Journal of Intelligent & Fuzzy Systems - Volume 40, issue 4

Authors: Longjiang, Duan

Article Type: Research Article

Abstract: English vocabulary recognition has certain applications in both learning and life. The existing English vocabulary recognition model is limited by a variety of factors, which will result in a more complicated recognition process and a low recognition accuracy. In order to improve the effect of English vocabulary recognition, based on natural language processing algorithms and corpus systems, this paper proposes a multi-feature fusion adaptive kernel-related filter tracking algorithm for the problems of kernel-related filtering algorithms. Moreover, based on the KCF algorithm, this paper improves the algorithm from three parts: feature fusion, adaptive change of update rate, and scale detection. In …addition, this paper explores whether the vocabulary recognition of different rhythms will affect the reaction time and accuracy of the second language vocabulary recognition when the test subjects are in the experimental conditions with similar characters and different voices. The research results show that the model constructed in this paper performs well in the recognition of English words. Show more

Keywords: Natural language, corpus, English vocabulary, vocabulary recognition

DOI: 10.3233/JIFS-189537

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7073-7084, 2021

Authors: Gang, Zhang

Article Type: Research Article

Abstract: At present, the posterior probability measure widely used in English speech recognition has the situation that the posterior probability measure of different phonemes cannot be consistent to measure the pronunciation quality of the phoneme and the acoustic modeling method of voice recognition is inconsistent with the evaluation target. Therefore, in order to improve the evaluation effect of English pronunciation quality in colleges and universities, this article is based on artificial emotion recognition and high-speed hybrid model to analyze and filter various clutters that affect speech quality to improve students’ English speech recognition. Moreover, this article uses the characteristics of the …clutter and the target in the data to conform to different distributions and based on the clutter distribution characteristics obtained by statistics, this article realizes the suppression of the clutter to improve the target detection performance. In addition, the method proposed in this paper solves the limitations of the clutter suppression technology in the traditional voice detection system and improves the target detection performance. In order to study the pronunciation quality evaluation effect of this model and its effect in English teaching, this paper designs a controlled experiment to analyze the model’s performance. The research results show that the model constructed in this paper has good performance. Show more

Keywords: Artificial emotion recognition, Gaussian mixture model, English pronunciation, quality evaluation

DOI: 10.3233/JIFS-189538

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7085-7095, 2021

Authors: Han, Yongqing

Article Type: Research Article

Abstract: The English online teaching automatic evaluation system is unstable in actual teaching evaluation. Therefore, how the automatic evaluation system can better adapt to high school teaching also needs a more in-depth theoretical and practical discussion. According to the actual needs of English online teaching, this article combines remote supervision and deep learning algorithms, builds a system structure for the English online teaching evaluation process, and simulates and analyzes the application of supervision algorithms in the teaching process. Moreover, this article evaluates the actions and status of the student’s learning process from the aspects of teacher evaluation and student evaluation, and …also scores the teacher’s teaching process. In order to study the practical effect of this system in English online teaching, this paper designs experiments to evaluate the model online English teaching effect. The research results show that the model constructed in this paper has good performance. Show more

Keywords: Remote supervision, deep learning, English teaching, online teaching, evaluation

DOI: 10.3233/JIFS-189539

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7097-7108, 2021

Authors: Jiang, Zhou | Wei, Zhenwu

Article Type: Research Article

Abstract: Grassland resources are an important part of land resources. Moreover, it has the functions of regulating the climate, windproof and sand fixation, conserving water sources, maintaining water and soil, raising livestock, providing food, purifying the air, and beautifying the environment in terrestrial ecosystems. Grassland resource evaluation is of great significance to the sustainable development of grassland resources. Therefore, this paper improves the BP neural network, uses the comprehensive index method to calculate the weights in the analytic hierarchy process, and constructs a water resources carrying capacity research and analysis system based on the entropy weight extension decision theory. Meanwhile, this …paper analyzes different levels of resource and environmental carrying capacity to achieve the purpose of comprehensive evaluation of resource and environmental carrying capacity. In addition, based on the theory of sustainable development, under the guidance of the principle of index system construction, this paper studies the actual situation of grassland resources and the availability and operability of data, and combines with the opinions given by experts to form an evaluation index system of grassland resources and environmental carrying capacity. Finally, through the actual case study analysis, it is concluded that the model constructed in this paper has a certain effect. Show more

Keywords: BP neural network, improved algorithm, analytic hierarchy process, grassland resources

DOI: 10.3233/JIFS-189540

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7109-7120, 2021

Authors: Wang, Xinhua | Chen, Guanyu | Gong, Huajun | Jiang, Ju

Article Type: Research Article

Abstract: At present, the UAV swarm positioning solution has the problems of poor positioning accuracy and instability. Therefore, it is necessary to design a sliding mode formation controller to realize formation. This study analyzes the self-service control strategy of the UAV swarm and establishes the behavior-based formation control strategy as the main research point of this article. This paper combines the Internet of Things and artificial intelligence algorithms to build an autonomous control model for the UAV swarm and designs the UAV formation control law from the disturbed and undisturbed conditions respectively. With reference to the basic architecture of the Internet …of Things, this study imitates ZigBee’s self-organizing network to propose an adaptive networking scheme based on the Internet of Things by using the AP+STA working mode of the Internet of Things module in the node device. The results of the experiment show that the positioning accuracy of the UAV is high, which can meet the needs of cluster flight. Based on the Z-axis coordinates of the UAV, the accuracy of the laser distance measurement and the barometer value is significantly improved, the root mean square error is reduced, and the positioning result is significantly better than the data of direct traditional positioning. Show more

