Prediction and Impact Analysis of Energy Vehicle Development Based on Nonlinear Optimization APH Method DOI

Zixu Li,

Yuhui Huang,

Ding Wen Yu

и другие.

Опубликована: Март 15, 2024

New energy electric vehicles have seen rapid growth in recent years due to their low pollution, efficiency, and peak load-shifting capabilities. However, evaluations of the developmental trends new vehicle industry remain relatively limited. In this paper, we first employed nonlinear optimization APH method construct an indicator system its weight system, thus modeling main factors influencing development vehicles. The method's consistency parameter CR is order 10 -4 , indicating high feasibility. Then, utilized ARIMA time series forecasting multiple linear regression model predict future ten years' industry. Evaluated comprehensively by assessment indicators like RMSE F-values, demonstrates precision good fitting effects. Finally, our optimized population competition innovatively analyzed interactive effects global traditional industries, two may stabilize after a period joint future, dominate.

Язык: Английский

Deep learning in motor imagery EEG signal decoding: A Systematic Review DOI
Aurora Saibene, Hafez Ghaemi, Eda Dağdevır

и другие.

Neurocomputing, Год журнала: 2024, Номер 610, С. 128577 - 128577

Опубликована: Сен. 14, 2024

Язык: Английский

Процитировано

4

The Application of Entropy in Motor Imagery Paradigms of Brain–Computer Interfaces DOI Creative Commons
Chengzhen Wu, Bo Yao, Xin Zhang

и другие.

Brain Sciences, Год журнала: 2025, Номер 15(2), С. 168 - 168

Опубликована: Фев. 8, 2025

Background: In motor imagery brain-computer interface (MI-BCI) research, electroencephalogram (EEG) signals are complex and nonlinear. This complexity nonlinearity render signal processing classification challenging when employing traditional linear methods. Information entropy, with its intrinsic nonlinear characteristics, effectively captures the dynamic behavior of EEG signals, thereby addressing limitations methods in capturing features. However, multitude entropy types leads to unclear application scenarios, a lack systematic descriptions. Methods: study conducted review 63 high-quality research articles focused on MI-BCI, published between 2019 2023. It summarizes names, functions, scopes 13 commonly used measures. Results: The findings indicate that sample (16.3%), Shannon (13%), fuzzy (12%), permutation (9.8%), approximate (7.6%) most frequently utilized features MI-BCI. majority studies employ single feature (79.7%), dual (9.4%) triple (4.7%) being prevalent combinations multiple applications. incorporation can significantly enhance pattern accuracy (by 8-10%). Most (67%) utilize public datasets for verification, while minority design conduct experiments (28%), only 5% combine both Conclusions: Future should delve into effects various specific problems clarify their scenarios. As methodologies continue evolve advance, poised play significant role wide array fields contexts.

Язык: Английский

Процитировано

0

Forensic identification of tears from different ethnic groups in China using portable infrared spectral analysis and swarm intelligence algorithms DOI

Zhu Mi,

Meizi He,

Yaoqing Chen

и другие.

Microchemical Journal, Год журнала: 2025, Номер unknown, С. 114155 - 114155

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Designing a Modified Grey Wolf Optimizer Based Cyclegan Model for Eeg Mi Classification in Bci DOI
Arunadevi Thirumalraj,

K Aravinda,

V Revathi

и другие.

Опубликована: Янв. 1, 2023

Язык: Английский

Процитировано

8

Evaluation of English Speech Interaction Quality Based on Deep Learning DOI

Lihong Du

Опубликована: Фев. 23, 2024

In order to improve the traditional computer English pronunciation quality assessment method, this paper uses spoken of university students in China as research object, and examines various measures such intonation accuracy, speaking rate, rhythm, intonation. Intonation is measured by Mel-frequency cepstral characteristic expression, speech rate according time, rhythm evaluated short-term power pair variation index, base frequency. Based on evaluation indicators quality, article develops an model based DBN. Experiments were conducted performance model, test results showed that recognition DBN developed was 96.65%, which better than other models. addition, consistency experiments between machine manual evaluation, total value 87.5%, environmental similarity level 100%, Pearson correlation coefficient 0.722, indicating evaluation.

