Journal of Intelligent & Fuzzy Systems - Volume 40, issue 2

Authors: Lanlan, Pan | Liangyu, Hu | Zhengya, Li

Article Type: Research Article

Abstract: English part-of-speech intelligent recognition is the scientific and technological basis for the development of intelligent speech systems. The difficulty in the current English speech recognition system lies in the recognition of English parts of speech. In order to improve the effect of English part-of-speech recognition, this study builds the language rules and morphological models of English morphological forms based on machine learning algorithms. Moreover, this study proposes a stemming extraction algorithm and a syllable division algorithm based on English characteristic rules. By studying basic phrases in English, this study analyzes the compositional structure of phrases, and determines the basic phrase …structure and composition rules of English such as noun, verb, and adjective. In addition, this research studies the basic English phrase recognition algorithm based on the rule method and the analysis of basic phrase ambiguity resolution. Finally, this study designs a control experiment to analyze the performance of the algorithm proposed in this paper model and confirm the classification algorithm. The research results show that the algorithm proposed in this paper has a certain practical effect. Show more

Keywords: Machine learning, prediction algorithm, English, part-of-speech recognition, algorithm improvement

DOI: 10.3233/JIFS-189236

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2409-2419, 2021

Authors: Chonggao, Pang

Article Type: Research Article

Abstract: Classroom student behavior recognition has important guiding significance for the development of distance education strategies. At present, the accuracy of students’ classroom behavior recognition algorithms has problems. In order to improve the effect of distance education student status analysis, this study combines the traditional clustering analysis algorithm and the random forest algorithm to improve the traditional algorithm and combines the human skeleton model to identify students’ classroom behavior in real time. Moreover, this research combines with the needs of students’ classroom behavior recognition to build a network topology model. The error rate of feature reconstruction using spatio-temporal features is lower …than that of a single feature. Through experiments, this study verifies the effectiveness of the extracted spatial angle features based on the human skeleton model. The results of algorithm performance test show that the proposed algorithm network structure is superior to the network structure of single feature extraction algorithm. Show more

Keywords: Cluster analysis, random forest, classroom behavior, feature recognition, student behavior

DOI: 10.3233/JIFS-189237

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2421-2431, 2021

Authors: Dongmei, Li

Article Type: Research Article

Abstract: English text-to-speech conversion is the key content of modern computer technology research. Its difficulty is that there are large errors in the conversion process of text-to-speech feature recognition, and it is difficult to apply the English text-to-speech conversion algorithm to the system. In order to improve the efficiency of the English text-to-speech conversion, based on the machine learning algorithm, after the original voice waveform is labeled with the pitch, this article modifies the rhythm through PSOLA, and uses the C4.5 algorithm to train a decision tree for judging pronunciation of polyphones. In order to evaluate the performance of pronunciation discrimination …method based on part-of-speech rules and HMM-based prosody hierarchy prediction in speech synthesis systems, this study constructed a system model. In addition, the waveform stitching method and PSOLA are used to synthesize the sound. For words whose main stress cannot be discriminated by morphological structure, label learning can be done by machine learning methods. Finally, this study evaluates and analyzes the performance of the algorithm through control experiments. The results show that the algorithm proposed in this paper has good performance and has a certain practical effect. Show more

Keywords: Machine learning, English, text-to-speech conversion, improved algorithm, simulation

DOI: 10.3233/JIFS-189238

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2433-2444, 2021

Authors: Lin, Liu

Article Type: Research Article

Abstract: The difficulty of knowledge point recommendation based on the learning diagnosis model lies in how to perform feature recognition and selection of recommended knowledge points. At present, the recommendation system has certain problems in the accuracy of recommended knowledge points. Based on this, this study mainly studies the personalized problem recommendation of middle school students in the field of education. Moreover, this study takes the answer records of students’ exercises as data, and combines the characteristics of the field of education to propose an exercise recommendation algorithm based on hidden knowledge points and an exercise recommendation method based on the …decomposition of student exercise weight matrix. In addition, in order to verify the effectiveness of this research algorithm, this paper selects the accuracy rate and recall rate as evaluation indicators to analyze the recommendation results of this algorithm and the current more advanced CF algorithm, and the statistical experiment results are drawn into charts. The research results show that the method proposed in this paper has certain advantages and can be used as one of the subsystems of the learning system. Show more

Keywords: Text vector model, support vector machine, learning information, personalized recommendation

DOI: 10.3233/JIFS-189239

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2445-2455, 2021

Authors: Qianna, Sun

Article Type: Research Article

Abstract: The intelligent evaluation of classroom teaching quality is one of the development directions of modern education. At present, some teaching quality evaluation models have accuracy problems, and the evaluation process is affected by a variety of interference factors, which leads to inaccurate model results, and it is impossible to find out the specific factors that affect teaching. In order to improve the accuracy of classroom teaching quality evaluation, this study improves RVM based on the method of feature extraction and empirical modal decomposition of ACLLMD method, and establishes classroom theoretical teaching quality evaluation model and experimental teaching quality evaluation model …based on RVM algorithm. Moreover, this study uses test data to analyze the accuracy and reliability of the evaluation results to verify the feasibility and reliability of the new method. In addition, this study verifies the reliability of this algorithm by comparing with the manual scoring results. The research results show that RVM can be used to construct classroom theory teaching quality evaluation models and experimental teaching quality evaluation models with high accuracy and good reliability. Show more