Keywords: Internet of things, artificial intelligence, UAV, cluster, autonomous control

DOI: 10.3233/JIFS-189541

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7121-7133, 2021

Authors: Ma, Xiangfei

Article Type: Research Article

Abstract: The sustainable economic learning course recommendation can quickly find the knowledge information that the user really needs from the massive information space and realize the personalized recommendation to the user. However, the occurrence of trust attacks seriously affects the normal recommendation function of the recommendation system, resulting in its failure to provide users with reliable and reliable recommendation results. In order to solve the vulnerability of the recommendation system to the support attack, based on text vector model and support vector machine, this paper makes a comprehensive analysis of the current research status of the robust recommendation technology. Moreover, based …on the idea of suspicious user metrics, this paper has conducts in-depth research on how to design highly robust recommendation algorithms, and constructs a highly reliable sustainable economic learning course recommendation model. In addition to this, this research tests the performance of the system from two perspectives of course recommendation satisfaction and system retrieval accuracy. The experiment proves that the model constructed in this paper performs well in the recommendation of sustainable economic learning courses. Show more

Keywords: Text vector model, support vector machine, sustainable economy, system construction

DOI: 10.3233/JIFS-189542

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7135-7145, 2021

Authors: Diao, Lijing | Hu, Ping

Article Type: Research Article

Abstract: On the basis of convolution neural network, deep learning algorithm can make the convolution layer convolute the input image to complete the hierarchical expression of feature information, which makes pattern recognition more simple and accurate. Now, in the theory of multimodal discourse analysis, the nonverbal features in communication are studied as a symbol system similar to language. In this paper, the author analyzes the deep learning complexity and multimodal target recognition application in English education system. Multimodal teaching gradually has its practical significance in the process of rich teaching resources. The large-scale application of multimedia technology in college English classroom …is conducive to the construction of a real language environment. The simulation results show that the multi-layer and one-dimensional convolution structure of the product neural network can effectively complete many natural language problems, including the tagging of lexical and semantic roles, and thus effectively improve the accuracy of natural language processing. Multimodal teaching mode helps to memorize vocabulary images more deeply. 84% of students think that multi-modal teaching mode is closer to life. Meanwhile, multimedia teaching display is more acceptable. College English teachers should renew their teaching concepts and adapt themselves to the new teaching mode. Show more

Keywords: Deep learning, multimodal target recognition, information technology, artificial intelligence

DOI: 10.3233/JIFS-189543

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7147-7158, 2021

Authors: Chen, Zijuan | Lian, Ying | Lin, Zhipeng

Article Type: Research Article

Abstract: Due to various factors, the learning process of business English is mostly autonomous learning. However, the traditional autonomous learning model is difficult to effectively improve the learning effect of business English. In order to improve the business English learning model, based on artificial intelligence and improved BP network model, this paper builds a business intelligence autonomous learning system with certain intelligence. Moreover, this paper designs functional modules for the characteristics of business English learners, and combines the self-learning needs to facilitate the processing of structural functions, so that students can complete the operation independently. The system sets up multiple functional …modules, conducts guided recommendation learning according to the characteristics of the self-learning process, and combines the feedback system to correct the shortcomings in students’ autonomous learning. Through this system, teachers can perform a variety of operations offline and eliminate restrictions on location and teaching time. In addition, in order to verify the performance of the model, the experimental study was conducted by setting up a control group and an experimental group. The research results show that the model constructed in this paper has good performance. Show more

Keywords: Artificial intelligence, improved algorithm, BP neural network, business English

DOI: 10.3233/JIFS-189544

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7159-7170, 2021

Authors: Xinhan, Nie

Article Type: Research Article

Abstract: Classroom teaching in the context of artificial intelligence needs to be combined with modern intelligent recognition technology to improve classroom teaching efficiency. In order to study the auxiliary teaching system for classroom student management, this article is based on neural network technology and emotional feature recognition algorithm, and according to the actual situation of classroom teaching, an intelligent analysis system for classroom student status is constructed. The system simulates the RFID mode to tag the students. Moreover, this article sets the system function module according to the actual teaching management needs and designs the learning algorithm of the quantitative assessment …model. In addition, this study uses machine learning methods to design the quantitative evaluation index system, logistic regression scoring algorithm and model training algorithm. Finally, this study uses the neural network algorithm as the comparison algorithm to verify the performance of the constructed model and analyzes the comparison results through chart comparison. The research results show that the model proposed in this paper has good performance and can be applied to practical classrooms. Show more

Keywords: Neural network, emotion recognition, student status, intelligent recognition

DOI: 10.3233/JIFS-189545

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7171-7182, 2021

Authors: Zhang, Mei | Zhang, Lijun

Article Type: Research Article

Abstract: Cross-cultural English teaching is limited by the influence of traditional teaching models, resulting in poor teaching results. In order to improve the efficiency of cross-cultural English teaching, with the support of AI emotion recognition and neural network algorithm, this paper builds a cross-cultural O2O English teaching system with intelligent recognition and management. Moreover, this research uses background models to detect and track targets, to realize the full recognition of students’ emotions, and to facilitate teachers to effectively control online teaching. In addition, combined with online and offline teaching, this study uses neural network algorithm to stabilize the system and perform …data processing, construct an overall O2O English teaching model according to actual needs, and formulate the corresponding teaching process. In order to verify the performance of the model, this study starts from two aspects: system performance test and system practice effect and uses statistical methods to collect and process data. The test results show that the model constructed in this paper has good performance and meets expectations. Show more

Keywords: AI emotion recognition, neural network, cross-cultural, English teaching, O2O

DOI: 10.3233/JIFS-189546

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 4, pp. 7183-7194, 2021