Язык: Английский

Процитировано

1

Optimal Allocation of Innovation and Entrepreneurship Education Resources in Colleges and Universities Based on Pso Algorithm DOI

Liu Jue

Опубликована: Фев. 23, 2024

Under the background of knowledge economy and globalization, entrepreneurship education in colleges universities has become an important force to promote economic development social progress. Optimizing allocation educational resources stimulating students' innovative spirit practical ability are key directions current higher reform. This paper will discuss how cultivate talents meet needs future society through optimizing resource universities.

Язык: Английский

Процитировано

1

Construction of STEAM Personalized Online Learning System for Artificial Intelligence DOI
Lan Ma

Опубликована: Фев. 23, 2024

Traditional online learning systems have long system response times and low accuracy in predicting learners' behavior, results, or personalized needs. In order to optimize the article on this issue, a STEAM for artificial intelligence is constructed. This research adopts combination of technology data analysis methods construction. First, learner's personal information, behavior results other are collected, effective carried out. Secondly, application recommendation algorithms intelligent models recommend content, projects activities suitable individual needs based their interests, abilities history. Through experimental tests, mean square error paper maintained at 0.01-0.05, can improve user experience, effect performance.

Язык: Английский

Процитировано

1

Three-Dimensional Convolutional Neural Network for Wheat Rust Disease Classification DOI

N Jagadeeshan,

Y. Nagendar,

K. S. Swarnalatha

и другие.

Опубликована: Март 15, 2024

In worldwide, the wheat is a significant crop which generates main source of food for numerous peoples. Through, development productions vulnerable through various diseases such as bacterial, viral and fungal infections. These type disease can cause important damage in crops leads to diminish yield production grain quality. This paper proposed Three-Dimensional Convolutional Neural Network (3D-CNN) rust classification that learns recognize pattern structure using convolution filter layers. The CGIAR dataset used contains 1486 images it pre-processed by gaussian reduces noise smoothens image. Then, Discrete Wavelet Transform (DWT) feature extraction works discrete timespan outputs low computational cost. 3D-CNN disease. performance estimated accuracy, recall, f1score precision. attains accuracy 99.83%, recall 98.89%, 98.81 % precision 98.79 % when compared existing techniques like GNet+FERSPNET-50 Few-shot learning based EfficientNet.

Язык: Английский

Процитировано

1

Design of Network Public Opinion Monitoring System based on LDA Model DOI
Li Wang

Опубликована: Фев. 23, 2024

Network public opinion has the characteristics of suddenness, easy dissemination, and uncontrollability. With help new generation information technology, ability to effectively accurately improve network governance can be improved. The Dirichlet distribution is a multivariate beta distribution, there conjugate relationship between polynomial distributions. This article based on basic ideas LDA model, constructs model topology structure, studies core algorithm composed Gibbs sampling TF-IDF feature weight algorithm, conducts experimental design result analysis. At same time, functional structure analysis system was designed, providing guidance for software development. research results are used construction online culture, strengthen opinion, enhance respond decision-making level.

Язык: Английский

Процитировано

0

Research on English Wisdom Teaching Quality Evaluation based on RBF Neural Network Algorithm DOI
Bingbing Zhang

Опубликована: Фев. 23, 2024

With the continuous development of science and technology, field education is constantly undergoing reform innovation. Among them, wisdom teaching, as a new teaching mode, has gradually become hot topic in education. Wisdom refers to optimal allocation educational resources improvement quality effect by means modern information technology. In English increasingly widely used. This paper will discuss evaluation order provide some reference for educators.

Язык: Английский

Процитировано

0