Keywords: Improved algorithm, neural network, path sequencing, network teaching, knowledge recommendation

DOI: 10.3233/JIFS-189240

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2457-2467, 2021

Authors: Wenjuan, Zhang

Article Type: Research Article

Abstract: The traditional English examination and the current examination system have been unable to meet the needs of the education industry for English examinations. In view of this, based on the neural network algorithm, this study proposes a hierarchical network management model from the user’s perspective. Based on the in-depth study of the neural network, this study combined with the network performance characteristics of large data volume, complex data to propose a new BP neural network algorithm. By dynamically changing the momentum factor and learning rate, the algorithm has greatly improved the accuracy and stability of the error. In addition, this …study proposes a user perception prediction model, and the model is continuously trained on the model based on the improved BP neural network algorithm and the monitored network performance. In order to study the performance of the research model, a control experiment is designed to analyze the performance of the model. The research results show that the intelligent model and algorithm proposed in this paper are completely feasible and effective. Show more

Keywords: Neural network, English, hierarchical model, improved algorithm

DOI: 10.3233/JIFS-189241

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2469-2480, 2021

Authors: Qianyun, Yang | Xiaoyan, Wang

Article Type: Research Article

Abstract: The increasing complexity of the financial system has increased the uncertainty of the market, which has led to the complexity of the evolution of limited rational investor behavior decisions. Moreover, it also has a negative effect on the market and affects the development of the real economy and social stability. In view of the interconnected characteristics of various elements presented in financial complexity, based on complex network theory, Bayesian learning theory and social learning theory, this study systematically describes the behavioral decision-making mechanism of individual investors and institutional investors from the perspective of network learning. In addition, this study builds …an evolutionary model of investor behavior based on Bayesian learning strategies. According to the results of the horizontal and vertical bidirectional studies simulated by experiments, we can see that the method proposed in this study has a certain effect on the evaluation and decision support of stock market investment. Show more

Keywords: Bayesian learning, stock market, investment behavior, behavior simulation

DOI: 10.3233/JIFS-189242

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2481-2491, 2021

Authors: Pengyu, Wang | Wanna, Gao

Article Type: Research Article

Abstract: Basketball player detection technology is an important subject in the field of computer vision and the basis of related image processing research. This study uses machine learning technology to build a basketball sport feature recognition model. Moreover, this research mainly takes the characteristic information of basketball in the state of basketball goals as the starting point and compares and analyzes the detection methods by detecting the targets in the environment. By comprehensively considering the advantages and disadvantages of various methods, a method suitable for the subject is proposed, namely, a fast skeleton extraction and model segmentation method. The fitting effect …of this method, whether in terms of compactness or quantity, has greater advantages than traditional bounding boxes, and realizes the construction of dynamic ellipsoidal bounding boxes in a moving state. In addition, this study designs a controlled trial to verify the analysis of this research model. The research results show that the model proposed in this paper has certain effects and can improve practical guidance for competitions and basketball players training. Show more

Keywords: Machine learning, basketball, simulation model, basketball player

DOI: 10.3233/JIFS-189243

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2493-2504, 2021

Authors: Bu, Suhua

Article Type: Research Article

Abstract: In the era of the Internet of Things, smart logistics has become an important means to improve people’s life rhythm and quality of life. At present, some problems in logistics engineering have caused logistics efficiency to fail to meet people’s expected goals. Based on this, this paper proposes a logistics engineering optimization system based on machine learning and artificial intelligence technology. Moreover, based on the classifier chain and the combined classifier chain, this paper proposes an improved multi-label chain learning method for high-dimensional data. In addition, this study combines the actual needs of logistics transportation and the constraints of the …logistics transportation process to use multi-objective optimization to optimize logistics engineering and output the optimal solution through an artificial intelligence model. In order to verify the effectiveness of the model, the performance of the method proposed in this paper is verified by designing a control experiment. The research results show that the logistics engineering optimization based on machine learning and artificial intelligence technology proposed in this paper has a certain practical effect. Show more

Keywords: Machine learning, artificial intelligence, logistics, optimization

DOI: 10.3233/JIFS-189244

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2505-2516, 2021

Authors: Chen, Haixia

Article Type: Research Article

Abstract: Innovation and entrepreneurship are an important support for social and economic development in the new era, and it is also the key to the cultivation of practical talents in universities. In order to mine the effective information of innovation and entrepreneurship data, based on the neural network algorithm, this paper combines the bat algorithm to construct a data processing model to obtain an artificial intelligence innovation and entrepreneurship system with data analysis capabilities. Moreover, this study combines with actual needs to improve the algorithm, effectively eliminate the noise existing in the data, eliminate the interference of invalid data on the …judgment ability of the system model, and choose the best denoising algorithm through comparison and verification of various algorithms. In order to verify the model proposed in this paper, the data is input into this research model by collecting data in a college survey, so as to verify and analyze the performance of the model. The research results show that the artificial intelligence system proposed in this paper has good performance and has certain practical value. Show more

Keywords: Artificial intelligence, neural network, improved algorithm, innovation and entrepreneurship

DOI: 10.3233/JIFS-189245

Citation: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2517-2528, 2021