material parameters are identified by using a validated stepwise grid search method.
View Article and Find Full Text PDFA guidance to intelligent metamaterials and metamaterials intelligence.
Nat Commun
January 2025
ZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou, China.
The bidirectional interactions between metamaterials and artificial intelligence have recently attracted immense interest to motivate scientists to revisit respective communities, giving rise to the proliferation of intelligent metamaterials and metamaterials intelligence. Owning to the strong nonlinear fitting and generalization ability, artificial intelligence is poised to serve as a materials-savvy surrogate electromagnetic simulator and a high-speed computing nucleus that drives numerous self-driving metamaterial applications, such as invisibility cloak, imaging, detection, and wireless communication. In turn, metamaterials create a versatile electromagnetic manipulator for wave-based analogue computing to be complementary with conventional electronic computing.
View Article and Find Full Text PDFElucidating the potential of EGFR mutated NSCLC and identifying its multitargeted inhibitors.
Sci Rep
January 2025
Amrita School of Artificial Intelligences, Coimbatore, Amrita Vishwa Vidyapeetham, Coimbatore, India.
Lung cancer is the leading cause of cancer-related fatalities globally, accounting for the highest mortality rate among both men and women. Mutations in the epidermal growth factor receptor (EGFR) gene are frequently found in non-small cell lung cancer (NSCLC). Since curcumin and CB[2]UN support various medicinal applications in drug delivery and design, we investigated the effect of curcumin and CB[2]UN-based drugs in controlling EGFR-mutant NSCLC through a dodecagonal computational approach.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!